Vide Item No 623 R BE information Technolology Sem VII VIII CBCS Rev 2019 C Scheme_1 Syllabus Mumbai University

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Copy to : -
1. The Deputy Registrar, Academic Authorities Meetings and Services
(AAMS),
2. The Deputy Registrar, College Affiliations & Development
Department (CAD),
3. The Deputy Registrar, (Admissions, Enrolment, Eligibility and
Migration Department (AEM),
4. The Deputy Registrar, Research Administration & Promotion Cell
(RAPC),
5. The Deputy Registrar, Executive Authorities Section (EA),
6. The Deputy Registrar, PRO, Fort, (Publi cation Section),
7. The Deputy Registrar, (Special Cell),
8. The Deputy Registrar, Fort/ Vidyanagari Administration Department
(FAD) (VAD), Record Section,
9. The Director, Institute of Distance and Open Learni ng (IDOL Admin),
Vidyanagari,
They are requested to treat this as action taken report on the concerned
resolution adopted by the Academic Council referred to in the above circular
and that on separate Action Taken Report will be sent in this connection.

1. P.A to Hon’ble Vice -Chancellor,
2. P.A Pro -Vice-Chancellor,
3. P.A to Registrar,
4. All Deans of all Faculties,
5. P.A to Finance & Account Officers, (F.& A.O),
6. P.A to Director, Board of Examinations and Evaluation,
7. P.A to Director, Innovation, Incubation and Linkages,
8. P.A to Director, Board of Lifelong Learning and Extension (BLLE),
9. The Director, Dept. of Information and Communication Technology
(DICT) (CCF & UCC), Vidyanagari,
10. The Director of Board of Student Development,
11. The Director, Dep artment of Students Walfare (DSD),
12. All Deputy Registrar, Examination House,
13. The Deputy Registrars, Finance & Accounts Section,
14. The Assistant Registrar, Administrative sub -Campus Thane,
15. The Assistant Registrar, School of Engg. & Applied Sciences, Kalyan ,
16. The Assistant Registrar, Ratnagiri sub -centre, Ratnagiri,
17. The Assistant Registrar, Constituent Colleges Unit,
18. BUCTU,
19. The Receptionist,
20. The Telephone Operator,
21. The Secretary MUASA

for information.

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AC – 11 July, 2022
Item No. – 6.23 (R)





University of Mumbai








Revised Syllabus for
B.E. (Information Technology )
(Sem. - VII to VIII)
(Choice Based Credit System)





(With effect from the academic year 2022 -23)

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Preamble


To meet the challenge of ensuring excellence in engineering education, the issue of quality needs to be
addressed, debated and taken forward in a systematic manner. Accreditation is the principal means of
quality assurance in higher education. The major emphasis of accreditation process is to measure the
outcomes of the program that is being accredited. In line with this Faculty of Science and Technology (in
particular Engineering)of University of Mumbai has taken a lead in incorporating philosophy of outcome
based education in the process of curriculum development.
Faculty resolved that course objectives and course outcomes are to be clearly defined for each course, so
that all facul ty members in affiliated institutes understand the depth and approach of course to be taught,
which will enhance learner‘s learning process. Choice based Credit and grading system enables a much -
required shift in focus from teacher -centric to learner -centr ic education since the workload estimated is
based on the investment of time in learning and not in teaching. It also focuses on continuous evaluation
which will enhance the quality of education. Credit assignment for courses is based on 15 weeks teaching
learning process, however content of courses is to be taught in 13 weeks and remaining 2 weeks to be
utilized for revision, guest lectures, coverage of content beyond syllabus etc.
There was a concern that the earlier revised curriculum more focused on pro viding information and
knowledge across various domains of the said program, which led to heavily loading of students in terms
of direct contact hours. In this regard, faculty of science and technology resolved that to minimize the
burden of contact hours, total credits of entire program will be of 170, wherein focus is not only on
providing knowledge but also on building skills, attitude and self learning. Therefore in the present
curriculum skill based laboratories and mini projects are made mandatory acr oss all disciplines of
engineering in second and third year of programs, which will definitely facilitate self learning of students.
The overall credits and approach of curriculum proposed in the present revision is in line with AICTE
model curriculum.
The present curriculum will be implemented for Second Year of Engineering from the academic year
2020 -21. Subsequently this will be carried forward for Third Year and Final Year Engineering in the
academic years 2021 -22, 2022 -23, respectively.






Dr. S. K. Ukarande Dr. Anuradha Muzumdar
Associate Dean DeanFaculty of Scien ce and Technology Faculty of Science
and TechnologyUniversity of MumbaUniversity of Mumbai

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Incorporation and Implementation of Online Contents from NPTEL/
Swayam Platform



The cur riculum revision is mainly focused on knowledge component, skill based activities and project based
activities. Self learning opportunities are provided to learners. In the revision process this time in particular
Revised syllabus of ‗C ‗ scheme wherever p ossible additional resource links of platforms such as NPTEL,
Swayam are appropriately provided. In an earlier revision of curriculum in the year 2012 and 2016 in
Revised scheme ‗A' and ‗B' respectively, efforts were made to use online contents more approp riately as
additional learning materials to enhance learning of students.
In the current revision based on the recommendation of AICTE model curriculum overall credits are
reduced to 171, to provide opportunity of self learning to learner. Learners are no w getting sufficient time
for self learning either through online courses or additional projects for enhancing their knowledge and skill
sets.
The Principals/ HoD‘s/ Faculties of all the institute are required to motivate and encourage learners to use
additional online resources available on platforms such as NPTEL/ Swayam. Learners can be advised to
take up online courses, on successful completion they are required to submit certification for the same. This
will definitely help learners to facilitate their enhanced learning based on their interest.





Dr. S. K. Ukarande Dr Anuradha Muzumdar
Associate Dean Dean
Faculty of Science and Technology Faculty of Science and Technology
University of Mumbai University of Mumbai

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Preface By Bo ard of Studies Team

It is our honor and a privilege to present the Rev-2019 ‗C‘ scheme syllabus of Bachelor of
Engineering in InformationTec hnology (effective from year 2019 -20) with inclusion of cutting edge
technology.Information Techno logy is comparatively a young branch among other engineering
disciplines in the Universityof Mumbai. It is evident from the placement statistics of various colleges
affiliated to the University of Mumbaithat IT branch has taken the lead in the placement.

The branch also provides multi -faceted scope like betterplacement and promotion of
entrepreneurship culture among students, and increased Industry InstituteInteractions.Industries
views are considered as stakeholders will design of the syllabus of Informa tion Technology. As per
Industries views only 16 % graduates are directly employable. One of the reasons is a syllabus which
isnot in line with the latest technologies. Our team of faculties has tried to include all the latest
technologies in thesyllabus. Also first time we are giving skill -based labs and Mini -project to
students from third semester onwards which will help students to work on latest IT technologies.
Also the first time we are giving the choice of elective from fifth semester such that stude nts will
bemaster in one of the IT domain.The syllabus is peer reviewed by experts from reputed industries
and as per their suggestions it covers futuretrends in IT technology and research opportunities
available due to these trends.

We would like to thank senior faculties of IT department of all colleges affiliated to University of
Mumbai forsignificant contribution in framing the syllabus. Also on behalf of all faculties we thank
all the industry experts fortheir valuable feedback and suggestions. We sincerely hope that the
revised syllabus will help all graduate engineers to face the future challenges in thefield of
information and technology


Program Specific Outcome for graduate Program in Information Technology

1. ApplyCore Inform ation Technology knowledge to develop stable and secure IT system.
2. Design, IT infrastructures for an enterprise using concepts of best practices in information
Technology and security domain .
3. Ability to work in multidisciplinary projects and make it IT enabled.
4. Ability to adapt latest trends and technologies like Analytics, Blockchain, Cloud, Data science.




Board of Studies in Information Technology - Team
Dr. Deven Shah ( Chairman)
Dr. Lata Ragha (Member)
Dr. Vaishali D. Khairnar (Member)
Dr. Sharvari Govilkar (Member)
Dr. Sunil B. Wankhade (Member)
Dr. Anil Kale (Member)
Dr. Vaibhav Narwade (Member)
Dr. GV Choudhary (Member)



Ad-hoc Board Information Technology
University of Mumbai

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Program Structure for Fourth Year Information Technology
Semester VII & VIII
UNIVERSITY OFMUMBAI
(With Effect from2022 -2023)
Semester VII

Course
Code
Course Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
ITC701 AI and DS –II 3 -- 3 -- 3
ITC702 Internet of Everything 3 -- 3 3
ITDO701
X Department Optional
Course – 3 3 -- 3 -- 3
ITDO702
X Department
Optional Course –4 3 -- 3 -- 3
ITIO701 X Institute Optional
Course – 1 3 -- 3 -- 3
ITL701 Data Science Lab -- 2 -- 1 1
ITL702 IOE Lab -- 2 -- 1 1
ITL703 Secure Application
Development -- 2 -- 1 1
ITL704 Recent Open Source
Project Lab -- 2 -- 1 1
ITP701 Major Project I -- 6# -- 3 3
Total 15 14 15 7 22



Course
Code


Course Name Examination Scheme
Theory Term
Work Prac/o
ral Total

Internal Assessment End
Sem
Exam Exam.
Duration
(in Hrs)
Test1 Test2 Avg
ITC701 AI and DS –II 20 20 20 80 3 -- -- 100
ITC702 Internet of Everything 20 20 20 80 3 -- -- 100
ITDO701
X Department
Optional Course –3 20 20 20 80 3 -- -- 100
ITDO702
X Department
Optional Course –4 20 20 20 80 3 -- -- 100
ILO701X Institute Optional
Course – 1 20 20 20 80 3 -- -- 100
ITL701 Data Science Lab -- -- -- -- -- 25 25 50
ITL702 IOE Lab -- -- -- -- -- 25 25 50
ITL703 Secure Application
Development -- -- -- -- -- 25 25 50
ITL704 Recent Open Source
Project Lab -- -- -- -- -- 25 25 50

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ITP701 Major Project I -- -- -- -- -- 25 25 50
Total -- -- 100 400 -- 125 125 750
# indicates work load of Learner (Not Faculty), for Major Project

ITDO701X Department Optional Course –3
ITDO701 1 Storage Area Network
ITDO701 2 High Performance computing
ITDO701 3 Infrastructure Security
ITDO701 4 Software Testing and QA


ITDO702X Department Optional Course –4
ITDO702 1 MANET
ITDO702 2 AR – VR
ITDO702 3 Quantum Computing
ITDO702 4 Information Retrieval System
# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VII, which is
not closely allied to their disciplines. Different sets of courses will run in the both
the semesters.


ILO701X Institute Optional Course – 1 ( Common for all branches will be notified )
ILO7011 Product Lifecycle Management
ILO7012 Reliability Engineering
ILO7013 Management Information System
ILO7014 Design of Experiments
ILO7015 Operation Research
ILO7016 Cyber Security and Laws
ILO7017 Disaster Management and Mitigation
Measures
ILO7018 Energy Audit and Management
ILO7019 Development Engineering

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Program Structure for Fourth Year Information Technology Semester
VII & VIII
UNIVERSITY OFMUMBAI
(With Effect from2022 -2023)
Semester VIII

Course
Code
Course Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
ITC801 Blockchain and DLT 3 -- 3 -- 3
ITDO801
X Department Optional Course – 5 3 -- 3 -- 3
ITDO802
X Department Optional Course – 6 3 -- 3 -- 3
ITIO801X Institute Optional Course – 2
3 -- 3 -- 3
ITL801 Block chain Lab -- 2 -- 1 1
ITL802 Cloud computing -- 2 -- 1 1
ITP801 Major Project II -- 12# -- 6 6
Total 12 16 12 8 20



Course
Code



Course Name Examination Scheme
Theory Term
Work Prac
/oral Total

Internal Assessment End
Sem
Exam Exam.
Duratio
n
(in Hrs)
Test1 Test2 Avg
ITC801 Blockchain and DLT 20 20 20 80 3 -- -- 100
ITDO801
X Department Optional Course – 5 20 20 20 80 3 -- -- 100
ITDO802
X Department Optional Course – 6 20 20 20 80 3 -- -- 100
ILO801X Institute Optional Course – 2
20 20 20 80 3 -- -- 100
ITL801 Blockchain Lab -- -- -- -- -- 25 25 50
ITL802 Cloud computing -- -- -- -- -- 25 25 50
ITP801 Major Project II -- -- -- -- -- 100 50 150
Total -- -- 80 320 -- 150 100 650
# indicates work load of Learner (Not Faculty), for Major Project

Students group and load of faculty per week.
Mini Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four)
Faculty Load : 1 hour per week per four groups

Major Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four)
Faculty Load : In Semester VII – ½ hou r per week per project group
In Semester VIII – 1 hour per week per project group

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ITDO801X Department Optional Course – 5
ITDO8 011 Big Data Analytics
ITDO8 012 Reinforcement learning
ITDO8 013 Simulation and Modeling
ITDO8 014 Knowledge management


ITDO802X Department Optional Course –6
ITDO8 021 User Interface Design
ITDO8 022 Robotics
ITDO8 023 ERP
ITDO8 024 Cloud computing and Services

# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VI II, which is
not closely allied to their disciplines. Different sets of courses will run in the both the
semesters.


ILO801X Institute Optional Course – 2 ( Common for all branches will be notified )
ILO801 1 Project Management
ILO801 2 Finance Management
ILO801 3 Entrepreneurship Development
and Management
ILO801 4 Human Resource Management
ILO801 5 Professional Ethics and CSR
ILO801 6 Research Methodology
ILO801 7 IPR and Patenting
ILO801 8 Digital Business Management
ILO801 9 Environmental Management

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Program Structure for Fourth Year Information Technology
Semester VII & VIII
UNIVERSITY OFMUMBAI
(With Effect from2022 -2023)
Semester VII

Course
Code
Course Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
ITC701 AI and DS –II 3 -- 3 -- 3
ITC702 Internet of Everything 3 -- 3 3
ITDO701
X Department Optional
Course – 3 3 -- 3 -- 3
ITDO702
X Department
Optional Course –4 3 -- 3 -- 3
ITIO701 X Institute Optional
Course – 1 3 -- 3 -- 3
ITL701 Data Science Lab -- 2 -- 1 1
ITL702 IOE Lab -- 2 -- 1 1
ITL703 Secure Application
Development -- 2 -- 1 1
ITL704 Recent Open Source
Project Lab -- 2 -- 1 1
ITP701 Major Project I -- 6# -- 3 3
Total 15 14 15 7 22



Course
Code


Course Name Examination Scheme
Theory Term
Work Prac/o
ral Total

Internal Assessment End
Sem
Exam Exam.
Duration
(in Hrs)
Test1 Test2 Avg
ITC701 AI and DS –II 20 20 20 80 3 -- -- 100
ITC702 Internet of Everything 20 20 20 80 3 -- -- 100
ITDO701
X Department
Optional Course –3 20 20 20 80 3 -- -- 100
ITDO702
X Department
Optional Course –4 20 20 20 80 3 -- -- 100
ITIO701X Institute Optional
Course – 1 20 20 20 80 3 -- -- 100
ITL701 Data Science Lab -- -- -- -- -- 25 25 50
ITL702 IOE Lab -- -- -- -- -- 25 25 50
ITL703 Secure Application
Development -- -- -- -- -- 25 25 50
ITL704 Recent Open Source
Project Lab -- -- -- -- -- 25 25 50
ITP701 Major Project I -- -- -- -- -- 25 25 50
Total -- -- 100 400 -- 125 125 750

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# indicates work load of Learner (Not Faculty), for Major Project

ITDO701X Department Optional Course –3
ITDO701 1 Storage Area Network
ITDO701 2 High Performance computing
ITDO701 3 Infrastructure Security
ITDO701 4 Software Testing and QA


ITDO702X Department Optional Course –4
ITDO702 1 MANET
ITDO702 2 AR – VR
ITDO702 3 Quantum Computing
ITDO702 4 Information Retrieval System



ILO701X Institute Optional Course – 1 ( Common for all branches will be notified )
ILO7011 Product Lifecycle Management
ILO7012 Reliability Engineering
ILO7013 Management Information System
ILO7014 Design of Experiments
ILO7015 Operation Research
ILO7016 Cyber Security and Laws
ILO7017 Disaster Management and Mitigation
Measures
ILO7018 Energy Audit and Management
ILO7019 Development Engineering

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Course Code Course N ame Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITC701 AI and DS –II 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITC701 AI and DS –
II 20 20 20 80 -- -- -- 100
Course Objectives:




Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Design models for reasoning with uncertainty as well as the use of unreliable
information . L1,L2,L3
2 Analyze the process of building a Cognitive application . L1,L2,L3,L4
3 Design fuzzy controller system . L1,L2,L3
4 Apply learning concepts to develop real life applications . L1,L2,L3
5 Evaluate performance of learning algorithms . L1,L2,L3,L4,L5
6 Analyze current trends in Data Science . L1,L2,L3,L4

Prerequisite: AI and DS - 1 (ITC604) , Data Mining & Business Intelligence (ITC601)

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping Sr. No. Course Objectives
The course aims:
1 To model a decision making for a new problem in an uncertain domain .
2 To demonstrate Cognitive skills of Artificial Intelligence .
3 To become familiar with the basics of Fuzzy Logic and Fuzzy Systems .
4 To become familiar with Deep Learning Concepts and Architectures .
5 To define and apply metrics to measure the performance of various learning algorithms .
6 To enable students to analyze data science methods for real world problems .

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0 Prerequisite Intelligent Agents, Search Techniques, Knowledge and
Reasoning, Data Science, Machine Learning. 02 --
I Uncertainty Uncertainty in AI, Inference using full joint distributions,
Bayes Theorem, the semantics of Bayesian Networks,
Inference in Bayesian networks, Decision Theory, Markov
Decision Processes.
Self-learning Topics: Hidden Markov Model (HMM),
Gaussian Mixture Model (GMM). 04 CO1
II Cognitive
Computing Foundation of Cognitive Computing, Design Principles for
Cognitive Systems, Natural Language Processing in Support of
a Cognitive System, Representing Knowledge in Taxonomies
and Ontologies, Applying Advanced Analytics to Cognitive
Computing, The Process of Building a Cognitive Application.
Self-learning Topics: Cognitive Systems such as IBM‘s
Watson. 06 CO2
III Fuzzy Logic
& Its
Applications Introduction to Fuzzy S ets, Properties of Fuzzy Sets,
Operations on Fuzzy Sets, Fuzzy Membership Functions,
Fuzzy Relations with Operations and its Properties, Fuzzy
Composition: Max -Min Composition, Max -Product
Composition, Defuzzification Methods, Architecture of
Mamdani Type Fuzzy Control System, Design of Fuzzy
Controllers like Domestic Shower Controller, Washing
Machine Controller, Water Purifier Controller, etc.
Self-learning Topics: Other Fuzzy Composition
Operat ions, Fuzzy Inference System (FIS) & ANFIS. 07 CO3
IV Introduction to
Deep Learning Introduction to Deep Learning, ANN, Machine Learning Vs
Deep Learning, Working of Deep Learning; Convolutional
Neural Network: Introduction, Components of CNN
Architecture, Properties of CNN, Architectu res of CNN,
Applications of CNN, Recurrent Neural Network: Introduction,
Simple RNN , LSTM Implementation, Deep RNN,
Autoencoder : Introduction, Features, Types, Applications of
Deep Learning.
Self-learning Topics: Restricted Boltzmann Machine
(RBM). 08 CO4
V Advanced ML
Classification
Techniques Ensemble Classifiers: Introduction to Ensemble Methods,
Bagging, Boosting, Random forests, Improving classification
accuracy of Class -Imbalanced Data.
Metrics for Evaluating Classifier Performance, Holdout
Method and Random Subsam pling, Cross -Validation,
Bootstrap, Model Selection Using Statistical Tests of
Significance, Comparing Classifiers Based on Cost –Benefit
and ROC Curves.
Self-learning Topics: Introduction to ML (Revision), 06 CO4
CO5

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Introduction to Reinforcement Learning .
VI Trends and
applications in
Data Science Data Science: applications and case studies, Data science for
text, image, video, audio. Data science for Multimodal
applications.
Self-learning Topics: ImageNet Large Scale Visual
Recognition Challenge (ILSVRC) . 06 CO6


Text Books:
1. Stuart Russell and Peter Norvig, ―Artificial Intelligence: A Modern Approach‖, Third Edition, Pearson Education.
2. Judith S. Hurwitz, Marcia Kaufman, Adrian Bowles, ―Cognitive Computing and Big Data Analytics‖, Wiley India,
2015.
3. S.N. Sivanandam, S.N. Deepa, ―Principles of Soft Computing‖, Wiley Publication.
4. Dr. S Lovelyn Rose, Dr. L Ashok Kumar, Dr. D Karthika Renuka, ―Deep Learning Using Python‖, Wiley India, 2020.
5. B. Uma Maheshwari, R. Sujatha, ―Introduction to Data Science Practical Approach with R and Python‖, Wiley India,
2021.
6. François Chollet, ―Deep Learning with Python‖, Manning Publications, 2018.
7. Han J, Kamber M, Pei J, ―Data Mining Concepts and Techniques‖, Third Edition, Morgan Kaufmann.
References:
1. Deepak Khemani, ―A First Course in Artificial Intelligence‖, McGraw Hill Publication.
2. Ethem Alpaydin , ―Introduction to Machine Learning‖, PHI Learning Pvt. Ltd.
3. Jon Krohn, Grant Beyleveld, Aglae B assens, ―Deep Learning Illustrated: A Visual, Interactive Guide to Artificial
Intelligence‖, Pearson Education.
4. Prateek Joshi, ―Artificial Intelligence with Python‖, Packt Publishing.
Online References:
Sr. No. Website Links
1 https://d2l.ai/index.html
2 https://onlinecourses.nptel.ac.in/noc20_cs62/preview
3 https://onlinecourses.nptel.ac.in/noc22_cs35/preview
4 https://www.coursera.org/specializations/deep -learning
5 https://onlinecourses.nptel.ac.in/noc22_cs56/preview

Assessment:
Internal Assessment for 20 marks :
Consisting of Two Compulsory Class Tests
Approximately 40% to 50% of syllabus content must be covered in First test and remaining 40% to 50% of syllabus
contents must be covered in second test.

End Semester Examination : Some guidelines for setting the question papers are as:
 Weightage of each module in end semester examination is expected to be/will be proportional to number of respective
lecture hours mentioned in the syllabus.
 Question paper will compris e of total six questions, each carrying 20 marks .
 Q.1 will be compulsory and should cover maximum contents of the syllabus .

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 Remaining question will be mixed in nature (for example if Q.2 has part (a) from module 3 then part (b) will be from
any other mo dule. (Randomly selected from all the modules.)
 Total four questions need to be solved.

Course Code Course N ame Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITC702 Internet of
Everything 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITC702 Internet of
Everything 20 20 20 80 -- -- -- 100


Course Objectives:

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Describe the Characteristics and Conceptual Framework of IoT. L1,L2
2 Differentiate between the levels of the IoT architectures. L1,L2,L3,L4
3 Analyze the IoT access technologies. L1,L2,L3,L4
4 Illustrate various edge to cloud protocol for IoT. L1,L2,L3
5 Apply IoT analytics and data visualization. L1,L2,L3
6 Analyze and evaluate IoT applications. L1,L2,L3,L4

Prerequisite:
1. Python programming
2. C programing language
3. Computer Networks Sr. No. Course Objectives
The course aims:
1 To comprehend Characteristics and Conceptual Framework of IoT.
2 To understand levels of the IoT architectures.
3 To correlate the connection of smart objects and IoT access technologies .
4 To Interpret edge to cloud protocols .
5 To explore data analytics and data visualization on IoT Data .
6 To explore IoT applications.

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DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Ports, Timers ,Programming of controller , How to
use IDE to write code of microcontroller, TCP -IP
protocol stack 02
I Introduction to IoT Introduction to IoT - Defining IoT, Characteristics
of IoT, Conceptual Framework of IoT, Physical
design of IoT, Logical design of IoT, Functional
blocks of IoT,Brief review of applications of IoT.
Smart Object – Definition, Characteristics and
Trends
Self-learning Topics: Hardware and software
development tools for - Arduino, NodeMCU,
ESP32, Raspberry Pi, for implementing internet of
things, Simulators -Circuit.io,Eagle,Tinkercad 04 CO1
II IoT Architecture Drivers Behind New Network Architectures :
Scale,Security,Constrained Devices and Networks
,Data,Legacy Device Support
Architecture : The IoT World Forum (IoTWF)
Standardized Architecture :Layer 1 -7, IT and OT
Responsibilities in the IoT Reference
Model,Additional IoT Reference Models
A Simplif ied IoT Architecture
The Core IoT Functional Stack ::Layer 1 -3 ,
Analytics Versus Control Applications , Data
Versus Network Analytics Data Analytics Versus
Business Benefits , Smart Services,
IoT Data Management and Compute Stack :Fog
Computing , Edge Com puting ,The Hierarchy of
Edge, Fog, and Cloud
Self-learning Topics: Brief review of applications
of IoT: Connected Roadways , Connected Factory,
Smart Connected Buildings , Smart Creatures etc, 06 CO2
III Principles of
Connected Devices
and Protocols in IoT RFID and NFC (Near -Field Communication),
Bluetooth Low Energy (BLE) roles, LiFi , WPAN
std : 802.15 standards: Bluetooth, IEEE 802.15.4,
Zigbee, Z -wave, Narrow Band IoT, Internet
Protocol and Transmission Control Protocol,
6LoWPAN, WLAN and WAN , IEEE 802.11,
Long -range Communication Systems and Protocols:
Cellular Connectivity -LTE, LTE -A, LoRa and
LoRaWAN. 08 CO3
IV Edge to Cloud
Protocol HTTP, WebSocket, Platforms. HTTP - MQTT -
.Complex Flows: IoT Patterns: Real -time Clients,
MQTT, MQTT -SN, Constrained Application
Protocol (CoAP), Streaming Text Oriented Message
Protocol ( STOMP), Advanced Message Queuing
Protocol (AMQP), Comparison of Prot ocols. 08 CO4

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V IoT and Data
Analytics Defining IoT Analytics, IoT Analytics challenges,
IoT analytics for the cloud, Strategies to organize
Data for IoT Analytics, Linked Analytics Data Sets,
Managing Data lakes, The data retention strategy,
visualization and Dashboarding -Designing visual
analysis for IoT data, creating a dashboard ,creating
and visualizing alerts.
Self-learning Topics: AWS and Hadoop
Technology 06 CO5
VI IoT Application
Design Prototyping for IoT and M2M, Case study related to
: Home Automation (Smart lighting, Home
intrusion detection), Cities (Smart Parking),
Environment (Weather monitoring, weather
reporting Bot, Air pollution monitoring, Forest fire
detection, Agriculture (Smart irrigation), Smart
Library. Introduction t o I-IoT, Use cases of the I -
IoT,IoT and I -IoT – similarities and differences,
Introduction to Internet of Behavior (IoB) .
Self-learning Topics: Internet of Behaviors (IoB)
and its role in customer services 04 CO6

Text Book
1.Arsheep Bahga (Author), Vijay Madisetti , Internet Of Things: A Hands -On Approach Paperback, Universities Press,
Reprint 2020
2.David Hanes , Gonzalo Salgueiro , Patrick Grossetete , Robert Barton , Jerome Henry , IoT Fundamentals Networking
Technologies, Protocols, and Use Cases for the Internet of Thing s CISCO.
3.Analytics for the Internet of Things (IoT) Intelligent Analytics for Your Intelligent Devices.Andrew Minteer,Packet
4.Giacomo Veneri , Antonio Capasso,‖ Hands -On Industrial Internet of Things: Create a powerful Industrial IoT
infrastructure usin g Industry 4.0‖, Packt

References:
1. Pethuru Raj , Anupama C. Raman , The Internet of Things: Enabling Technologies, Platforms, and Use Cases by , CRC
press,
2. Raj Kamal, Internet of Things, Architecture and Design Principles, McGraw Hill Education, Reprint 201 8.
3. Perry Lea, Internet of Things for Architects: Architecting IoT solutions by implementing sensors, communication
infrastructure, edge computing, analytics, and security, Packt Publications, Reprint 2018.
4. Amita Kapoor, ―Hands on Artificial intellige nce for IoT‖, 1st Edition, Packt Publishing, 2019.
5. Sheng -Lung Peng, Souvik Pal, Lianfen Huang Editors: Principles of Internet of Things (IoT)Ecosystem:Insight Paradigm,
Springer

Online Resources:
Sr. No. Website Name
1. https://owasp.org/www -project -internet -of-things/
2. NPTEL: Sudip Misra, IIT Khargpur, Introduction to IoT: Part -1,
https://nptel.ac.in/courses/106/105/106105166/
3. NPTEL: Prof. Prabhakar, IISc Bangalore, Design for Internet of Things,
https://onlinecourses.nptel.ac.in/noc21_ee85/preview
4. Mohd Javaid, Abid Haleem, Ravi Pratap Singh, Shanay Rab, Rajiv Su man,Internet of
Behaviors (IoB) and its role in customer services,Sensors International,Volume

Page 20

2,2021,100122,ISSN 2666 -3511,https://doi.org/10.1016/j.sintl.2021.100122

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) f rom Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered .

Page 21

Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ITL701 Data Science
Lab -- 2 -- -- 1 -- 01

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical/
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITL701 Data Science Lab -- -- -- -- 25 25 50
Lab Objectives:

Sr. No Lab Objectives
1 To apply reasoning for a problem in an uncertain domain.
2 To discuss the solution after building a Cognitive application.
3 To familiarize the students with the basics of Fuzzy Logic and Fuzzy Systems.
4 To familiarize the students with Learning Architectures and Frameworks.
5 To define and apply metrics to measure the performance of various learning algorithms .
6 To enable students to analyze data science methods for real world problems.
Lab Outcomes:
Sr.
No Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
1 Implement reasoning with uncertainty. L1, L2, L3
2 Explore use cases of Cognitive Computing L1, L2
3 Implement a fuzzy controller system. L1, L2, L3
4 Develop real life applications using learning concepts. L1, L2, L3
5 Evaluate performance of applications. L1, L2, L3, L4
6 Implement and analyze applications based on current trends in Data Science. L1, L2, L3, L4, L5

Hardware & Software requirements:

Hardware Specifications Software Specifications
PC with following Configuration
1. Intel Core i3/i5/i7
2. 4 GB RAM Python, MySQL or Database Software

Page 22

3. 500 GB Hard disk

Prerequisite: Artificial Intelligence and Data Science -I, Python Programming, Data Mining & Business Intelligence.

Page 23

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours LO
Mapping
I Uncertainty in AI 1. Implement Inferencing with
Bayesian Network in Python 02 LO1
II Cognitive
Computing 2. Building a Cognitive Healthcare
application
3. Smarter cities: Cognitive Computing
in Government
4. Cognitive computing in Insurance
5. Cognitive computing in Customer
Service 04 LO2
III Fuzzy Logic & Its
Applications 6. Implementation of Fuzzy
Membership Functions.
7. Implementation of fuzzy set
Properties.
8. Design of a Fuzzy control system
using Fuzzy tool. 04 LO3
IV Introduction to Deep
Learning 9. Implementing Deep Learning
Applications like
a. Image Classification System
b. Handwritten Digit Recognition
System (like MNIST Dataset)
c. Traffic Signs Recognition
System.
d. Image Caption Generator 06 LO4
V Advanced ML
Classification
Techniques 10. Implementation of supervised
learning algorithm like
a. Ada-Boosting
b. Random forests
11. Evaluation of Classification
Algorithms. 05 LO4,LO5
VI Mini -project on
trends and
applications in Data
Science 12. Build text/ image/ video/ audio
based DS Applications such as
a. Chatbot
b. Document Classification
c. Sentiment Analysis
d. Bounding Box Detection
e. Music/Video Genre
Classification 05 LO6

Text Books:
1. Stuart Russell and Peter Norvig, ―Artificial Intelligence: A Modern Approach‖, Third Edition, Pearson Education.
2. Judith S. Hurwitz, Marcia Kaufman, Adrian Bowles, ―Cognitive Computing and Big Data Analytics‖, Wiley India,
2015.

Page 24

3. S.N. Sivanandam, S.N. Deepa, ―Princ iples of Soft Computing‖, Wiley Publication.
4. Dr. S Lovelyn Rose, Dr. L Ashok Kumar, Dr. D Karthika Renuka, ―Deep Learning Using Python‖, Wiley India,
2020.
5. B. Uma Maheshwari, R. Sujatha, ―Introduction to Data Science Practical Approach with R and Python‖, Wiley
India, 2021.
6. François Chollet, ―Deep Learning with Python‖, Manning Publications, 2018.
7. Han J, Kamber M, Pei J, ―Data Mining Concepts and Techniques‖, Third Edition, Morgan Kaufmann.
References:
1. Deepak Khemani, ―A First Course in Artificial Intellig ence‖, McGraw Hill Publication.
2. Ethem Alpaydin , ―Introduction to Machine Learning‖, PHI Learning Pvt. Ltd.
3. Jon Krohn, Grant Beyleveld, Aglae Bassens, ―Deep Learning Illustrated: A Visual, Interactive Guide to Artificial
Intelligence‖, Pearson Education.
4. Prateek Joshi, ―Artificial Intelligence with Python‖, Packt Publishing.
Online References:
Sr. No. Website Links
1 https://wisdomplexus.com/blogs/cognitive -computing -examples/
2 http://vlabs.iitb.ac.in/vlabs -dev/labs/machine_learning_old/labs/explist.php
3 https://infyspringboard.onwingspan.com/en/app/toc/lex_auth_01329517021676339249401_
shared/overview
4 https://infyspringboard.onwingspan.com/en/app/toc/lex_auth_01329500219268300841860_
shared/overview
5 https://www.udemy.com/course/ibm -watson -for-artificial -intelligence -cognitive -computing/
Term Work:

Term Work shall consist of at least 10 practical b ased on the above list. Also Term Wor k Journal must include Mini -
Project as mentioned in above syllabus.

Term Work Marks : 25 Marks (Total marks) = 10 Marks (Experiments) + 10 Marks (Mini -project) + 5 Marks (Attendance)

Oral Exam : An Oral exam will be hel d based on the above syllabus.

Page 25

Teaching Scheme
(Contact Hours)
Credits Assigned
Course
Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ITL702
Internet of
Everything Lab
-- 2 -- -- 1 -- 01

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical/
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
ITL702 Internet of
Everything Lab
-- -- -- -- 25 25 50

Lab Objectives:

Sr.
No. Lab Objectives
The Lab experiments aims:
1 To learn different types of sensors .
2 To design the problem solution as per the requirement analysis done using sensors .
3 To study the basic concepts of programming/sensors/ emulators .
4 To design and implement the mini project intended solution for project based learning .
5 To build and test the mini project successfully .
6 To improve the team building, communication and management skills of the students .

Lab Outcomes:

Sr.
No. Lab Outcomes Cognitive Levels
of Attainment as
per Bloom’s
Taxanomy
On successful completion, of course, learner/student will be able to:
1 Identify the requirements for the real world problems . L1,L2
2 Conduct a survey of several available literatures in the preferred field of study . L1,L2
3 Study and enhance software/ hardware skills . L1,L2
4 Demonstrate and build the project successfully by hardware/sensor requirements, coding,
emulating and testing . L1,L2,L3
5 To report and present the findings of the study conducted in the preferred domain . L1,L2,L3,L4
6 Demonstrate an ability to work in teams and manage the conduct of the research study . L1,L2,L3,L4

Hardware & Software requirements:

Hardware Specifications Software Specifications

Page 26

PC with following Configuration
1. Intel Core i3/i5/i7
2. 4 GB RAM
3. 500 GB Hard disk
4. Arduino/ Raspberry Pi kit Python/C, Conitiki, Cooja or any open source
Simulator


Prerequisite: Basics of Java and Python Programming, Devops
DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours LO
Mapping
0 Prerequisite Experimentation with Microprocessor and Microcontroller ,
Experimentation with python and c 02
I Arduino Introduction to Arduino, Hardware requirements, Software
requirements, Arduino Programming Language, Arduino Uno
Wired & Wireless connectivity, LCD commands, Serial
Communication commands. Program for blinking LED using
Arduino. Traffic Light pattern using Arduino. ESP8266 WiFi
Module 05 LO1, LO2
II Raspberry Pi Introduction to Raspberry Pi, Installation of NOOBS and
Raspbian on SD card, Libraries on Raspberry Pi, getting static
IP address of Raspberry Pi, Interfacing of Relay, DHT11, DC
Motor and LCD with Raspberry Pi. 05 LO1,LO2
III Contiki OS Contiki OS : History of Contiki OS, Applications, Features,
,Communication Components in Contiki OS, Cooja simulator
,Running Cooja Simulator, 05
LO3
IV Cooja
Simulator Using the Contiki OS with the Cooja simulator to program the
IoT for broadcasting data from sensors 03 LO5,LO6
V Protocols and
Security with
Cooja Understanding of 6LowPAN , COAP and protocol
implementation in Cooja . Encryption Decryption techniques
for IoT
03 LO5,LO6

Page 27

VI IoT data to
Cloud Installing the Remote desktop server. Installation of Pi camera,
Face recognition, serial peripheral interface using Raspberry Pi.
. DHT11 data logger with ThingSpeak/ thingsboard/ AWS/
Azure server . 03 LO4,L06



Text Books:
1. Interconnecting Smart Objects with IP: The Next Internet, Jean -Philippe Vasseur, Adam Dunkels, Morgan
Kuffmann
2. Designing the Internet of Things , Adrian McEwen (Author), Hakim Cassimally
3. Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems, Dr. Ovidiu
Vermesan, Dr. Peter Friess, River Publishers
4. Internet of Things (A Hands -on-Approach) , Vijay Madisetti , Arshdeep Bahga

References:
1. 6LoWPAN: The Wireless Embedded Internet, Zach Shelby, Carsten Bormann, Wiley
2. Building the internet of things with ipv6 and mipv6, The Evolving World of M2M Communications, Daniel
Minoli John Wiley & Sons
3. Contiki Cooja User Guide.
4. Fundamentals of Sensor Network Programming: Applications and Technology, By S. Sitharama Iyengar, Nandan
Parameshwaran, Vir V. Phoha, N. Balakrishnan, Chuka D. Okoye, Wiley publication.
5. Recent research/white papers

Digital Reference :
1. IoT Analytics -Things https://thingspeak.com
2. https://www.contiki -ng.org/
3. http://www.ideationinstru.com/training.htm


List of Experiments.
Guidelines for Mini Project
1. The mini project work is to be conducted by a group of three students
2. Each group will be associated with a subject Incharge/ mini project mentor. The group should meet with the concerned
faculty during Laboratory hours and the progress of work discussed must be documented.
3. The students must understand the
a. Concept
b. Importance
c. Interdisciplinary
d. Challenges
e. Various applications/smart objects
f. Major Players/Industry Standards.

4. The students must understand the IoT Architecture:
a. Node Structure: Sensing, Processing, Communication, Powering
b. Net working: Topologies, Layer/Stack architecture
c. Communication Technologies: Introduction to ZigBee, BLE, WiFi, LTE, IEEE 802.11ah, Discuss data rate,
range, power, computations/bandwidth, QoS
d. Smartness - Signal Processing/Analytics: Impact on Power/E nergy savings, dynamic networks, simple case
studies
e. IoT Fabricator: Introduction to Embedded electronics, fabricating electronics, Communication Network

Page 28

requirements, Data processing challenges – recreation, IP/security, Challenges
f. Hands -on in IoT : Projects based on some Hardware (Raspberry pi, Arduino, Intel, IITH Mote, Smartphones),
Software (Contiki, TinyOS, Android), IoT Fabricator etc. can be used.

5. The students may visit different websites to identify their IOT topic for the mini project .
6. The students may do surveys for different applications using different types of sensors for their mini project.
7. Each group will identify the Hardware (Motes from different Motes families) & sensor configuration and software
requirements for their m ini project problem statement.
8. Design your own circuit board using multiple sensors etc.
9. Installation, configure and manage your sensors in such a way so that they can communicate with each other.
10. Work with operating system, emulator like cont iki cooja and do coding to for input devices on sensors
11. Create an interface using Mobile/Web to publish or remotely access the data on the Internet.
12. Each group along with the concerned faculty shall identify a potential problem statement, on which the study and
implementation is to be conducted.
13. Analyze data collected from different sensors on platform like thinkspeak/AWS/Azure etc
14. Devops and Advance Devops concepts students have learnt in earlier semesters can be used while working with IoT
projects.
15. Each group may present their work in various project competitions or paper presentations.
16. A detailed report is to be prepared as per guidelines given by the concerned faculty.


Term Work:

Term Work shall consist of Mini -Project based on the above syllabus and guidelines . Also Term Work Journal
must include at least 2 assignments.

Term Work Marks:

25 Marks (Total marks) = 15 Marks ( Mini -Project ) + 5 Marks (Assignments) + 5 Marks (Attendance)
Oral Exam: An Oral exam will be held based on the above syllabus.

Page 29

Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ITL703 Secure
Application
Development -- 2 -- -- 1 -- 01


Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical/
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITL703 Secure
Application
Development -- -- -- -- 25 25 50
Lab Objectives:

Sr. No Lab Objectives
 The Lab experiments aims:
1  To understand the secure programming of application code .
2  To understand the Owasp methodologies and standards .
3  Understand and Identify m ain vulnerabilities inherent in applications .
4  Understand how Data Validation and Authentication can be applied for application .
5  Understand how to apply Security at Session Layer Management .
6  Understand how to apply to secure coding for cryptography .
Lab Outcomes:
Sr.
No Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1  Apply secure programming of application code . L1,L2,L3
2  Understand the Owasp methodologies and standards . L1,L2,L3
3  Identify m ain vulnerabilities inherent in applications . L1,L2,L3
4  Apply Data Validation and Authentication for application L1,L2,L3,L4,L5
5  Apply Security at Session Layer Management L1,L2,L3,L4,L5
6  Apply secure coding for cryptography . L1,L2,L3,L4,L5


Hardware & Software requirements:

Page 30

Hardware Specifications Software Specifications
PC with following Configuration
1. Intel Core i3/i5/i7
2. 4 GB RAM
3. 500 GB Hard disk Web Application, HTML5, CSS3, Java, C, Python,
MySQL or Database Software.
Internet Connection, Browser, Security tools. SAST
tools etc.

 Prerequisite: Knowledge of programming languages like java/python/C is required.

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours LO
Mapping
0 Prerequisite Programming Language and Web application basic
concepts. 02
I Introduction to
Secure
Programming Introduction to laws, standards and guidelines of cyber
security. What do you mean by attacks, types of
attacks and statistics of main vulnerabilities ?

Lab1: Study of different laws and standards of cyber
security. 04 LO1
II Methodologies for
developing secure
code Software Development Lifecycle. Risk Analysis.
Threat Modeling. Study different SAST (Static
Application Security Testing) tools . Study different top
10 methodologies and guidelines of OWASP (Open
Web Application Security Project) for the secure
applica tion development. Any top 5 OAT. Best eight
guidelines for Secure Coding. Understand the flow of
Verification testing for secure coding.


Lab2: Case study for SDLC.
Lab3: Exercise on Threat Modeling.
Lab4: Study of SAST Tools (open Source like GitHub,
GitLab and so on) and use at least one for practical
Lab5: Study and implement at least any 5
methodologies of OWASP.
Lab6: Study and implement at least any 5 OAT Denial
of Inventory for E -commerce Website.. 06 LO2
III VAPT of
Applications Introduction to the HTTP protocol.Owasp Web
Security Testing Guidelines. Tools for VAPT testing.

Lab7 :Use Burp proxy to test web applications . 04 LO3
IV Data Validation &
Authentication Guidelines for input data validation (Data type, Data
size, Data range, Data Content etc.) and
authentication for login page. Types of
Authentication attacks . Study different type of 05 LO4

Page 31

vulnerabilities like SQL Injection vulnerability,
LDAP and XPath Injection vulnerabilities, Cross -
Site S cripting (XSS) vulnerability, OS Command,
LFI/RFI, Unvalidated file upload and buffer
overflow etc.


Lab8: Registration Page Data Validation.
Lab9: SQL injection vulnerability allow s login page
to bypass .
Lab10: LDAP and XPath Injection vulnerabilities
for login /registration page.
Lab11: Cross -Site Scripting (XSS) vulnerability
Lab
Lab12: OS Command vulnerability Lab
Lab13: LFI/RFI or Unvalidated file upload or
Buffer Overflow vulnerability Lab .
Lab14: Onl ine Password attack.
V Security in Session
Layer Introduction to Session Layer in Web Applications
and management. Session Management Best
practices according to OWASP .

Lab15: Session Management for Web Application.
03 LO5
VI Secure Coding for
cryptography. Overview of cryptography and guidelines for using
encryption. Types of cryptography ie symmetric and
asymmetric. Hashing Algorithms etc.

Lab16: Symmetric and Asymmetric
Lab17: Symmetric Encryption and Hashing .
02 LO6

Text & References Books:
1. Fundamental Practice for Secure Software Development.
2. The OWASP Automated Threat Handbook - Web Applications.
3. OWASP Alpha Release Code Review Guide 2.0
4. Secure Programming HOWTO
5. OWASP Quick reference guide 2.



Online References:
Sr. No. Website Links
1 https://www.udemy.com/course/secure -coding -secure -application -development/
2 https://kirkpatrickprice.com/blog/secure -coding -best-practices/

Page 32

3 https://owasp.org/www -project -automated -threats -to-web-applications/assets/oats/EN/OAT -
021_Denial_of_Inventory

Term Work:

Term Work shall consist of at least 10 to 12 practical based on the above list. Also Term Work Journal must include at
least 2 assignments as mentioned in above syllabus.

Term Work Marks : 25 Marks (Total marks) = 15 Marks (Experiments) + 5 Marks ( Assignment ) + 5 Marks (Attendance)

Oral Exam : An Oral exam will be held based on the above syllabus.

Page 33

Teaching Scheme (Contact
Hours)
Credits Assigned
Course
Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ITL704 Recent Open
Source Project
Lab -- 2 -- -- 1 -- 01

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical/
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITL70 4 Recent Open
Source Project
Lab -- -- -- -- 25 25 50
Lab Objectives:

Sr. No Lab Objectives
The Lab experiments aims:
1 To understand the basic concepts of Open Source Software.
2 To understand the GPL(General Public Licence ) and Contribute of Open Source .
3 To Understand Contribute to Open Source in different Operating System.
4 To Understand Contribute to Open Source in different Technologies.
5 To Understand Contribute to Open Source in different Network Management..
6 To Understand Contribute to Open Source in different Applications and Services.
Lab Outcomes:
Sr.
No Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand and apply the basic concepts of Open Source Software. L1,L2,L3
2 Identify the difference between the GPL(General Public Licence ) and
Contributet o Open Source . L1,L2,L3
3 Apply and evaluate your knowledge for the Contributet o Open Source in
different Operating System. L1,L2,L3,L4,L5
4 Apply and evaluate your knowledge for the Contribute to Open Source in
different Technologies. L1,L2,L3,L4,L5
5 Apply and evaluate your knowledge for the Contribute to Open Source in
different Network Management.. L1,L2,L3,L4,L5
6 Apply and evaluate your knowledge for the Contribute to Open Source in
different Applications and Services. L1,L2,L3,L4,L5

Page 34

Hardware & Software requirements:

Hardware Specifications Software Specifications
PC with following Configuration
1. Intel Core i3/i5/i7
2. 4 GB RAM
3. 500 GB Hard disk Internet Connection.
Any O perating System.
Any technology open source tools/simulator/emulator.
Any open source Testing Tools
Any open source Network Monitoring Tools.
Any open Source Database tools.
Any open sourc e Latex report writing tools.

Prerequisite: OS, Programming Language, DBMS, IP, Network.
DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours LO
Mapping
0 Prerequisite Basic Concepts of OS, Programming Language,
Network and DMBS. 02 --
I Introduction to OSS Overview of OSS. Basic Concepts of OSS. Advantages
of OSS. Difference between free and open source
software. What is GPL and Contribute to Open Source
Project . Different ways to contribute. 04 LO1
II Contribute to Open
Source Project. Overview of Contribute Open Source Project. Steps or
Guidelines of Contribute to Open Source Projects : 1.
Why to Contribute to open source Project. 2. What do
you mean by Contribute Open Source Projects. 3.
Identifying the new/existing open source projects to
contribute. 4. Submit your contribute to open source.5.
Results after s ubmitting your contribute to Open
Source. 04 LO2
III Contribute to Open
Source in Operating
System. As per Contribute to Operating System to introduce
new OS version, Improve OS by removing bugs,
Improve existing Skill sets for growth in career.
Interact with Stakeholders for feedback and provide
training and mentoring. Start own Startup. 04 LO3
IV Contribute to Open
Source in
Technologies. As per Contribute to various emerging technologies
like AI/ML/DL/Blockchain/IoT/Data Analytics/Cyber
Security/Andriod/iOS/Flutter/DeVoPs/Virtualization
and Cloud Computing etc. To improve technologies.
Introduce new version of technologies, Improve
technologies by removing bugs, Improve existing
Skill sets for growth in career. Interact with
Stakeholders and provide training and mentoring.
Start own Startup. 04 LO4
V Contribute to Open
Source in Network
Management. As per Contribute to different types of Network and
Management Systems like LAN/WAN/MAN/Adhoc
Network/Data Centre/Wireless Network/Enterprise 04 LO5

Page 35

Network etc. To improve Networks as a Network
administrator. Design own Network as per customer
requirements , Imp rove existing Skill sets for growth
in career. Interact with Stakeholders and provide
training and mentoring. Start own Startup.
VI Contribute to Open
Source in
Application & Cloud
Services. As per Contribute to various Applications or Case
studies using Cloud Services etc. To improve
applications, remove bugs. Improve existing Skill sets
for growth in career. Interact with Stakeholders and
provide training and mentoring. Start own Startup. 04 LO6

Guidelines for Recent Open Source Mini Project as per above syllabus.
 Students shall form a group of 3 to 4 students, while forming a group shall not be allowed less than three
or more than four students, as it is a group activity.
 Students should do survey and identify needs, which shall be converted into problem statement how to
contribute to open source mini project in consultation with faculty supervisor/head of department/internal
committee of faculties.
 Students shall submit implementation plan in the form of Gantt/PERT/CPM chart, which will cove r
weekly activity of recent contribute to open source mini project.
 A log book to be prepared by each group, wherein group can record weekly work progress,
guide/supervisor can verify and record notes/comments.
 Faculty supervisor may give inputs to stude nts during mini project activity;however, focus shall be on
self-learning.
 Students in a group shall understand contribute to open source problem effectively, propose multiple
solution and select best possible solution in consultation with guide/ supervi sor.
 Students shall convert the best solution into working model using various components of their domain
areas and demonstrate.
 The solution to be validated with proper justification and report using open source tools to be compiled in
standard format of University of Mumbai.
 With the focus on the self -learning, innovation, addressing societal problems and entrepreneurship quality
development within the students through the open source Mini Projects .
Guidelines for Assessment of Recent Open Source Mini P roject:
Term Work
 The review/ progress monitoring committee shall be constituted by head of departments of each
institute. The progress of mini project to be evaluated on continuous basis, minimum two reviews in
each semester.
 In continuous assessment focu s shall also be on each individual student, assessment based on
individual‘s contribution in group activity, their understanding and response to questions.
 Distribution of Term work marks for both semesters shall be as below;
o Marks awarded by guide/supervisor based on log book : 10
o Marks awarded by review committee : 10
o Quality of Project Report :05

Page 36

Text & Reference Books:

1. Forge Your Future with Open Source: Build Your Skills. Build Your Network. Build the Future
of Technology. 1st Edit ion

Online References:

Sr. No. Website Links
1 https://github.com/freeCodeCamp/how -to-contribute -to-open -source
2 https://opensource.guide/how -to-contribute/#why -contribute -to-open -source

Term Work:

Term Work shall consist of at least Open Source Project based on the above syllabus . Also Term Work Journal must
include at least 2 assignments to explain contribute to open source as mentioned in above syllabus.

Term Work Marks : 25 Marks (Total marks) = 15 Marks ( Mini -Project ) + 5 Marks ( Assignment ) + 5 Marks (Attendance)

Oral Exam : An Oral exam will be held based on the above syllabus.

Page 37

Course Code
Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
ITM701 Major Project – I -- 06 -- -- 03 -- 03


Course
Code
Course Name Examination Scheme
Theory Marks
Term Work Pract. /Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg.
ITM701 Major Project – I
-- -- -- -- 25 25 50

Course Objectives
1. To acquaint with the process of identifying the needs and converting it into the problem.
2. To familiarize the process of solving the problem in a group.
3. To acquaint with the process of applying basic engineering fundamentals to attempt solutions to the problems.
4. To inculcate the process of self -learning and research.
Course Outcome: Learner will be able to…
1. Identify problems based on societal /research needs.
2. Apply Knowledge and skill to solve societal problems in a group.
3. Develop interpersonal skills to work as member of a group or leader.
4. Draw the proper inferences from available results through theoretical/ experimental/simulations.
5. Analyse the impact of solutions in societal and environmental context for sustainable dev elopment.
6. Use standard norms of engineering practices
7. Excel in written and oral communication.
8. Demonstrate capabilities of self -learning in a group, which leads to life long learning.
9. Demonstrate project management principles during project work.

Guidel ines for Major Project
 Students shall form a group of 3 to 4 students, while forming a group shall not be allowed less than three
or more than four students, as it is a group activity.
 Students should do survey and identify needs, which shall be converted into problem statement for mini
project in consultation with faculty supervisor/head of department/internal committee of faculties.
 Students shall submit implementation plan in the form of Gantt/PERT/CPM chart, which wi ll cover
weekly activity of major project -I and major project -II.
 A log book to be prepared by each group, wherein group can record weekly work progress,
guide/supervisor can verify and record notes/comments.
 Faculty supervisor may give inputs to students d uring major project -I & II activity;however, focus shall be
on self -learning.

Page 38

 Students in a group shall understand problem effectively, propose multiple solution and select best
possible solution in consultation with guide/ supervisor.
 Students shall convert the best solution into working model using various components of their domain
areas and demonstrate.
 The solution to be validated with proper justification and report to be compiled in standard format of
University of Mumbai.
 With the focus on the self -learning, innovation, ad dressing societal problems and entrepreneurship quality
development with in the students through the Major Project , it is preferable that a single project of
appropriate level and quality to be carried out in two semesters by all the grou ps of the students. i.e. Majo r
Project -I in semester VII and Major Project -IIin semesters V III.
 However, based on the individual students or group capability, with the mentor‘s recommendations, if the
proposed M ajor Project adhering to the qualitative aspects mentioned above gets completed in odd
semester, then that group can be allowed to Scopus paper publications in Journal/Conference or motivate
for Copyright or Indian Patent as an extension of the M ajor Project -1 with suitable
improvements/modifications after testing and analysis in even semester. This policy can be adopted on
case by case basis.
Guidelines for Assessment of Major Project:
Term Work
1. The review/ progress monitoring committee shall be constituted by head of departments of ea ch
institute. The progress of majo r project to be evaluated on continuous basis, minimum two reviews
in each semester VII and VIII .
2. In continuous assessment focus shall also be on each individual student, assessment based on
individual‘s contribution in group activity, their understanding and response to questions.
3. Distribution of Term work marks for both semesters shall be as below;
a. Marks awarded by guide/supervisor based on log book : 10
b. Marks awarded by review committee : 10
c. Quality of Project report : 05

Review/progress monitoring committee may consider following points for assessment based on either one
year major project as mentioned in general guidelines.
One-year project:
 In semester VII entire theoretical solution shall be ready, including components/system selection and
cost analysis , building of working prototype . Two reviews will be conducted based on presentation
given by students group.
 First shall be for finalization of problem and proposed solution of the problem
 Second shall be on readiness of working and testing of prototypeto be conducted.
 In semester VIII expected work shall be procurement of testing and validation of results based on
work completed in an odd semester.
 First re view is based on improvements in testing and validation results cum demonstration
for publication to be conducted.
 Second review shall be based on paper presentation in conference/journal or copyright or
Indian patent in last month of the said semester.

Assessment criteria of Major Project.

Major Project shall be assessed based on following criteria;
1. Quality of survey/ need identification

Page 39

2. Clarity of Problem definition based on need.
3. Innovativeness in solutions
4. Feasibility of proposed problem solutions and selection of best solution
5. Cost effectiveness
6. Societal impact
7. Innovativeness
8. Cost effectiveness and Societal impact
9. Full functioning of working model as per stated requirements
10. Effective use of skill sets
11. Effective use of standard engineering norms
12. Contribution of an individual‘s as member or leader
13. Clarity in written and oral communication

 In one year, project , first semester evaluation may be based on first six criteria‘s and remaining
may be used for second semester evaluation of performance of s tudents in mini project.
Guidelines for Assessment of Major Project Practical/Oral Examination:
 Report should be prepared as per the guidelines issued by the University of Mumbai.
 Major Project shall be assessed through a presentation and demonstration of working model by the student
project group to a panel of Internal and External Examiners preferably from industry or research
organizations having experience of more than five years approved by head of Institution.
 Students shall be motivated to publish a paper based on the work in Scopus Conferences/ Journals or copy
right or Indian Patent .

Major Project shall be assessed based on following points;
1. Quality of problem and Clarity
2. Innovativeness in solutions
3. Cost effectiveness and Societal impact
4. Full functioning of working model as per stated requirements
5. Effective use of skill sets
6. Effective use of standard engineering norms
7. Contribution of an individual‘s as member or leader
8. Clarity in written and oral communication
9. Publications in Sem VIII.

Page 40

Course Code Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ITDO7011 Storage Area
Network 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
ITDO7011 Storage Area
Network 20 20 20 80 -- -- -- 100

Course Objectives:

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify the limitations of the client -server architecture and evaluate the need for
data protection and storage centric architectures such as Intelligent storage
system . L1,L2
2 Understand various SAN technologies . L1,L2
3 Interpret and examine NAS technologies and its application in Storage Area
Network . L1,L2
4 Explain Different I/O Techniques in SAN . L1,L2
5 DescribeCloud based storage virtualization technologies in SAN . L1,L2
6 Explain Storage infrastructure management with security . L1,L2

Prerequisite: Operating System, Computer Organization, Computer Networks .

Sr. No. Course Objectives
The course aims:
1 To provide the knowledge of types Storage Network .
2 To examine NAS technology and its applications in Storage Area Networks .
3 To study Emerging Technologies in SAN .
4 To define backup, recovery, disaster recovery and business continuity in the storage area Network .
5 To learn cloud based storage virtualization technologies in SAN .
6 To understand the logical and physical components of storage infrastructures .

Page 41

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Components of a Storage System
Environment, Disk drive components, RAID
levels, Cloud Computing 02 --
I Introduction to
Storage Area
Network Intelligent Storage Systems (ISS) , Storage
Provisioning, Types of Intelligent Storage
Systems
Evolution of Storage System: Server -
Centric IT Architecture and its Limitations,
Storage -Centric IT Architecture and its
Advantages, SAN & its advantages.
Self-learning Topics:
Case Study on Replacing a server with
Storage networks .
04 CO1
II Networked Attached
Storage & its
Application Local File Systems: File systems and
databases,Journaling, Snapshots,Volume
manager Network File Systems, and File
Servers: Network Attached Storage (NAS),
Performance bottlenecks in file servers,
Acceleration of network file systems, Case
study: The Direct Access File System
(DAFS), Shared Disk File Systems: A case
study The General Parallel File System
(GPFS),
Applying NAS solution: NAS workload
characterization, applying NAS to
departmental workloads, enterprise web
workloads, and specialized workloads;
Considerations when integrating SN and
NAS: Differences and similarities, the need to
integrate, future storage connectivity and
integration.
Self-learning Topics: Case study on
Successful SAN Deployment steps . 07 CO2
III Storage I/O
Techniques The Physical I/O Path from the CPU to the
Storage System, SCSI, The Fibre Channel
Protocol Stack, Fibre Channel SAN, IP
Storage, Infiniband -based Storage Networks,
Fibre Channel over Ethernet (FCoE).
Self-learning Topics: C ase Study on FCoE
SAN. 06 CO3
IV Backup and Data
Archive Introduction to Business Continuity:
Information Availability, BC Terminology,
BC Planning Lifecycle, Failure Analysis,
Business Impact Analysis
Backup and Archive: Backup Purpose,
Backup Considerations, Backup Granularity, 06 CO4

Page 42

Recovery Considerations, Backup Methods
,Backup Architecture, Backup and Restore
Operations, Backup Topologies
Self-learning Topics: Case Study on
Replication strategy
V Storage Area
Network as a
Service for Cloud
Computing &
Virtualization Virtualization and the cloud: Cloud
infrastructure virtualization, Cloud platforms,
Storage virtualization, SAN virtualization
Virtualization Appliances:
Black Box Virtualization, In -Band
Virtualization Appliances, Out -of-Band
Virtualization Appliances High Availability
for Virtualization Appliances, Appliances for
Mass Consum ption.

Storage Automation and Virtualization:
Policy -Based Storage Management,
Application -Aware Storage Virtualization,
Virtualization -Aware Applications.
Self-learning Topics: Case study on
symmetric and asymmetric virtualization in
networks. 06 CO5
VI Securing and
Managing storage
infrastructure Securing and Storage Infrastructure:
Information Security Framework, Risk Triad,
Storage Security Domains, Security
Implementations in Storage Networking,
Securing Storage Infrastructure in Virtualized
and Clou d Environments. Managing the
Storage Infrastructure: Monitoring the
Storage Infrastructure, Storage Infrastructure
Management activities, Storage Infrastructure
Management Challenges, Information
Lifecycle Management, Storage Tiering
Self-learning Topics: Case study on SAN
Management and Standards . 08 CO6

Text Books:
1. G. Somasundaram, Alok Shrivastava, EMC Educational Services, ―Information Storage and Management‖, Wiley
India.
2. Storage Virtualization, Author: Clark Tom, Publisher: Addison Wesley Publishing Company
3. Ulf Troppens, Wolfgang Muller -Friedt, Rainer Wolafka, ―Storage Networks Explained‖ Wiley Publication
4. "Introduction to Storage Area Networks" Jon Tate, Pall Beck, Hector Hugo Ibarra, Shanmuganathan Kumaravel,
Libor Miklas, IBM Redbooks.
References:

1. Richard Barker and Paul Massiglia, ìStorage Area Network Essentials: A Complete Guide to Understanding and
Implementing SANsî, Wiley India.
2. Storage Networks: The Complete Reference, by Robert Spalding (Author)
3.―Storage Network Management and Retrieval‖, Vaishali Khairnar, Nilima Dongre. Wiley

Online References:

Page 43

1. https://www.itprc.com/ultimate -guide -to-storage -area-networks/
2. https://www.techtarget.com/searchstorage/definition/storage -area-network -SAN
3. https:/ /www.snia.org/educational -library/object -storage -trends -use-cases -2021
4. https://www.sciencedirect.com/topics/computer -science/network -attached -storage
5. https://www.techtarget.com/searchstorage/tip/Understand -your-storage -infrastructure -management
6. https://sites.google.com/site/testwikiforfirstciscolab/shd/14 -securing -the-storage -infrastructure
7. https://www.techtarget.com/searchdatabackup/tip/What -is-the-difference -between -archives -and-backups

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Modul e randomly selected from all the modules)
 A total of four questions need to be answered .

Page 44

Course Code Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ITDO7012 High
Performance
Computing 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO7012 High
Performance
Computing 20 20 20 80 -- -- -- 100

Course Objectives:

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand fundamentals of parallel Computing . L1,L2
2 Describe different parallel processing platforms involved in achieving High
Performance Computing . L1,L2,L3
3 Demonstrate the principles of Parallel Algorithms and their execution . L1,L2,L3
4 Evaluate the performance of HPC systems . L1,L2,L3,L4
5 Apply HPC programming paradigm to parallel applications . L1,L2,L3
6 Discuss different current HPC Platforms . L1,L2

Prerequisite: Computer Organization, C Programming, Data structures and Algorithm Analysis.
Sr. No. Course Objectives
The course aims:
1 Learn the concepts of high -performance computing .
2 Gain knowledge of platforms for high performance computing .
3 Design and implement algorithms for parallel programming applications .
4 Analyze the performance metrics of High Performance Computing .
5 Understand the parallel programming paradigm, algorithms and applications .
6 Demonstrate the understanding of different High Performance Computing tools .

Page 45

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Computer Organization, C Programming, Data structures and
Algorithm Analysis. 02 --
I Introduction Introduction to Parallel Computing: Motivating Parallelism,
Scope of Parallel Computing, Levels of parallelism (instruction,
transaction, task, thread, memory, function), Models (SIMD,
MIMD, SIMT, SPMD, Dataflow Models, Demand -driven
Computation).

Self-learning Topics: Parallel Architectur es: Interconnection
network, Processor Array, Multiprocessor.
05 CO1
II Parallel
Programming
Platforms Parallel Programming Platforms: Implicit Parallelism:
Dichotomy of Parallel Computing Platforms, Physical
Organization of Parallel Platforms, Communication Costs in
Parallel Machines.

Self-learning Topics: Trends in Microprocessor & Architectures,
Limitations of Memory System Performan ce.
04 CO2
III Parallel
Algorithm
And
Concurrency Principles of Parallel Algorithm Design: Preliminaries,
Decomposition Techniques, Characteristics of Tasks and
Interactions, Mapping Techniques for Load Balancing,
Basic Communication operations: Broadcast and Reduction
Communication types.

Self-learning Topics: Parallel Algorithm Models
09 CO3
IV Performance
Measures for
HPC Performance Measures : Speedup, execution time, efficiency,
cost, scalability, Effect of granularity on performance, Scalability
of Parallel Systems, Amdahl‘s Law, Gustavson‘s Law.

Self-learning Topics: Performance Bottlenecks.
05 CO4
V Programming
Paradigms for
HPC Programming Using the Message -Passing Paradigm : Principles
of Message Passing Programming, The Building Blocks: Send and
Receive Operations, MPI: the Message Passing Interface,
Topology and Embedding.
Parallel Algorithms and Applications :
One-Dimensiona l Matrix -Vector Multiplication, Graph
Algorithms, Sample Sort, Two -Dimensional Matrix Vector
Multiplication.

Self-learning Topics: Introduction to OpenMP.
09 CO5

Page 46

VI General
Purpose
Graphics
Processing
Unit(GPGPU)
Architecture
and
Programming OpenCL Device Architectures, Introduction to OpenCL
Programming .

Self-learning Topics: Introduction to CUDA architecture, and
Introduction to CUDA Programming. 05 CO6

Text Books:
1. AnanthGrama, Anshul Gupta, George Karypis, Vipin Kumar , ―Introduction to Parallel Computing‖, Pearson
Education, Second Edition, 2007.
2. Kai Hwang, Naresh Jotwani, ―Advanced Computer Architecture: Parallelism, Scalability, Programmability‖,
McGraw Hill, S econd Edition, 2010.
3. Edward Kandrot and Jason Sanders, ―CUDA by Example – An Introduction to General Purpose GPU
Programming‖, Addison -Wesley Professional ©, 2010.
4. Georg Hager, Gerhard Wellein, ―Introduction to High Performance Computing for Scientists a nd Engineers",
Chapman & Hall / CRC Computational Science series, 2011.
5. Benedict Gaster, Lee Howes, David Kaeli, Perhaad Mistry, Dana Schaa ,
―Heterogeneous Computing with OpenCL‖ , 2nd Edition, Elsevier, 2012.

References Books :

1. Michael J. Quinn, ―Parallel Programming in C with MPI and OpenMP‖, McGraw -Hill International Editions,
Computer Science Series, 2008.
2. Kai Hwang, Zhiwei Xu, ―Scalable Parallel Computing: Technology, Architecture, Programming‖, McGraw Hill,
1998.
3. Laurence T. Yang, MinyiGuo, ―High - Performance Computing: Paradigm and Infrastructure‖ Wiley, 2006.
4. Fayez Gebali, ―Algorithms and Parallel Computing‖, John Wiley & Sons, Inc., 2011.


Online References:

Sr. No. Website Name
1. https://onlinecourses.nptel.ac.in/noc21_cs46/preview
2. https://onlinecourses.nptel.ac.in/noc22_cs21/preview

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus

Page 47

 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module r andomly selected from all the modules)
 A total of four questions need to be answered .

Course Code Course Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ITDO7013 Infrastructure
Security 03 -- - 03 -- - 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO7013 Infrastructure
Security 20 20 20 80 - - - 100

Course Objectives:

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the concept of vulnerabilities, attacks and protection mechanisms . L1,L2
2 Analyze and evaluate software vulnerabilities and attacks on databases and
operating systems . L1,L2,L3
3 Explain the need for security protocols in the context of wireless communication . L1,L2,L3
4 Understand and explain various security solutions for Cloud infrastructure . L1,L2
5 Understand, and evaluate different attacks on Open Web Applications and Web
services . L1,L2
6 Design appropriate security policies to protect infrastructure components . L1,L2,L3

Prerequisite: Computer Networks, Cryptography and Network Security
Sr. No. Course Objectives
The course aims:
1 To understand underlying principles of infrastructure security.
2 To explore software vulnerabilities, attacks and protection mechanisms to learn security aspects of wireless
network infrastructure and protocols.
3 To investigate web server vulnerabilities and their countermeasures.
4 To investigate cloud infrastructure vulnerabilities and their countermeasures.
5 To learn the different attacks on Open Web Applications and Web services.
6 To learn the different security policies.

Page 48

DETAILED SYLLABUS :

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basic of OSI Model, Topology‘s and Computer
Networks, Cryptography and Network Security. 02 --



I


Introduction Cyber -attacks, Vulnerabilities, Defense Strategies and
Techniques, Authentication Methods - Password, Token
and Biometric, Access Control Policies and Models
(DAC,MAC, RBAC, ABAC, BIBA, Bell La
Padula),
Self-Learning Topics: Authentication and Access
Control Services - RADIUS, TACACS, and TACACS+



04


CO1
Software Vulnerabilities:
Buffer overflow, Format String, Cross -Site Scripting,
SQL Injection, Malware: Viruses, Worms, Trojans, Logic
Bomb, Bots, Rootkits
Operating System Security:

II Software
Security Memory and Address Protection, File
Protection Mechanism, UserAuthentication.
08
CO2
Database Security:
Database Security Requirements, Reliability and
Integrity, Sensitive Data, Inference Attacks, Multilevel
Database Security
Self-Learning Topics: Format String , File System
Security (Windows and Linux OS)


III
Wireless
Security Mobile Device Security - Security Threats,
Device Security, IEEE 802.11xWireless LAN Security,
VPN Security, Wireless Intrusion Detection System
(WIDS)
Self-Learning Topics: Wireshark, Cain and Abel,
Aircrack.

06

CO3


IV
Cloud
Security Cloud Security Risks and Countermeasures,
Data Protection in Cloud, Cloud Application Security,
Cloud Identity and Access Management, Cloud Security
as a Service.
Self-Learning Topics: Metasploit, Ettercap.

06

CO4

Page 49

V




Web Security Web Security Considerations, User
Authentication and Session Management, Cookies, SSL,
HTTPS, SSH, Privacy on Web, Web Browser Attacks,
Account Harvesting, Web Bugs, Clickjacking, Cross - Site
Request Forgery, Session Hijacking and Management,
Phishing and Pharming Techniques, DNS Attacks, Web
Service Security, Secure Electronic Transaction, Email
Attacks, Web Server Security as per OWASP, Firewalls.
Self-Learning Topic s: Penetration Testing tools: SQL
Map, Wapiti.




08



CO5
Information Security Policies, Business Continuity Plan,
VI Security and
Risk Risk Analysis, Incident Management, Legal
System and Cybercrime, Ethical Issues in 05 CO6
Management Security Management.
Self-Learning Topics: The Indian IT Act, Indian Cyber
Law

Text Books:

1. Computer Security Principles and Practice, William Stallings, Sixth Edition, Pearson Education
2. Security in Computing, Charles P. Pfleeger, Fifth Edition, Pearson Education
3. Network Security and Cryptography, Bernard Menezes, Cengage Learning
4. Network Security Bible, Eric Cole, Second Edition, Wiley

References Books :

1. Web Application Hackers Handbook by Wiley.
2. Computer Security, Dieter Gollman, Third Edition, Wiley
3. CCNA Security Study Guide, Tim Boyle, Wiley
4. Introduction to Computer Security, Matt Bishop, Pearson.
5. Cloud Security and Privacy, Tim Mather, Subra Kumaraswamy, Shahed Latif , O‘Riely
6. Nina Godbole, Sunit Belapure, Cyber Security , Wiley India, New Delhi


Online References:
1. https://www.cousera.org
2. https://nptel.ac.in

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format

Page 50

 Question Paper will comprise of a total of six questions each carrying 20 ma rks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) mu st be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered .

Page 51

Course Code Course Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITDO7014
Software Testing
and QA 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO7014
Software
Testing and
QA 20 20 20 80 -- -- -- 100

Course Objectives:

Co
urs
e
Out
co
mes
:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Investigate the reason for bugs and analyze the principles in software testing to
prevent and remove bugs . L1, L2, L3
2 Understand various software testing methods and strategies . L1, L2
3 Manage the testing process and testing metrics . L1, L2, L3
4 Understand fundamental concepts of software automation and use automation
tools . L1, L2
5 Apply the software testing techniques in the real time environment . L1, L2. L3
6 Use practical knowledge of a variety of ways to test software and quality
attributes . L1, L2

Prerequisite: Programming Language (C++, Java), Software Engineering

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Software Engineering Concepts, Basics of programming
Language 02 Sr. No. Course Objectives
The course aims:
1 To provide students with knowledge in Software Testing techniques .
2 To provide knowledge of Black Box and White Box testing techniques .
3 To provide skills to design test case plans for testing software .
4 To prepare test plans and schedules for testing projects .
5 To understand how testing methods can be used in a specialized environment .
6 To understand how testing methods can be used as an effective tool in providing quality assurance
concerning software .

Page 52

I Testing
Methodology
Introduction, Goals of Software Testing, Software Testing
Definitions, Model for Software Testing, Effective
Software Testing vs Exhaustive Software Testing,
Software Failure Case Studies, Software Testing
Terminology, Software Testing Life Cycle (STLC),
Software Testing methodology, Verification and
Validation, Verification requirements, Verification of high
level design, Verification of low level design, validation.

Self-learning Topics: Study any system/application, find
requirement specifications and design the system. Select
software testing methodology suitable to the application. 07 CO1
II Testing
Techniques
Dynamic Testing: Black Box Testing: Boundary Value
Analysis, Equivalence
Class Testing, State Table Based testing,
Cause -Effect Graphing Based Testing,
Error Guessing.
White Box Testing Techniques: need,
Logic Coverage Criteria, Basis Path
Testing, Graph Matrices, Loop Testing,
Data Flow testing, Mutation testing.
Static Testing.
Validation Activities: Unit validation,
Integration, Function , System,
Acceptance Testing.
Regression Testing: Progressive vs.
Regressive, Regression Testing, Regression Testability,
Objectives of Regression Testing,
Regression Testing Types, Define
Problem, Regression Testing Techniques.

Self-learning Topics: Select the test cases (positive and
negative scenarios) for the selected system and Design
Test cases for the system using any two studied testing
techniques. 09 CO2
III Managing the Test
Process
Test Management: test organization,
structure and of testing group, test
planning, detailed test design and test
Specification.
Software Metrics: need, definition and
Classification of software matrices.
Testing Metrics for Monitoring and
Controlling the Testing Process:
attributes and corresponding metrics,
estimation model for testing effort,
architectural design, information flow
matrix used for testing, function point
and test point analysis.
Efficient Test Suite Management:
minimizing the test suite and its
benefits, test suite minimization
problem, test suite prioritization its
type , techniques and measuring
effectiveness.
08 CO3

Page 53

Self-learning Topics: Design quality matrix for your
selected system
IV Test Automation Automation and Testing Tools: need,
categorization, selection and cost in
testing tool, guidelines for testing tools.
Study of testing tools: JIRA, Bugzilla,
TestDirector and IBM Rational
Functional Tester, Selenium etc.

Self-learning Topics: Write down test cases, execute and
manage using studied tools 05 CO4
V Testing for
specialized
environment
Agile Testing, Agile Testing Life
Cycle, Testing in Scrum phases,
Challenges in Agile Testing
Testing Web based Systems: Web
based system, web technology
evaluation, traditional software and
web based software, challenges in
testing for web based software, testing
web based testing

Self-learning Topics: Study the recent technical papers
on software testing for upcoming technolog ies (Mobile,
Cloud, Blockchain, IoT) 04 CO5
VI Quality
Management
Software Quality Management,
McCall‘s quality factors and Criteria,
ISO9000:2000, SIX sigma, Software quality
management

Self-learning Topics: Case Stud ies to Identify Quality
Attributes Relationships for different types of
Applications ( Web based, Mobile based etc.) 04 CO6

Text Books:

1.Software Testing Principles and Practices Naresh Chauhan Oxford Higher Education
2. Software Testing and quality assurance theory and practice by Kshirasagar Naik, Priyadarshi
Tripathy , Wiley Publication

References Books :

1.Effective Methods for Software Testing , third edition by Willam E. Perry, Wiley
Publication
2. Software Testing Concepts and Tools by Nageswara Rao Pusuluri , Dreamtech press

Online References:
1. www.swayam.gov.in
2. www.coursera.org
3. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099 -1689
4.https://onlinecourses.nptel.ac.in/noc17_cs32/preview
5. https://www.youtube.com/channel/UC8w8_H_1uDfi2ftQx7a64uQ

Assessment:
Internal Assessment (IA) for 20 marks:

Page 54

 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
differ ent modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered .
Course Code Course
Name Theory Practical Tutorial Theory Practica l/
Oral Tutorial Total
ITDO7021 Theory
Course 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO7021 Mobile Ad-
hoc Network 20 20 20 80 -- -- -- 100

Course Objectives:

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the fundamentals of Mobile ad -hoc Networks . L1,L2
2 Understand and be able to use advanced concept of MAC layer protocols more
effectively . L1,L2
3 Analyse different routing technologies for designing a routing protocol . L1,L2,L3,L4 Sr. No. Course Objectives
The course aims:
1 To identify and distinguish major issues associated with ad -hoc networks.
2 To analyze the basic concepts for designing a routing protocol for MANETs.
3 To explore and analyze routing protocols of Ad -hoc network.
4 To learn the concepts of Transport layer and Security issues for MANETs.
5 To apply fundamental principles characteristics of QoS and understand the need of Energy Management in
wireless ad -hoc network.
6 To learn the basic concepts of Sensor Networks for Communication in Mobile Ad -hoc network.

Page 55

4 Understand the concepts of Transport layer and security features of Ad -hoc
network . L1,L2
5 Create the awareness of QoS and Energy Management in Ad hoc network . L6
6 Demonstrate the ability of wireless sensor network . L2,L3,L4

Prerequisite: Wireless Technology .

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Fundamentals of Wireless Communication, Wireless
Metropolitan and Local Area Networks: IEEE 802.16
(WiMax) – Mesh mode, IEEE 802.11(Wi -Fi) –
Architecture, Wireless Ad hoc Networks: WPAN Device
Architecture, Wireless Sensor Network Applications,
Advantages and Limitations, Wireless Network Security:
Security in GSM; UMTS Security; Bluetooth Security;
WEP. 02 --
I Introduction to Ad -
hoc Wireless
Networks Introduction: Cellular and Ad Hoc Wireless Networks,
Applications of Ad Hoc Wireless Networks,
Issues In Ad Hoc Wireless Networks: Medium Access
Scheme, Routing, Multicasting, Transport Layer
Protocols, Pricing, Quality of Service Provisioning,
Addressing and Service Discovery, Energy Management,
Scalability, Deployment Considerations,
Ad Hoc Wirel ess Internet
Self-learning Topics: Global Mobile Ad Hoc Network
Market 05 CO1
II Medium Access
Control Protocols Issues in Designing a MAC Protocol, Design Goals of
MAC Protocols, Classification of MAC protocols,
Contention -Based Protocols with Reservation
Mechanisms and Scheduling Mechanisms, IEEE 802.11a
and HiperLan standard
Self-learning Topics:
MAC Protocols that use Directional Antennas and Other
MAC Protocols 07 CO2
III Routing Protocols Routing Protocols inAd -hoc Wireless Networks:
Introduction, Design issues, Classification of
Routing Protocols: Routing information update
mechanism, Use of temporal information for routing,
Routing topology, Utilization of specific resources,
Multicast Routing in Ad -hoc Wireless Networks :
Introduction, Design Issues, Operation of Multicast
Routing Protocols, An Architecture Reference Model
for Multicast Routing Protoc ols

Self-learning Topics: Table Driven Routing Protocols,
Classifications of Multicast Routing Protocols 08 CO3
IV Transport Layer and
Security Protocols Transport Layer in Ad -hoc Wireless Networks :
Introduction, Design Issues and Goals of a Transport
Layer Protocol; Classification of
Transport Layer Solutions.
Security in Ad -hoc Wireless Networks: Issues and 07 CO4

Page 56

Challenges
in Security Provisioning, Network Security Attacks
classification.
Self-learning Topics:
TCP over Transport Layer Solutions, Key Manag ement
and Secure Touting
V Quality of Service
and Energy
Management Quality of Servicein Ad -hoc Wireless Networks :
Introduction, Issues and Challenges in Providing QoS in
Ad-hoc Wireless Networks, Classification of QoS
Solutions

Energy Management inAd -hoc Wireless Networks :
Introduction, Need for Energy Management in Ad -hoc
Wireless Networks,
Classification of Energy Management Schemes

Self-learning Topics:
MAC Layer Solutions
Battery Management Schemes 06 CO5
VI Wireless Sensor
Networks Introduction, Sensor Network Architecture, Data
Dissemination, Data Gathering
Self-learning Topics:
Location Discovery and Quality of a Sensor Network 04 CO6



Text Books:

1. C. S. Ram Murthy, B. S. Manoj, ―Ad Hoc Wireless Networks: Architectures and Protocols‖,
Prentice Hall of India, 2nd Edition, 2005
2. C. K. Toh, ―Adhoc Mobile Wireless Networks‖, Pearson Education, 2002
3. Wireless Communications & Networks, By William Stallings, Second Edition, Pearson Education

References Books :

1. Shih-Lin W u Yu -Chee Tseng, ―Wireless Ad Hoc Networking: Personal -Area, Local -Area, and the Sensory -Area
Networks‖, Auerbach Publications, 2007
2. Subir Kumar Sarkar, ―Adhoc Mobile Wireless Network: Principles, Protocols and Applications‖ CRC Press
3. Prashant Mohapa tra and Sriramamurthy, ―Ad Hoc Networks: Technologies and Protocols‖, Springer International
Edition, 2009

Online References:
1. https://www.cousera.org
2. https://nptel.ac.in

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Tes t
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus

Page 57

 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered .









































Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITDO7022 ARVR 03 -- -- 03 -- -- 03

Page 58

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test2 Avg. of 2
Tests
ITDO7022 ARVR
20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives
The course aims:
1 To understand the concepts of Augmented Reality and related technologies.
2 To understand the AR tracking system and use of computer vision in AR/MR.
3 To describe the technology for multimodal user interaction and authoring in AR.
4 To understand primitives of computer graphics fundamental.
5 To analyze various Hardware devices suitable for VR.
6 To analyze visual physiology and issues related to it.

Course Outcomes:

Sr.
No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify and compare different Augmented Reality and Mixed Reality
Technologies. L1, L2
2 Apply concepts of Computer Vision for tracking in AR and MR Systems. L3
3 Model different interfaces and authoring in AR/MR. L3
4 Solve Computer Graphics Problems. L1
5 Analyze application of VR hardware and software components. L1, L2, L3
6 Identify issues related to visual physiology. L1, L2

Prerequisite : Programming Language, Computer Graphics, Virtual Reality

DETAILED SYLLABUS:

Module Title Description Hours CO
0 Pre-requisite Basics of Computer Graphics, Coordinate Systems, VR Introduction,
Tracking in VR 02 --
I Introduction to
Augmented
Reality and
Mixed Reality Definition and Scope, A Brief History of Augmented Reality, AR
Architecture, Related Fields of AR (like Mixed Reality, Virtual
Reality, Immersive Reality, Extended Reality) and Their comparison,
General Architecture of Mixed Reality System, Algorithm Steps in
Mixed Reality

Self-Learning Topics : How AR/MR are related to Ubiquitous
Computing, Multidimensional Systems. 04 CO1
II Tracking and Multimodal Displays; Visual Perception; Spatial Display Model; 06 CO2

Page 59

Computer
Vision for AR
and MR Visual Displays; Tracking, Calibration and Registration; Coordinate
Systems; Characteristics of Tracking Technology; Stationary Tracking
Systems; Mobile Sensors; Optical Tracking; Sensor Fusion; Marker
Tracking; Multiple Camera Infrared Tracking; Natural Feature
Tracking by Detection; Incremental Tracking; Simultaneous
Localizatio n and Tracking; Outdoor Tracking

Self-Learning Topics : Indoor Tracking, Full Body Tracking
III Interaction,
Modeling and
Annotation
and Authoring Output Modalities, Input Modalities, Tangible Interfaces, Virtual User
Interfaces on Real Surfaces, Multi -view Interfaces, Haptic Interaction,
Multimodal Interaction, Specifying Geometry, Specifying Appearance,
Semi -automatic Reconstruction, Free -form Modeling, Annotation,
Requirement of AR Authoring, Elements of Authoring, Stand -alone
Authoring Solution s, Plug -in Approaches, Web Technology

Self-Learning Topics : Case Study on Object Annotation in Real
Time, Avatar Modeling. 06 CO3
IV Geometry of
Virtual World
Geometric Modeling, 2D transformations, Homogenous coordinate
system, 3D rotation and 6 degree of freedom, Viewport
Transformation
Self: Eye Transformation, demo of 2D transformation 08 CO4
V Introduction to
VR
Introduction to VR and definitions and its components.,
Hardware components: Display devices: LCD, OLED
Audio: Speakers, Earphones, Bone conduction
Touch: Haptic Device
GPU and CPU, Input devices like game controller, data glows,
Joysticks
Tracking Hardware: Industrial measurement Unit -IMU, Gyroscope,
accelerometer
Software component: Java3D, VRML
Self: Feedback mechanisms in
VR environ ment
07 CO5
VI Visual
Physiology,
perception and
tracking
Functioning of Eye with photoreceptors, Resolution for VR, Eye
movements and issues with it in VR, Neuroscience of vision, Depth
and motion perception, Frame rates and display, Orientation tracking,
tilt and yaw drift correction, Tracking with camera
Self: Light House approach 06 CO6


Textbooks :
1. Dieter Schmalsteig and Tobias Hollerer, ―Augmented Reality - Principles and Practice‖, Pearson Education, Inc.
2016 Edition.
2. Chetankumar G Shetty, ―Augmented Reality - Theory, Design and Development‖, Mc Graw Hill, 2020 Edition.
3. Alan B. Craig, ―Understanding Augmented Reality – Concepts and Applications‖, Morgan Kaufmann, Elsevier,
2013 Edition.
4. . Hearn and Baker, ―Computer Graphics - C version‖, 2nd edition, Pearson, 2002.
5. . R. K Maurya, ―Computer Graphics with Virt ual Reality‖, 3rd Edition, Wiley India, 2018.
6. . Steven M. LaVelle,‖ Virtual Reality‖, Cambridge University press, 2019
7. . Grigore Burdea, Philippe Coiffet, ―Virtual Reality Technology‖, 2nd Edition, Wiley India,
2003
8. . Vince, ―Virtual Reality Systems‖, 1st Edition, Pearson Education, 2002

References Books :

Page 60

1. Borko Furht, ―Handbook of Augmented Reality‖, Springer, 2011 Edition.
2. Erin Pangilinan, Steve Lukas, and Vasanth Mohan, ―Creating Augmented and Virtual Realities - Theory and Practice for
Next -Generation Spatial Computing‖, O‘Reilly Media, Inc., 2019 Edition.
3. Jens Grubert, Dr. Raphael Grasset, ―Augmented Reality for Android Application Development‖, PACKT Publishing,
2013 Edition.
4. George Mather, ―Foundations of Sensation and Perception‖ , Psychology Press book; 3rd
Edition, 2016
5. Tony Parisi, ― Learning Virtual Reality‖, 1st edition, O‘Reilly, 2015
6. Alan Craig and William Sherman,‖ Understanding virtual reality: Interface, application and
design‖, 2nd Edition, Morgan Kaufmann Publisher, 2019
7. Peter Shirley, Michael Ashikhmin, and Steve Marschner, ―Fundamentals of Computer
Graphics‖ ,A K Peters/CRC Press; 4th Edition, 2016.

Online Resources:

Sr. No. Website Name
1. www.nptel.ac.in
2. www.coursera.org
3. https://nptel.ac.in/courses/121/106/121106013/#
4. http://msl.cs.uiuc.edu/vr/
5. http://lavalle.pl/vr/

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remain ing questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered .

Page 61

Course Code Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ITDO7023 Quantum
Computing 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test2 Avg. of 2
Tests
ITDO7023 Quantum
Computing 20 20 20 80 -- -- -- 100

Course Objectives:

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Basics of Quantum computing and its applications. L1,L2
2 Solve various problems using quantum algorithms. L1,L2
3 Methodology for quantum computers and their principles. L1,L2,L3
4 Comprehend quantum noise and operations. L1,L2,L3
5 Gain knowledge about different quantum error correction techniques. L1,L2,L3
6 To gain knowledge about different quantum cryptographic algorithms. L1,L2,L3

Prerequisite: NA

DETAILED SYLLABUS :

Sr.
No. Module Detailed Content Hours CO
Mapping
I FUNDAMENTA
LS OF
QUANTUM Fundamental Concepts: Introduction and Overview – Global
Perspectives – Quantum Bits – Quantum Computation –
Quantum Algorithms – Experimental Quantum Information 07 CO1 Sr. No. Course Objectives
The course aims:
1 To know the fundamentals of Quantum computing and its applications.
2 To understand the efficient quantum algorithms for several basic promise problems.
3 To gain knowledge about quantum computers and their principles.
4 To understand the principles, quantum information and limitation of quantum operations formalizing.
5 To gain knowledge about different quantum error and its correction techniques.
6 To gain knowledge about different quantum cryptographic algorithms.

Page 62

COMPUTING Processing – Quantum Information. Problems on Qubits
Self-learning Topics: Detail ofQuantum c omputing and its
applicationshttps://www.ibm.com/quantum -computing/what -is-
quantum -computing/
II
QUANTUM
COMPUTATIO
N Quantum Circuits – Quantum algorithms, Single Orbit
operations, Control Operations, Measurement, Universal
Quantum Gates, Simulation of Quantum Systems, Quantum
Fourier transform, Phase estimation, Applications, Quantum
search algorithms – Quantum counting – Speeding up the
solution of NP – complete problems – Quantum Search for an
unstructured database. Problems on Boolean functions and
Quantum gates, Quantum gates and circuits.
Self-learning Topics: Application of Quantum Computing 08 CO2
III QUANTUM
COMPUTERS Guiding Principles, Conditions for Quantum Computation,
Harmonic Oscillator Quantum Computer, Optical Photon
Quantum Computer – Optical cavity Quantum electrodynamics,
Ion traps, Nuclear Magnetic resonance.
Self-learning Topics: Qiskit 06 CO3
IV QUANTUM
INFORMATION
S Quantum noise and Quantum Operations – Classical Noise and
Markov Processes, Quantum Operations, Examples of Quantum
noise and Quantum Operations – Applications of Quantum
operations, Limitations of the Quantum operations formalism,
Distance Measures for Quantum information. Problems on
Measurement
Self-learning Topics: Case study on Quantum noise and
operations. 07 CO4
V QUANTUM
ERROR
CORRECTION Introduction, Shor code, Theory of Quantum Error –Correction,
Constructing Quantum Codes, Stabilizer codes, Fault – Tolerant
Quantum Computation.
Self-learning Topics: Case study on Quantum error correction. 05 CO5
VI QUANTUM
CRYPTOGRAP
HY Quantum Cryptography -Private Key Cryptography, Privacy
Amplification and Information Reconciliation, Quantum Key
Distribution, Privacy and Coherent Information, The Security of
Quantum Key Distribution. Problems on Quantum error
correction and cryptography.
Self-learning Topics:
Attacks on Quantum Cryptography 06 CO6

Text Books:

1. Chris Bernhardt,‖ Quantum Computing for Everyone‖, (The MIT Press) Hardcover – Illustrate ,September 2020,
2. Willi -Hans Steeb; ―Problems and Solutions in Quantum Computing and Quantum Information‖, Yorick Hardy
Academic Consulting and Editorial Services (ACES) Private Limited, January 2020.
3. M.A. Nielsen and I.Chuang,―Quantum Computation and Quantum Information‖, Cambridge University Press 2010.
References Books :

1. Computer Science: An Introduction by N. DavidMermin 5. Yanofsky's and Mannucci, Quantum Computing for
Computer Scientists.
2. Parag K. Lala ,Quantum Computing: A Beginner's Introduction Paperback‖ , McGraw Hill November 2020.
3. V. Sahni, ―Quantum Computing‖, Tata McGraw -Hill Publishing company,2007.
4. Nayak, Chetan; Simon, Steven; Stern, Ady; Das Sarma, Sankar, ― NonabelianAnyons and Quantum Computation‖,
2008.

Page 63

Online References:
1. https://www.cousera.org
2. https://nptel.ac.in


Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered .


























Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITDO7024 Information
Retrieval
System 03 -- -- 03 -- -- 03

Page 64

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO7024 Information
Retrieval
System 20 20 20 80 -- -- -- 100

Course Objectives:

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Define and describe the objectives of the basic concepts of the Information
retrieval system . L1,L2
2 Evaluate the taxonomy of different information retrieval models . L1,L2,L3,L4
3 Try to s olve and process text and multimedia retrieval queries and their
operations . L1,L2
4 Evaluate text processing techniques and operations in the information retrieval
system . L1,L2,L3,L4
5 Demonstrate and evaluate various indexing and searching tec hniques . L1,L2,L3,L4
6 Design the user interface for an information retrieval system . L1,L2,L3,L4

Prerequisite: Data Structures

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Indexing and searching Algorithms 02
I Introduction
Motivation, Basic Concepts, The Retrieval Process,
Information System: Components, parts and types on 06 CO1 Sr. No. Course Objectives
The course aims:
1 To learn the fundamentals of the information retrieval system .
2 To classify various Information retrieval models .
3 To demonstrate the query processing techniques and operation s.
4 To compare the relevance of query languages for text and multimedia data .
5 To evaluate the significance of various indexing and searching techniques for information retrieval .
6 To develop an effective user interface for information retrieval .

Page 65

information system; Definition and objectives on
information retrieval system , Information versus Data
Retrieval. Search Engines and browsers
Self-learning Topics: Search Engines , Search API
II IR Models Modeling: Taxonomy of Information Retrieval Models,
Retrieval: Formal Characteristics of IR models, Classic
Information Retrieval, Alternative Set Theoretic
models, Probabilistic Models, Structured text retrieval
Models, models for Browsing;

Self-learning Topics: Terrier 06 CO2
III Query Processing
and Operations
Query Languages: Keyword based Querying, Pattern
Matching, Structural Queries, Query Protocols; Query
Operations: User relevance feedback, Multimedia IR
models: Data Modeling

Self-learning Topics: Proximity Queries and
Wildcard Queries
06 CO3
IV Text Processing Text and Multimedia languages and properties:
Metadata, Markup Languages, Multimedia; Text
Operations: Document Preprocessing, Document
Clustering.

Self-learning Topics: Digital Library : Greenstone 06 CO4
V Indexing and
Searching
Inverted files, Other indices for text, Boolean Queries,
Sequential Searching, Pattern Matching, Structural
Queries, Compression; Multimedia IR: Indexing and
Searching: - A Generic Multimedia indexing approach, ,
Automatic Feature extraction; Searching Web:
Challeng es, Characterizing the web, Search Engines.
Browsing, Meta searches, Searching using Hyperlinks.
Self-learning Topics: Koha 07 CO5
VI User interface and
visualization
Human Computer interaction, the information access
process, starting points, query specifications, context,
using relevance judgments, interface support for the
search process.

Self-learning Topics: SeeSoft 06 CO6


Text Books:

1. Modern Information Retrieval, Ricardo Baeza -Yates,berthier Ribeiro - Neto, ACM Press - Addison Wesley
2. Information Retrieval Systems: Theory and Implementation, Gerald Kowaski, Kluwer Academic Publisher
3. Storage Network Management and Retrieval by Dr. Vaishali Khairnar, Nilima Dongre, Wiley India .

References Books :

1. Introduction to Information Retrieval By Christopher D. Manning and Prabhakar Raghavan, Cambridge University
Press.
2. Information Storage & Retrieval By Robert Korfhage – John Wiley & Sons
3. Introduction to Modern Information Retrieval. G.G. Chowdhury. NealSchuman.

Online References:

Page 66

1. https://www.ge eksforgeeks.org/what -is-information -retrieval/
2. https://nlp.stanford.edu/IR -book/
3. https://en.wikipedia.org/wiki/Information_retrieval
4. https://people.ischool.berkeley.edu/~hearst/irbook/10/node1.html


Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
 A total of four questions need to be answered .
























Course Code Course Name Credits
ILO7011 Product Life Cycle Management 03

Page 67

Course Objectives: Students will try :
1. To familiarize the students with the need, benefits and components ofPLM
2. To acquaint students with Product Data Management & PLMstrategies
3. To give insights into new product development program and guidelines for designing and
developing aproduct
4. To familiarize the students with Virtual ProductDevelopment

Course Outcomes: Students will be able to :
1. Gain knowledge about phases of PLM, PLM strategies and methodology for PLM feasibility
study and PDMimplementation.
2. Illustrate various approaches and tech niques for designing and developingproducts.
3. Apply product engineering guidelines / thumb rules in designing products for moulding,
machining, sheet metal workingetc.
4. Acquire knowledge in applying virtual product development tools for components, machining
and manufacturingplant



Module
Detailed Contents
Hrs



01 Introduction to Product Lifecycle Management (PLM): Product Lifecycle
Management (PLM), Need for PLM, Product Lifecycle Phases, Opportunities of
Globalization, Pre -PLM Environment, PLM Paradigm, Importance & Benefits of PLM,
Widespread Impact of PLM, Focus and Application, A PLM Project, Starting the PLM
Initiative, PLMApplications
PLM Strategies: Industrial strategies, Strategy elements, its identification, selection and
implementation, Developing PLM Vision and PLM Strategy ,
Change management for PLM 10





02 ProductDesign: Product Design and Development Process, Engineering Design,
Organization and Decomposition in Product Design, Typologies of Design Process
Models, Reference Model, Product Design in the Context of the Product Development
Process, Relation with the Development Process Planning Phase, Relation with the Post
design Planning Phase, Methodological Evolution in Product Design, Concurrent
Engineering, Characteristic Features of Concurrent Engineering, Concurrent
Engineering and Life Cycle Approach, New Product Development (NPD) and
Strategies, Product Configuration and Variant Management, The Design for X System,
Objective Properties and Design for X
Tools, Choice of Design for X Tools and Their Use in the Design Process 09

03 Product Data Management (PDM): Product and Product Data, PDM systems and
importance, Components of PDM, Reason for implementing a PDM system,
financial justification of PDM, barriers to PDM implementation 05
04 Virtual Product Development Tools: For components, machines, and
manufacturing plants, 3D CAD systems and realistic rendering techniques, 05

Page 68

Digital mock -up, Model building, Model analysis, Modeling and simulations in Product
Design, Examples/Case studies


05 Integration of Environmental Aspects in Product Design: Sustainable
Development, Design for Environment,Need for Life Cycle Environmental Strategies,
Useful Life Extension Strategies, End -of-Life Strategies, Introduction of Environmental
Strategies into the Design Process, Life Cycle Environmental Strategies and
Considerations for Product Design 05


06 Life Cycle Assessment and Life Cycle Cost Analysis: Properties, and
Framework of Life Cycle Assessment, Phases of LCA in ISO Standards, Fields of
Application and Limitations of Life Cycle Assessment, Cost Analysis and the Life
Cycle Approach, General Framework for LCCA, Evolution of Models for Product Life
Cycle Cost Analysis 05


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the questio n paper.Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.


REFERENCES:

1. John Stark, ―Product Lifecycle Management: Paradigm for 21st Century Product Realisation‖, Springer -
Verlag, 2004. ISBN:1852338105
2. Fabio Giudice, Guido La Rosa, AntoninoRisitano, ―Product Design for the environment -A life cycle
approach‖, Taylor & Francis 2006, ISBN:0849327229
3. SaaksvuoriAntti, ImmonenAnselmie, ―Product Life Cycle Management‖, Springer, Dreamtech,
ISBN:3540257314
4. Michael Grieve, ―Product Lifecycle Management: Driving the next generation of lean thinking‖, Tata
McGraw Hill, 2006, ISBN:0070636265

Page 69

Course Code Course Name Credits
ILO7012 Reliability Engineering 03


Objectives:
1. To familiarize the students with various aspects of probabilitytheory
2. To acquaint the students with reliability and itsconcepts
3. To introduce the students to methods of estimating the system reliability of simple and complexsystems
4. To understand the various aspects of Maintainability, Availability and FMEAprocedure

Outcomes: Learner will be able to…
1. Understand and apply the concept of Probability to engineeringproblems
2. Apply various reliability concepts to calculate different reliabilityparameters
3. Estimate the system reliability of simple and complexsystems
4. Carry out a Failure Mode Effect and CriticalityAnalysis



Module
Detailed Contents
Hrs


01 Probability theory: Probability: Standard definitions and concepts; Conditional
Probability, Baye‘s Theorem.
Probability Distributions: Central tendency and Dispersion; Binomial, Normal,
Poisson, Weibull, Exponential, relations between them and their significance.
Measures of Dispersion: Mean, Median, Mode, Range, Mean Deviation,
Standard Deviation, Variance, Skewness and Kurtosis.

08


02 Reliability Concepts: Reliability definitions, Importance of Reliability, Quality
Assurance and Reliability, Bath Tub Curve.
Failure Data Analysis: Hazard rate, failure density, Failure Rate, Mean Time To
Failure (MTTF), MTBF, ReliabilityFunctions.
Reliability Hazard Models: Constant Failure Rate, Linearly increasing, Time
Dependent Failure Rate, Wei bull Model. Distribution functions and reliability analysis.

08
03 System Reliability: System Configurations: Series, parallel, mixed
configuration, k out of n structure, Complex systems. 05

04 Reliability Improvement: Redundancy Techniques: Element redundancy, Unit
redundancy, Standby redundancies. Markov analysis.
System Reliability Analysis – Enumeration method, Cut -set method, Success
Path method, Decomposition method.
08


05 Maintainability and Availability: System downtime, Design for Maintainability:
Maintenance requirements, Design methods: Fault Isolation and self -diagnostics, Parts
standardization and Interchangeability, Modularization and Accessibility, Repair
VsReplacement.
Availability – qualitative aspects.
05

06 Failure Mode, Effects and Criticality Analysis: Failure mode effects analysis,
severity/criticality analysis, FMECA examples. Fault tree construction, basic symbols,
development of functional reliability block diagram, Fau1t tree
analysis and Event tree Analysis
05


Assessment :

Page 70

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.


REFERENCES:

1. L.S. Srinath, ―Reliability Engineering‖, Affiliated East -Wast Press (P) Ltd.,1985.
2. Charles E. Ebeling, ―Reliability and Maintainability Engineering‖, Tata McGraw Hill.
3. B.S. Dhillion, C. Singh, ―Engineering Reliability‖, John Wiley & Sons,1980.
4. P.D.T. Conor, ―Practical Reliability Engg.‖, John Wiley & Sons,1985.
5. K.C. Kapur, L.R. Lamberson, ―Reliability in Engineering Design‖, John Wiley &Sons.
6. Murray R. Spiegel, ―Probability and Statistics‖, Tata McGraw -Hill Publishing Co.Ltd.

Page 71

Course Code Course Name Credits
ILO7013 Management Information System 03


Objectives:
1. The course is blend of Management and Technicalfield.
2. Discuss the roles played by information technology in today‘s business and define various
technology architectures on which information systems arebuilt
3. Define and analyze typical functional information systems and identify how they meet the needs
of the firm to deliver efficiency and competitiveadvantage
4. Identify the basic steps in systemsdevelopment

Outcomes: Learner will be able to…
1. Explain how information systems TransformBusiness
2. Identify the impact information systems have on anorganization
3. Describe IT infrastructure and its components and its currenttrends
4. Understand the p rincipal tools and technologies for accessing information from databases to improve
business performance and decisionmaking
5. Identify the types of systems used for enterprise -wide knowledge management and how they provide
value forbusinesses



Module
Detailed Contents
Hrs

01 Introduction To Information Systems (IS): Computer Based Information Systems,
Impact of IT on organizations, Imporance of IS to Society.
Organizational Strategy, Competitive Advantages and IS.
4

02 Data and Knowledge Management: Database Approach, Big Data, Data warehouse and
Data Marts, Knowledge Management.
Business intelligence (BI): Managers and Decision Making, BI for Data analysis
and Presenting Results
7
03 Ethical issues and Privacy: Information Security. Threat to IS, and Security
Controls 7

04 Social Computing (SC): Web 2.0 and 3.0, SC in business -shopping, Marketing,
Operational andAnalytic CRM, E-business and E -commerce – B2B B2C.
Mobile commerce.
7
05 Computer Networks Wired and Wireless technology, Pervasivecomputing,
Cloud computing model. 6

06 Information System within Organization: Transaction Processing Systems, Functional
Area Information System, ERP and ERP support of Business Process. Acquiring
Information Systems and Applications: Various System development
life cycle models.
8


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

Page 72

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proport ional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.


REFERENCES:

1. Kelly Rainer, Brad Prince,Management Information Systems,Wiley
2. K.C. Laudon and J.P. Laudon, Management Information Systems: Managing the DigitalFirm, 10th Ed.,
Prentice Hall,2007.
3. D. Boddy, A. Boonstra, Managing Information Systems: Strategy and Organization, Prentice
Hall,2008

Page 73

Course Code Course Name Credits
ILO7014 Design of Experiments 03


Objectives:
1. To understand the issues and principles of Design of Experiments(DOE)
2. To list the guidelines for designingexperiments
3. To become familiar with methodologies that can be used in conjunction with experimental designs for
robustness andoptimization

Outcomes: Learner will be able to…
1. Plan data collection, to turn data into information and to make decisions that lead to appropriate action
2. Apply the methods taught to real lifesituations
3. Plan, analyze, and interpret the results ofexperiments



Module
Detailed Contents
Hrs


01 Introduction
Strategy ofExperimentation
Typical Applications of ExperimentalDesign
Guidelines for DesigningExperiments
Response SurfaceMethodology

06



02 Fitting Regression Models
Linear Regression Models
Estimation of the Parameters in Linear RegressionModels
Hypothesis Testing in MultipleRegression
Confidence Intervals in MultipleRegression
Prediction of new responseobservation
Regression modeldiagnostics
Testing for lack offit


08



03 Two -Level Factorial Designs
The 22Design
The 23Design
The General2kDesign
A Single Replicate of the 2kDesign
The Addition of Center Points to the 2kDesign,
Blocking in the 2k FactorialDesign
Split -PlotDesigns


07



04 Two -Level Fractional Factorial Designs
The One -Half Fraction of the 2kDesign
The One-Quarter Fraction of the 2kDesign
The General 2k-p Fractional FactorialDesign
Resolution III Designs
Resolution IV and VDesigns
Fractional Factorial Split -PlotDesigns


07

Page 74

05 Response Surface Methods and Designs
Introduction to Response SurfaceMethodology
The Method of SteepestAscent
Analysis of a Second -Order ResponseSurface
Experimental Designs for Fitting ResponseSurfaces

07

06 Taguchi Approach
Crossed Array Designs and Signal -to-NoiseRatios
AnalysisMethods
Robust design examples
04


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.


REFERENCES:

1. Raymond H. Mayers, Douglas C. Montgomery, Christine M. Anderson -Cook, Response Surface
Methodology: Process and Product Optimization using Designed Experiment, 3rd edition,John
Wiley & Sons, New York,2001
2. D.C. Montgomery, Design and Analysis of Experiments, 5th edition, John Wiley &Sons, New
York,2001
3. George E P Box, J Stuart Hunter, William G Hunter, Statics for Experimenters: Design,
Innovation and Discovery, 2nd Ed.Wiley
4. W J Dimond, Peactical Experiment Designs for Engineers and Scintists, John Wiley and Sons Inc.
ISBN:0 -471-39054 -2
5. Design and Analysis of Experiments (Springer text in Statistics), Springer by A.M. Dean,and
D.T.Voss

Page 75

University of Mumbai, B. E. (Information Technology), Rev 2016 220 Course Code Course Name Credits
ILO7015 Operations Research 03


Objectives:
1. Formulate a real -world problem as a mathematical programmingmodel.
2. Understand the mathematical tools that are needed to solve optimizationproblems.
3. Use mathematical software to solve the proposedmodels.

Outcomes: Learner will be able to…
1. Understand the theoretical workings of the simplex method, the relationship between a linear program
and its dual, including strong duality and complementaryslackness.
2. Perform sensitivity analysis to determine the direction and magnitude of chang e of a model‘s optimal
solution as the datachange.
3. Solve specialized linear programming problems like the transportation and assignment problems, solve
network models like the shortest path, minimum spanning tree, and maximum flowproblems.
4. Understand the a pplications of integer programming and a queuing model and compute important
performancemeasures



Module
Detailed Contents
Hrs









01 Introduction to Operations Research :Introduction, , Structure of the
Mathematical Model, Limitations of OperationsResearch
Linear Programming :Introduction, Linear Programming Problem,
Requirements of LPP, Mathematical Formulation ofLPP, Graphical method, Simplex
Method Penalty Cost Method or Big M-method, Two Phase Method, Revised simplex
method, Duality , Primal – Dual construction, Symmetric and Asymmetric Dual, Weak
Duality Theorem, Complimentary Slackness Theorem, Main Duality Theorem, Dual
Simplex Method, Sensitivity Analysis Transportation Problem : Formulation, solution,
unbalanced Transportation prob lem. Finding basic feasible solutions – Northwest corner
rule, least cost method and Vogel‘s approximation method. Optimality test: the stepping
stone method and MODImethod.
Assignment Problem : Introduction, Mathematical Formulation of the Problem,
Hungari an Method Algorithm, Processing of n Jobs Through Two Machines and m
Machines, Graphical Method of Two Jobs m Machines Problem Routing Problem,
Travelling SalesmanProblem
Integer Programming Problem : Introduction, Types of Integer Programming
Problems, Gomory‘s cutting plane Algorithm, Branch and Bound Technique.
Introduction to Decomposition algorithms.








14

02 Queuing models : queuing systems and structures, single server and multi -server
models, Poisson input, exponential service, constant rate service, finite and infinite
population
05
03 Simulation : Introduction, Methodology of Simulation, Basic Concepts, 05

Page 76

University of Mumbai, B. E. (Information Technology), Rev 2016 221 Simulation Procedure, Application of Simulation Monte -Carlo Method:
Introduction, Monte -Carlo Simulation, Applications of Simulation, Advantages of
Simulation, Limitations of Simulation

04 Dynamic programming . Characteristics of dynamic programming.Dynamic
programming approach for Priority Management employment smoothening,
capital budgeting, Stage Coach/Shortest Path, cargo loading and Reliability problems.
05

05 Game Theory . Competitive games, rectangular game, saddle point, minimax
(maximin) method of optimal strategies, value of the game. Solution of games with
saddle points, dominance principle. Rectangular games without saddle point – mixed
strategy for 2 X 2games.
05
06 Inventory Models : Classical EOQ Models, EOQ Model with Price Breaks,
EOQ with Shortage, Probabilistic EOQ Model, 05

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respect ive lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.


REFERENCES:

1. Taha, H.A. "Operations Research - An Introduction", Prentice Hall, (7th Edition), 2002.
2. Ravindran, A, Phillips, D. T and Solberg, J. J. "Operations Research: Principles and Practice", John
Willey and Sons, 2nd Edition,2009.
3. Hiller, F. S. and Liebermann, G. J. "Introduction to Operations Research", Tata McGraw Hill, 2002.
4. Operations Research, S. D. Sharma, KedarNath RamNath -Meerut.
5. Operations Research, KantiSwarup, P. K. Gupta and Man Mohan, Sultan Chand &Sons.

Page 77

University of Mumbai, B. E. (Information Technology), Rev 2016 222 Course Code Course Name Credits
ILO7016 Cyber Security and Laws 03


Objectives:
1. To understand and identify different types cybercrime and cyber law
2. To recognized Indian IT Act 2008 and its latestamendments
3. To learn various types of security standardscompliances

Outcomes: Learner will be able to…
1. Understand the concept of cybercrime and its effect on outsideworld
2. Interpret and apply IT law in various legalissues
3. Distinguish different aspects of cyber law
4. Apply Information Security Standards compliance during software design anddevelopment



Module
Detailed Contents
Hrs

01 Introduction to Cybercrime: Cybercrime definition and origins of the world,
Cybercrime and information security, Classifications of cybercrime, Cybercrime and the
Indian ITA 2000, A global Perspective on cybercrimes.
4




02 Cyber offenses & Cybercrime: How criminal plan the attacks, Social Engg, Cyber
stalking, Cyber café and Cybercrimes, Bot nets, Attack vector, Cloud computing,
Proliferation of Mobile and Wireless Devices, Trends in Mobility, Credit Card Frauds in
Mobile and Wireless Computing Era, Security Challenges Posed by Mobile Devices,
Registr y Settings for Mobile Devices, Authentication Service Security, Attacks on
Mobile/Cell Phones, Mobile Devices: Security Implications for Organizations,
Organizational Measures for Handling Mobile, Devices -Related Security Issues,
Organizational Security Po licies and Measures in Mobile
Computing Era, Laptops



9

03 Tools and Methods Used in Cyber line
Phishing, Password Cracking, Key loggers and Spywares, Virus and Worms,
Steganography, DoS and DDoS Attacks, SQL Injection, Buffer Over Flow, Attacks on
Wireless Networks, Phishing, Identity Theft (ID Theft)
6


04 The Concept of Cyberspace
E-Commerce , The Contract Aspects in Cyber Law ,The Security Aspect of Cyber
Law ,The Intellectual Property Aspect in Cyber Law
, The Evidence Aspect in Cyber Law , The Criminal Aspect in Cyber Law, Global
Trends in Cyber Law , Legal Framework for Electronic Data
Interchange Law Relating to Electronic Banking , The Need for an Indian Cyber
Law

8

05 Indian IT Act.
Cyber Crime and Criminal Justice : Penalties, Adjudication and Appeals Under the IT
Act, 2000, IT Act. 2008 and its Amendments
6
06 Information Security Standard compliances
SOX, GLBA, HIPAA, ISO, FISMA, NERC, PCI. 6

Page 78

University of Mumbai, B. E. (Information Technology), Rev 2016 223 Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question
papers of end semester examination.
In question paper weightage of each module will be proportional to number of respective lecture hours as
mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.


REFERENCES:

1. Nina Godbole, Sunit Belapure, Cyber Security , Wiley India, NewDelhi
2. The Indian Cyber Law by Suresh T. Vishwanathan; Bharat Law House NewDelhi
3. The Information technology Act, 2000; Bare Act - Professional Book Publishers, New Delhi.
4. Cyber Law & Cyber Crimes By Advocate Prashant Mali; Snow White Publications, Mumbai
5. Nina Godbole, Information Systems Security, Wiley India, NewDelhi
6. Kennetch J. Knapp, Cyber Security &Global Information Assurance Information Science Publishing.
7. William Stallings , Cryptography and Network Security, PearsonPublication
8. Websites for more information is availableon: The Information Technology ACT, 2008 -
TIFR : https://www.tifrh.res.in
9. Website for more information , A Compliance Primer for IT professional
:https://www.sans.org/reading -room/whitepapers/compliance/compliance -primer -
professionals - 33538

Page 79

University of Mumbai, B. E. (Information Technology), Rev 2016 224 Course Code Course Name Credits
ILO7017 Disaster Management and Mitigation Measures 03

Objectives:
1. To understand physics and various types of disaster occurring around theworld
2. To identify extent and damaging capacity of adisaster
3. To study and understand the means of losses and methods to overcome /minimizeit.
4. To understand role of individual and various organization during and afterdisaster
5. To understand application of GIS in the field of disastermanagement
6. To understand the emergency government response structures before, during andafter disaster
Outcomes: Learner will be able to…
1. Get to know natural as well as manmade disaster and their extent and possible effects on the
economy.
2. Plan of national importance structures based upon the previoushistory.
3. Get acquainted with government policies, acts an d various organizational structure
associated with anemergency.
4. Get to know the simple do‘s and don‘ts in such extreme events and actaccordingly.


Module
Detailed Contents
Hrs


01 Introduction
1.1 Definition of Disaster, hazard, global and Indian scenario, general perspective,
importance of study in human life, Direct and indirect effects of disasters, long term
effects of disasters. Introduction to global warming and
climate change.

03



02 Natural Disaster and Manmade disasters:
Natural Disaster: Meaning and nature of natural disaster, Flood, Flash flood, drought,
cloud burst, Earthquake, Landslides, Avalanches, Volcanic eruptions, Mudflow,
Cyclone, Storm, Storm Surge, climate change, global warming, sea level rise,
ozonedepletion
Manmade Disasters: Chemical, Industrial, Nuclear and Fire Hazards. Role of
growing population and subsequent industrialization, urbanization and changing
lifestyle of human beings in frequent occurrences ofmanmade
disasters.


09



03 Disaster Management, Policy and Administration
Disaster management: meaning, concept, importance, objective of disaster
management policy, disaster risks in India, Paradigm shift in disaster management.
Policy andadministration:
Importance and principles of disast er management policies, command and co -
ordination of in disaster management, rescue operations -how to startwith
and how to proceed in due course of time, study of flowchart showing the entire
process.


06


04 Institutional Framework for Disaster Management in India:
4.1 Importance of public awareness, Preparation and execution of emergency
management programme.Scope and responsibilities of National Institute of Disaster
Management (NIDM) and National disaster management authority
(NDMA) in India .Methods and measures to avoid disasters, Managementof

06

Page 80

University of Mumbai, B. E. (Information Technology), Rev 2016 225 casualties, set up of emergency facilities, importance of effective
communication amongst different agencies in suchsituations.
4.2 Use of Internet and softwares for effective disaster management.
Applications of GIS, Remote sensing and GPS in thisregard.


05 Financing Relief Measures:
Ways to raise finance for relief expenditure, role of government agencies and NGO‘s in
this process, Legal aspects related to finance raising as well as overall management of
disasters. Various NGO‘s and the works they have carried out in the past on the
occurrence of various disasters, Ways to approach theseteams.
International relief aid agencies and their role in extremeevents.

09




06 Preventive and Mitigation Measures:
Pre-disaster, during disaster and post -disaster measures in some events in general
Structural mapping: Risk mapping, assessment and analysis, sea walls and embankments,
Bio shield, shelters, early warning andcommunication
Non Structural Mitigation: Community based disaster preparedness, risk transfer and
risk financing, capacity develop ment and training, awareness and education,
contingencyplans.
Do‘s and don‘ts in case of disasters and effective implementation ofrelief
aids.



06

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

REFERENCES:

1. ‗Disaster Management‘ by Harsh K.Gupta, Universities PressPublications.
2. ‗Disaster Management: An Appraisal of Institutional Mechanisms in India‘ by O.S.Dagur, published by
Centre for land warfare studies, New Delhi,2011.
3. ‗Introduction to International Disaster Management‘ by Damon Copolla, Butterworth Heinemann
Elseveir Publications.
4. ‗Disaster Management Handbook‘ by Jack Pinkowski, CRC Press Taylor and Francisgroup.
5. ‗Disaster management & rehabilitation‘ by Rajdeep Dasgupta, Mittal Publications, NewDelhi.
6. ‗Natural Hazards and Disaster Management, Vulnerability and Mitigation – R B Singh, Rawat
Publications
7. Concepts and Techniques of GIS –C.P.Lo Albert, K.W. Yonng – Prentice Hall (India) Publications.
(Lear ners are expected to refer reports published at national and International level and updated
information available on authentic websites)

Page 81

University of Mumbai, B. E. (Information Technology), Rev 2016 226 Course Code Course Name Credits
ILO7018 Energy Audit and Management 03


Objectives:

1. To understand the importance energy security for sustainable development and the
fundamentals of energyconservation.
2. To introduce performance evaluation criteria of various electrical and thermal installations to
facilitate the energymanagement
3. To relate the data collected during performance evaluation of systems for identification of energy
savingopportunities.

Outcomes: Learner will be able to…

1. To identify and describe present state of energy security and itsimportance.
2. To identify and describe the basic principles and methodologies adopted in energy audit of an utility.
3. To describe the energy performance evaluation ofsome common electrical installations and identify
the energy savingopportunities.
4. To describe the energy performance evaluation ofsome common thermal installations and identify
the energy savingopportunities
5. To analyze the data collected during performance evaluation and recommend energy saving
measures


Module
Detailed Contents
Hrs


01 Energy Scenario:
Present Energy Scenario, Energy Pricing, Energy Sector Reforms, Energy Security,
Energy Conservation and its Importance, Energy Conservation Act- 2001 and its
Features. Basics of Energy and its various forms, Materialand
Energy balance

04



02 Energy Audit Principles:
Definition, Energy audit - need, Types of energy audit, Energy management (audit)
approach -understanding energy costs, Bench marking, Energy performance, Matching
energy use to requirement, Maximizing system efficiencies, Optimizing the in put energy
requirements, Fuel and energy substitution. Elements of monitoring& targeting; Energy
audit Instruments; Data and information -analysis.
Financial analysis techniques: Simple payback period, NPV, Return on investment
(ROI), Internal rate of return (IRR)


08



03 Energy Management and Energy Conservation in Electrical System: Electricity
billing, Electrical load management and maximum demand Control; Power factor
improvement, Energy efficient equipments and appliances, star ratings.
Energy efficiency measures in lighting system, Lighting control: Occupancy
sensors, daylight integration, and use of intelligent controllers.
Energy conservation opportunities in: water pumps, industrial drives, induction motors,
motor retrofitting, soft s tarters, variable speed drives.


10

Page 82

University of Mumbai, B. E. (Information Technology), Rev 2016 227


04 Energy Management and Energy Conservation in Thermal Systems:
Review of different thermal loads; Energy conservation opportunities in: Steam
distribution system, Assessment of steam distribution losses, Steam leakages, Steam
trapping, Condensate and flash steam recovery system.
General fuel economy measures in Boilers and furnaces, Waste heat recovery, use of
insulation - types and application. HVAC system: Coefficient of performance, Capacity,
factors affecting Refrigeration and Air Conditioning system performance and savings
opportunities.


10

05 Energy Performance Assessment:
On site Performance evaluation techniques, Case studies based on: Motors and variable
speed drive, pumps, HVAC system calculations; Lighting System:
Installed Load Efficacy Ratio (ILER) method, Financial Analysis.
04

06 Energy conservation in Buildings:
Energy Conservation Building Codes (ECBC): Green Building, LEED rating,
Application of Non -Conventional and Renewable Energy Sources
03


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only F our question need to besolved.


REFERENCES:

1. Handbook of Electrical Installation Practice, Geofry Stokes, BlackwellScience
2. Designing with light: Lighting Handbook, By Anil Valia, LightingSystem
3. Energy Management Handbook, By W.C. Turner, John Wiley and Sons
4. Handbook on Energy Audits and Management, edited by A. K. Tyagi, Tata Energy
Research Institute(TERI).
5. Energy Management Principles, C.B.Smith, PergamonPress
6. Energy Conservation Guidebook, Dale R. Patrick, S. Fardo, Ray E. Richardson, Fairmont Press
7. Handbook of Energy Audits, Albert Thumann, W. J. Younger, T. Niehus, CRCPress
8. www.energymanagertraining.com
9. www.bee -india.nic.in

Page 83

University of Mumbai, B. E. (Information Technology), Rev 2016 228 Course Code Course Name Credits
ILO7019 Development Engineering 03

Objectives:

1. To familiarise the characteristics of rural Society and the Scope, Nature and Constraints of
ruralDevelopment
2. To provide an exposure toimplications of 73rdCAA on Planning, Development and Governance of
RuralAreas
3. An exploration of human values, which go into making a ‗good‘ human being, a ‗good‘ professional, a
‗good‘ society and a ‗good life‘ in the context of work life and the personal life of modern
Indianprofessionals
4. To familiarise the Nature and Type of Human Values relevant to PlanningInstitutions

Outcomes: Learner will be able to…

1. Demonstrateunderstanding of knowledge for RuralDevelopment.
2. Prepare solutions for ManagementIssues.
3. Take up Initiatives and design Strate gies to complete thetask
4. Develop acumen for higher education andresearch.
5. Demonstrate the art of working in group of differentnature
6. Develop confidence to take up rural project activitiesindependently



Module Contents Hrs
1 Introduction to Rural Development Meaning, nature and scope of development; Nature of
rural society in India; Hierarchy of settlements; Social, economic and ecological
constraints for rural development
Roots of Rural Development in India Rural reconstruction and Sarvodaya progr amme
before independence; Impact of voluntary effort and Sarvodaya Movement on rural
development; Constitutional direction, directive principles; Panchayati Raj - beginning of
planning and community development; National extension services. 08
2 Post-Independence rural Development Balwant Rai Mehta Committee - three tier system
of rural local Government; Need and scope for people‘s participation and Panchayati Raj;
Ashok Mehta Committee - linkage between Panchayati Raj, participation and rural
development. 06
3 Rural Development Initiatives in Five Year Plans Five Year Plans and Rural
Development; Planning process at National, State, Regional and District levels; Planning,
development, implementing and monitoring organizations and agencies; Urban and rural
interface - integrated approach and local plans; Development initiatives and their
convergence; Special component plan and sub -plan for the weaker section; Micro -eco
zones; Data base for local planning; Need for decentralized planning; Sustainabl e rural
development 07

Page 84

University of Mumbai, B. E. (Information Technology), Rev 2016 229 4 Post 73rd Amendment Scenario 73rd Constitution Amendment Act, including -XI
schedule, devolution of powers, functions and finance; Panchayati Rajinstitutions
- organizational linkages; Recent changes in rural local planning; Gram Sabha -
revitalized Panchayati Raj; Institutionalization; resource mapping, resource mobilization
including social mobilization; Information Technology and rural planning; Need for
further amendments. 04
5 Values and Science and Technology Material development and its values; the
challenge of science and technology; Values in planning profession, research and
education
Types of Values Psychological values — integrated personality; mental health; Societal
values — the modern search for a good society; justice, democracy, rule of law, values in
the Indian constitution; Aesthetic values — perception and enjoyment of beauty; Moral
and ethical values; nature of moral judgment; Spiritual values; different concepts; secular
spirituality; Relative and absolute values; Human values — humanism and human values;
human rights; human values as freedom, creativity, love andwisdom 10
6 Ethics Ca nons of ethics; ethics of virtue; ethics of duty; ethics of responsibility;
Work ethics; Professional ethics; Ethics in planning profession, research and education 04

Assessment :

Internal Assessment for 20 marks:
Consisting Two Compulsory Class Tests
First test based onapproximately 40% of contents and second test based on remainingcontents (approximately
40% but excluding contents covered in Test I)

End Semester Examination:
Weightage of each module in end semester examination will be proportional to number of respective lecture
hours mentioned in the curriculum.
1. Question paper will comprise of total six questions , each carrying 20marks
2. Question 1 will be compulsory and should cover maximum contents of thecurriculum
3. Remaining questions will be mixed in nature (for example if Q.2 has part (a) from module 3 then part
(b) will be from any module other than module3)
4. Only Four questions need to besolved

Reference
1. ITPI, Village Planning and Rural Development, ITPI, New Delhi
2. Thooyavan, K.R. Human Settlements: A 2005 MA Publication,Chennai
3. GoI, Constitution (73rdGoI, New Delhi Amendment) Act, GoI, NewDelhi
4. Planning Commission, Five Year Plans, PlanningCommission
5. Planning Commission, Manual of Integrated District Planning, 2006, Planning Commission New Delhi
6. Planning Guide toBeginners
7. Weaver, R.C., The Urban Complex,Doubleday
8. Farmer, W.P. et al, Ethics in Planning, American Planning Association,Washington

Page 85

University of Mumbai, B. E. (Information Technology), Rev 2016 230 9. How, E., Normative Ethics in Planning, Journal of P lanning Literature, Vol.5, No.2, pp.123 -150
10. Watson, V. Conflicting Rationalities: -- Implications for Planning Theory and Ethics, Planning Theory and
Practice, Vol. 4, No.4, pp.395 –407

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University of Mumbai, B. E. (Information Technology), Rev 2016 271 Program Structure for Fourth Year Information Technology
Semester VII & VIII
UNIVERSITY OFMUMBAI
(With Effect from2022 -2023 )
Semester VIII

Course
Code
Course Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
ITC801 Blockchain and DLT 3 -- 3 -- 3
ITDO801
X Department Optional Course – 5 3 -- 3 -- 3
ITDO802
X Department Optional Course – 6 3 -- 3 -- 3
ITIO801X Institute Optional Course – 2
3 -- 3 -- 3
ITL801 Block chain Lab -- 2 -- 1 1
ITL802 Cloud computing -- 2 -- 1 1
ITP801 Major Project II -- 12# -- 6 6
Total 12 16 12 8 20



Course
Code



Course Name Examination Scheme
Theory Term
Work Prac
/oral Total

Internal Assessment End
Sem
Exam Exam.
Duratio
n
(in Hrs)
Test1 Test2 Avg
ITC801 Blockchain and DLT 20 20 20 80 3 -- -- 100
ITDO801
X Department Optional Course – 5 20 20 20 80 3 -- -- 100
ITDO802
X Department Optional Course – 6 20 20 20 80 3 -- -- 100
ITIO801X Institute Optional Course – 2
20 20 20 80 3 -- -- 100
ITL801 Blockchain Lab -- -- -- -- -- 25 25 50
ITL802 Cloud computing -- -- -- -- -- 25 25 50
ITP801 Major Project II -- -- -- -- -- 100 50 150
Total -- -- 80 320 -- 150 100 650
# indicates work load of Learner (Not Faculty), for Major Project

Students group and load of faculty per week.
Mini Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four)

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University of Mumbai, B. E. (Information Technology), Rev 2016 272 Faculty Load : 1 hour per week per four groups

Major Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four)
Faculty Load : In Semester VII – ½ hour per week per project group
In Semester VIII – 1 hour per week per project group



ITDO801X Department Optional Course – 5
ITDO8 011 Big Data Analytics
ITDO8 012 Reinforcement learning
ITDO8 013 Simulation and Modeling
ITDO8 014 Knowledge management


ITDO802X Department Optional Course –6
ITDO8 021 User Interface Design
ITDO8 022 Robotics
ITDO8 023 ERP
ITDO8 024 Cloud computing and Services


ILO801X Institute Optional Course – 2 ( Common for all branches will be notified )
ILO801 1 Project Management
ILO801 2 Finance Management
ILO801 3 Entrepreneurship Development
and Management
ILO801 4 Human Resource Management
ILO801 5 Professional Ethics and CSR
ILO801 6 Research Methodology
ILO801 7 IPR and Patenting
ILO801 8 Digital Business Management
ILO801 9 Environmental Management

Page 88

University of Mumbai, B. E. (Information Technology), Rev 2016 273 Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITC801 Blockchain
and DLT 03 -- -- 03 -- -- 03

Course Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End
Sem.
Exam Test1 Test 2 Avg.
of 2
Tests
ITC801 Blockchain
and DLT 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No Course Objectives
1 To get acquainted with the concept of Distributed ledger system and Blockchain.
2 To learn the concepts of consensus and mining in Blockchain through the Bitcoin network.
3 To understand Ethereum and develop -deploy smart contracts using different tools and frameworks.
4 To understand permissioned Blockchain and explore Hyperledger Fabric.
5 To understand different types of crypto assets.
6 To apply Blockchain for different domains IOT, AI and Cyber Security.

Course Outcomes:
Sr.
No Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Describe the basic concept of Blockchain and Distributed Ledger Technology. L1,L2
2 Interpret the knowledge of the Bitcoin network, nodes, keys, wallets and transactions L1,L2,L3
3 Implement smart contracts in Ethereum using different development frameworks. L1,L2,L3
4 Develop applications in permissioned Hyperledger Fabric network. L1,L2,L3
5 Interpret different Crypto assets and Crypto currencies L1,L2,L3
6 Analyze the use of Blockchain with AI, IoT and Cyber Security using case studies. L1,L2,L3,L4

Prerequisite: Cryptography and Distributed Systems .

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Cryptography and
Distributed Systems
(prerequisite) Hash functions, Public – Private keys, SHA, ECC, Digital
signatures, Fundamental concepts of Distributed systems 02 —-

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University of Mumbai, B. E. (Information Technology), Rev 2016 274 I Introduction to DLT
and Blockchain Introduction to Blockchain: Technical definition of
Blockchain . Elements of a blockchain Features of
Blockchain Type of Blockchain, What is DLT . DLT V/S
BlockchainCAP theorem Byzantine Generals Problem
Consensus Mechani sm and its TypeCryptographic
primitives and data structure used in blockchain
Block in a Blockchain : Structure of a Block, Block
Header Hash and Block Height, The Genesis Block,
Linking Blocks in the Blockchain, Merkle Tree.
Self-learning Topics: Blockchain Demo 04 CO1
II Bitcoin What is Bitcoin and the history of Bitcoin, Bitcoin
Transactions, Bitcoin Concepts: keys, addresses and
wallets, Bitcoin Transactions, UTXO. validation of
transactions, Bitcoin Keys , Addresses, ECC , Base58 ,
BIP-38 , P ay-to Script and Multisig Addresses, Vanity
Addresses , Concept of Wallet, Wallet Technologies in
Bitcoin HD wallet from Seed . Transaction Scripts and
Scripts address,Bitcoin Mining and Difficulty levels
Structure of Blocks and Blockheader and Genesis Bloc k ,
linking of Block .
Bitcoin Network : Bitcoin Core node and API, Peer -to-
Peer Network Architecture, Node Types and Roles,
Incentive based Engineering, The Extended Bitcoin
Network, Bitcoin Relay Networks, Network Discovery,
Full Nodes, Exchanging ―Invento ry‖, Simplified Payment
Verification (SPV) Nodes, SPV Nodes and Privacy,
Transaction Pools, Blockchain Forks Bitcoin
TestnetBasics of Bitcoin Forensics: Analysis of Address
and Wallet , Clustering of Addresses following Money
Self-learning Topics: Study and compare different
consensus algorithms like PoA, PoS, pBFT 08 CO2
III Permissionless
Blockchain:
Ethereum Introduction to Ethereum, Ethereum 1.0 and 2.0 , Turing
completeness EVM and compare with bitcoinBasics of
Ether Units, Ethereum Wallets Working with Metamask
EOA and Contracts Transaction:: Structure of
Transaction, Transaction Nonce, Transaction GAS,
Recipient, Values and Data, Transmitting Values to EOA
and Contracts
Smart Contracts and Solidity
Development environment and client , Basic of Solidity
and Web 3 Life cycle of Smart contract, Smart Contract
programming using solidity, Metamask (Ethereum
Wallet), Setting up development environment, Use cases 10 CO3

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University of Mumbai, B. E. (Information Technology), Rev 2016 275 of Smart Contract, Smart Contracts: Opportunities and
Risk.
Smart Contract Deployment : Intr oduction to Truffle,
Use of Remix and test networks for deployment
Self-learning Topics: Smart contract development using
Java or Python
IV Permissioned
Blockchain:
Hyperledger Fabric Introduction to Framework, Tools and Architecture of
Hyperledger Fabric Blockchain.
Components : Certificate Authority, Nodes, Chain codes,
Channels, Consensus: Solo, Kafka, RAFTDesigning
Hyperledger BlockchainOther Challenges :
Interoperability and Scalabi lity of blockchain
Self-learning Topics: Fundam entals of Hyperledger
Composer 07 CO4
V Crypto assets and
Cryptocurrencies ERC20 and ERC721 Tokens, comparison between
ERC20 & ERC721, NFT, ICO, STO, Different Crypto
currencies
Self-learning Topics: Defi, Metaverse, Types of
cryptocurrencies 04 CO5
VI Blockchain
Applications & case
studies Blockchain in IoT, AI, Cyber Security
Self-learning Topics: Applications of Blockchain in
various domains Education, Energy, Healthcare, real -
estate, logistics, supply chain 04 CO6

Text Books:

1. ―Mastering Bitcoin, PROGRAMMING THE OPEN BLOCKCHAIN‖, 2nd Edition by Andreas M. Antonopoulos, June
2017, Publisher(s): O'Reilly Media, Inc. ISBN: 9781491954386.
2. Mastering Ethereum, Building Smart Contract and Dapps, Andreas M. Antonopoulos Dr. Gavin Wood, O'reilly.
3. Blockchain Technology, Chandramouli Subramanian, Asha A George, Abhillash K. A and Meena Karthikeyen,
Universities press.
4. Hyperledger Fabric In -Depth: Learn, Build and Deploy Blockchain Applications Using Hyperledger Fabric, Ashwani
Kumar, BPB publications
5. Solidity Programming Essentials: A beginner's Guide to Build Smart Contracts for Ethereum and Blockchain, Ritesh
Modi, Packt publication
6. Cryptoassets: The Innovative Investor‘s Guide to Bitcoin and Beyond, Chris Burniske & Jack Tatar.

Reference Books :

1. Mastering Blockchain, Imran Bashir, Packt Publishing 2. Mastering Bitcoin Unlocking Digital Cryptocurrencies,
Andreas M. Antonopoulos, O'Reilly Media
2. Blockchain Technology: Concepts and Applications, Kumar Saurabh and Ashutosh Saxena, Wiley.
3. The Basics of Bitcoins and Blockchains: An Introduction to Cryptocurrencies and the Technology that Powers Them,
Antony Lewis. for Ethereum and Blockchain, Ritesh Mod i, Packt publication.

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University of Mumbai, B. E. (Information Technology), Rev 2016 276 4. Mastering Bitcoin Unlocking Digital Cryptocurrencies, Andreas M. Antonopoulos, O'Reilly Media

Online References:

1. NPTEL courses:
a. Blockchain and its Applications,
b. Blockchain Architecture Design and Use Cases
2. www.swayam.gov.in/
3. www.coursera.org
4. https://ethereum.org/en/
5. https://www.trufflesuite.com/tutorials
6. https://hyperledger -fabric.readthedocs.io/en/release -2.2/whatis.h
7. Blockchain demo: ht tps://andersbrownworth.com/blockchain/
8. Blockchain Demo: Public / Private Keys & Signing: https://andersbrownworth.com/blockchain/public -private -keys/
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered .

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University of Mumbai, B. E. (Information Technology), Rev 2016 277 Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ITL801 Blockchain Lab -- 2 -- -- 1 -- 01

Course Code Course Name Examination Scheme
Theory Marks
Term
Work Practical/
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
ITL801 Blockchain Lab
-- -- -- -- 25 25 50

Lab Objectives:

Sr.No Lab Objectives
1 To develop and deploy smart contracts on local Blockchain.
2 To deploy the smart contract on test networks.
3 To deploy and publish smart contracts on Ethereum test network.
4 To design and develop crypto currency.
5 To deploy chain code on permissioned Blockchain.
6 To design and develop a Full -fledged DApp using Ethereum/Hyperledger.

Lab Outcomes:

Sr.No Lab Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
1 Develop and test smart contract on local Blockchain. L3,L4
2 Develop and test smart contract on Ethereum test networks. L3,L4
3 Write and deploy smart contract using Remix IDE and Metamask. L4
4 Design and develop Cryptocurrency. L4
5 Write and deploy chain code in Hyperledger Fabric. L4
6 Develop and test a Full -fledged DApp using Ethereum/Hyperledger. L5

Prerequisite: Programming Langauges .

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours LO
Mapping
0 Prerequisite Java, Python, JavaScript 02 —
I Local Blockchain Introduction to Truffle, establishing local Blockchain
using Truffle
Mini Project: Allocation of the groups 02 LO1
II Smart contracts and Solidity programming language, chain code
(Java/JavaScript/Go), deployment on Truffle local 04 LO2

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University of Mumbai, B. E. (Information Technology), Rev 2016 278 Chain code Blockchain
Mini Project: Topic selection
III Deployment and
publishing smart
contracts on
Ethereum test
network Ethereum Test networks
(Ropsten/Gorelli/Rin keby), deployment on test
networks, Web3.js/Web3.py for interaction with
Ethereum smart contract
Mini Project: Topic validation and finalizing software
requirements 04 LO3
IV Remix IDE and
Metamask Smart contract development and deployment using
Metamask and Remix
Design and develop Crypto currency
Mini Project: Study the required programming
language for smart contract 04 LO4
V Chain code
deployment in
Hyperledger Fabric Chain code deployment in Hyperledger fabric
Mini project: Study required front end tools 04 LO5
VI Mini -project on
Design and
Development of a
DApps using
Ethereum/Hyperledg
er Fabric Implementation of Mini Project
1. Design, configure and testing of mini project
2. Report submission as per guidelines 06 LO6

Mini project :

1. Students should carry out mini -project in a group of three/four students with a subject In -charge
2. The group should meet with the concerned faculty during laboratory hours and the progress of work discussed must be
documented.
3. Each group should perform a detailed literature survey and formulate a problem statement.
4. Each group will identify the hardware and software requirement for their defined mini project problem statement.
5. Design, develop and test their smart con tract/chain code.
6. Each group may present their work in various project competitions and paper presentations

Documentation of the Mini Project

The Mini Project Report can be made on following lines:
1. Abstract
2. Contents
3. List of figures and tables
4. Chapter -1 (Introduction, Literature survey, Problem definition, Objectives, Proposed Solution, Technology/platform
used)
5. Chapter -2 (System design/Block diagram, Flow chart, Software requirements, cost estimation)
6. Chapter -3 (Implementation snapshots/figures with expl anation, code, future directions)
7. Chapter -4 (Conclusion)
8. References
Text Books:

1. Ethereum Smart Contract Development, Mayukh Mukhopadhyay, Packt publication.
2. Solidity Programming Essentials: A Beginner's Guide to Build Smart Contracts for Ethereum and Bloc kchain, Ritesh
Modi, Packt publication.

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University of Mumbai, B. E. (Information Technology), Rev 2016 279 3. Hands -on Smart Contract Development with Hyperledger Fabric V2, Matt Zand, Xun Wu and Mark Anthony Morris,
O‘Reilly.

References Books :

1. Mastering Blockchain, Imran Bashir, Packt Publishing
2. Introducing Ethereum and Solidity, Chris Dannen, APress.
3. Hands -on Blockchain with Hyperledger, Nitin Gaur, Packt Publishing.


Online References:

1. https://trufflesuite.com/
2. https://metamask.io/
3. https://remix.ethereum.org/
4. https://www.hyperledger.org/use/fabric
Term -Work: Term -Work shall consist of 5 experiments and Mini -Project on above guidelines/syllabus. Also, Term -work must
include at least 2 assignments and Mini -Project report.
Term Work Marks : 25 Marks (Total marks) =15 Marks (5 Experiments + Mini Project) + 5 Marks (Assignments) + 5 Marks
(Attendance)
Oral Exam: An Oral exam will be held based on the Mini Project and Presentation.

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University of Mumbai, B. E. (Information Technology), Rev 2016 280

Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ITL802 Cloud Computing -- 2 -- -- 1 -- 01

Course Code Course Name Examination Scheme
Theory Marks
Term
Work Practical/
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
ITL802 Cloud
Computing -- -- -- -- 25 25 50

Lab Objectives:

Sr.No Lab Objectives
1 Tomakestudents familiarwith keyconceptsof virtualization .
2 Tomakestudentsfamiliarwithvariousdeploymentmodelsofcloudsuchasprivate,public,hybridandcommunity .
3 To understand the usingandadoptingappropriatetypeofcloudfor theirapplication .
4 TomakestudentsfamiliarwithvariousservicemodelssuchasIaaS,SaaS,PaaS,Securityas
aService(SECaaS)andDatabaseasaService .
5 Apply the different service models for the application.
6 Tomakestudents familiar with securityand privacyissues in cloudcomputingandhow to
addressthem .

Lab Outcomes:

Sr.N
o Lab Outcomes Cognitive
levels of
attainment
as per
Bloom’s
Taxonomy
1 Implementdifferenttypesofvirtualizationtechniques . L1,LL 3,L4
2 Analyzevariouscloudcomputingservicemodelsandimplementthemtosolvethegivenproblems . L1,L2,L 3,L
4
3 Design anddeveloprealworldwebapplicationsanddeploythemoncommercialcloud(s). L6
4 Explainmajorsecurityissues in thecloud and mechanisms toaddress them . L1,L2,L3
5 Explorevarious commerciallyavailablecloudservicesandrecommendtheappropriateoneforthegivenapplicati
on. L1,L2,L3
6 Implementtheconceptofcontainerization . L1,L2,L3


Prerequisite: Programming Langauges , DBMS.

DETAILED SYLLABUS:

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University of Mumbai, B. E. (Information Technology), Rev 2016 281 Sr.
No. Module Detailed Content Hours LO
Mapping
0 Prerequisite DBMS, Programming Language. 02 —
I Overview &
Virtualization. Introductionandoverviewofcloudcomputing .
HostedVirtualizationusingKVM .

Lab1:
TostudyandimplementHostedVirtualizationusingVirtua
l Box &KVM.

Lab2: To study and Implement Bare -metal
Virtualization usingXen,HyperVor VMwareEsxi . 04 LO1
II Infrastructure
Services. To study the infrastructure services using different
cloud platform

Lab3: To study and Implement Infrastructure as a
Service using AWS/MicrosoftAzure/Google cloud
platform 04 LO2
III Platform Services To study the different platform services.


Lab4: To study and Implement Platform as a Service
usingAWSElasticBeanstalk/Microsoft AzureApp
Service . 03 LO3
IV Cloud Services IaaS,PaaS, STaaS,DbaaS,IAMandSecurity as a Service
on AWS andAzure .

Lab5: Tostudyand Implement
SecurityasaServiceonAWS/Azure .

Lab6:
TostudyandimplementIdentityandAccessManage
ment(IAM)practices onAWS/Azurecloud. 04 LO4
V Storage Services To study the storage services using Docker.

Lab7: To study and Implement Storage as a
Service using OwnCloud/AWSS3, Glaciers/
AzureStorage.
Lab8: Tostudyand Implement
DatabaseasaServiceonSQL/NOSQLdatabaseslike
AWSRDS,AZURESQL/MongoDBLab/Firebase.
Lab9: To study and Implement Containerization
using Dockeron AWS/Azure/Google cloud
platform . 04 LO5
VI Kubermetes Introduction and overview of Kubernetes .

Lab10: To study and implement container
orchestration usingKubernetes on
AWS/Azure/Google cloud platform
05 LO6

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University of Mumbai, B. E. (Information Technology), Rev 2016 282















Online References:

1. https://phoenixnap.com/kb/ubuntu -install -kvm\
2. NIST Cloud Computing Security Reference Architecture
3. https://docs.citrix.com/en -us/xenserver/7 -1/install.html
4. https://docs.aws.amazon.com
5. https://docs.microsoft.com/en -us/azure
6. https://docs.docker.com/get -started/
7. https://kubernetes.io/ docs/home/

Term -Work: Term -Work shall consist of 10 experiments on above guidelines/syllabus. Also, Term -work must include at least 2
assignments .
Term Work Marks : 25 M arks (Total marks) =15 Marks ( Experiments) + 5 Marks (Assignments) + 5 Marks (Attendanc e)
Oral Exam: An Oral exam will be held based on the syllabus .









Textbooks:
1 BernardGolden,―AmazonWeb ServicesforDummies‖,JohnWiley&Sons,Inc.
2 MichaelCollier,RobinShahan,―Fundamentalsof Azure,MicrosoftAzureEssentials‖,
MicrosoftPress.
3 RajkumarBuyya,ChristianVecchiola,SThamaraiSelvi,―Mastering CloudComputing‖,
TataMcGraw -HillEducation.
4 BarrieSosinsky, ―CloudComputingBible‖,Wileypublishing.
5 JohnPaulMueller,―AWSforAdminsfor Developers‖,JohnWiley&Sons,Inc.
6 KenCochrane,JeevaS.Chelladhurai,NeependraKhare, ―DockerCookbook -Second
Edition‖, Packtpublication
7 JonathanBaier,―GettingStartedwithKubernetes -SecondEdition‖,PacktPublication.

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University of Mumbai, B. E. (Information Technology), Rev 2016 283



Course Code
Course
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Practical Tutorial Theory Practical Tutorial Total
ITM701 Major Project
– II -- 12 -- -- 06 -- 06


Course
Code
Course Name Examination Scheme
Theory Marks
Term Work Pract. /Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg.
ITM7
01 Major Project
– II -- -- -- -- 100 50 150

Course Objectives
1. To acquaint with the process of identifying the needs and converting it into the problem.
2. To familiarize the process of solving the problem in a group.
3. To acquaint with the process of applying basic engineering fundamentalsto attempt solutions to the problems.
4. To inculcate the process of self -learning and research.
Course Outcome: Learner will be able to…
1. Identify problems based on societal /research needs.
2. Apply Knowledge and skill to solve societal problems in a group.
3. Develop interpersonal skills to work as member of a gr oup or leader.
4. Draw the proper inferences from available results through theoretical/ experimental/simulations.
5. Analyse the impact of solutions in societal and environmental context for sustainable development.
6. Use standard norms of engineering practices
7. Excel in written and oral communication.
8. Demonstrate capabilities of self -learning in a group, which leads to life long learning.
9. Demonstrate project management principles during project work.

Guidelines for Major Project
 Students shall form a group of 3 to 4 students, while forming a group shall not be allowed less than three or
more than four students, as it is a group activity.
 Students should do survey and identify needs, which shall be converted into problem statement for mini project
in consultati on with faculty supervisor/head of department/internal committee of faculties.
 Students shall submit implementation plan in the form of Gantt/PERT/CPM chart, which wi ll cover weekly
activity of major project -I and major project -II.
 A log book to be prepared by each group, wherein group can record weekly work progress, guide/supervisor
can verify and record notes/comments.

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University of Mumbai, B. E. (Information Technology), Rev 2016 284  Faculty supervisor may give inputs to students d uring major project -I & II activity; however, focus shall be on
self-learning.
 Students in a group shall understand problem effectively, propose multiple solution and select best possible
solution in consultation with guide/ supervisor.
 Students shall convert the best solution into working model using various components of their domain areas
and demonstrate.
 The solution to be validated with proper justification and report to be compiled in standard format of
University of Mumbai.
 With the focus on the self -learning, innovation, addressing societal problems and entrepreneurship quality
development with in the students through the Major Project , it is preferable that a single project of appropriate
level and quality to be carried out in two semesters by all the grou ps of the students. i.e. Maj or Project -I in
semester VIIand Major Project -II in semesters V III.
 However, based on the individual students or group capability, with the mentor‘s recommendations, if the
proposed M ajor Project adhering to the qualitative aspects mentioned above gets co mpleted in odd semester,
then that group can be allowed to Scopus paper publications in Journal/Conference or Copyright or Patent as
an extension of the M ajor Project -1 with suitable improvements/modifications after testing and analysis in even
semester. T his policy can be adopted on case by case basis.
Guidelines for Assessment of Major Project:
Term Work
1. The review/ progress monitoring committee shall be constituted by head of departments of ea ch
institute. The progress of major project to be evaluated on continuous basis, minimum two reviews in
each semester VII and VIII .
2. In continuous assessment focus shall also be on each individual student, assessment based on individual‘s
contribution in group activity, their understanding and response to questions.
3. Distribution of Term work marks for both semesters shall be as below;
a. Marks awarded by guide/supervisor based on log book : 10
b. Marks awarded by review committee : 10
c. Quality of Project report : 05

Review/progress monitoring committee may consider follo wing points for assessment based on either one year
major project as mentioned in general guidelines.
One-year project:
 In semester VII entire theoretical solution shall be ready, including components/system selection and cost
analysis , building of working prototype. Two reviews will be conducted based on presentation given by
students group.
 First shall be for finalization of problem and proposed solution of the problem
 Second shall be on readiness of working and testing of prototypeto be conducted.
 In semester VIII expected work shall be procurement of testing and validation of results based on work
completed in an odd semester.
 First review is based on improvements in testing and validation results cum demonstration for
publication to be conducted.
 Second review shall be based on paper presentation in conference/journal or motivate for
copyright or Indian patent in last month of the said semester.

Assessment criteria of Major Project.

Major Project shall be assessed based on following criteria;

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University of Mumbai, B. E. (Information Technology), Rev 2016 285 14. Quality of survey/ need identification
15. Clarity of Problem definition based on need.
16. Innovativeness in solutions
17. Feasibility of proposed problem solutions and selection of best solution
18. Cost effectiveness
19. Societal impact
20. Innovativeness
21. Cost effectiveness and Societal impact
22. Full functioning of working model as per stated requirements
23. Effective use of skill sets
24. Effective use of standard engineering norms
25. Contribution of an individual‘s as member or leader
26. Clarity in written and oral communica tion

 In one year, project , first semester evaluation may be based on first six criteria‘s and remaining may
be used for second semester evaluation of performance of students in mini project.
Guidelines for Assessment of Major Project Practical/Oral Examin ation:
 Report should be prepared as per the guidelines issued by the University of Mumbai.
 Major Project shall be assessed through a presentation and demonstration of working model by the student
project group to a panel of Internal and External Examiners preferably from industry or research organizations
having experience of more than five years approved by head of Institution.
 Students shall be motivated to publish a paper based on the work in Scopus Conferences/ Journals or copy right
or Indian Patent .

Major Project shall be assessed based on following points;
1. Quality of problem and Clarity
2. Innovativeness in solutions
3. Cost effectiveness and Societal impact
4. Full functioning of working model as per stated requirements
5. Effective use of skill sets
6. Effective use of standard engineering norms
7. Contribution of an individual‘s as member or leader
8. Clarity in written and oral communication
9. Publications in Sem VIII.

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University of Mumbai, B. E. (Information Technology), Rev 2016 286


Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITDO8011 Big Data
Analytics 03 -- -- 03 -- -- 03

Course Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO8011 Big Data
Analytics 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No Course Objectives
1 To provide an overview of an exciting growing field of Big Data analytics.
2 To discuss the challenges traditional data mining algorithms face when analyzing Big Data .
3 To introduce the tools required to manage and analyze big data like Hadoop, NoSql MapReduce .
4 To teach the fundamental techniques and principles in achieving big data analytics with scalability and streaming
capability .
5 To introduce to the students several types o f big data like social media, web graphs and data streams .
6 To enable students to have skills that will help them to solve complex real -world problems in decision support .

Course Outcomes:
Sr.
No Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Explain the motivation for big data systems and identify the main sources of Big Data
in the real world . L1,L2,L3
2 Demonstrate an ability to use frameworks like Hadoop, NOSQL to efficiently store,
retrieve and process Big Data for Analytics . L1,L2,L3
3 Implement several Data Intensive tasks using the Map Reduce Paradigm . L1,L2,L3
4 Apply several newer algorithms for Clustering Classifying and finding association s in
Big Data . L1,L2,L3
5 Design algorithms to analyze Big data like streams, Web Graphs and Social Media
data. L6
6 Design and implement successful Recommendation engines for enterprises . L6

Prerequisite: AI and DS

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO Mapping

Page 102

University of Mumbai, B. E. (Information Technology), Rev 2016 287 0 Prerequisite Data Mining, Data Science 02
I Introduction to
Big Data Introduction to Big Data, Big Data characteristics, types of
Big Data, Traditional vs. Big Data business approach, Big
Data Challenges, Examples of Big Data in Real Life, Big
Data Applications
Self-learning Topics: Identification of Big Data application s
and its solutions
03 CO1
II Introduction to
Big Data
Frameworks What is Hadoop? Core Hadoop Components; Hadoop
Ecosystem; Working with Apache Spark
What is NoSQL? NoSQL data architecture patterns: Key -
value stores, Graph stores, Column family (Bigtable) stores,
Document stores, MongoDB
Self-learning Topics: HDFS vs GFS , MongoDB vs other
NoSQL system, Implementation of Apache Spark
06 CO2
III MapReduce
Paradigm MapReduce: The Map Tasks, Grouping by Key, The Reduce
Tasks, Combiners, Details of MapReduce Execution, Coping
With Node Failures. Algorithms Using MapReduce: Matrix -
Vector Multiplication by MapReduce , Relational -Algebra
Operations, Computing Selections by MapReduce,
Computing Projections by MapReduce, Union, Intersection,
and Difference by MapReduce, Computing Natural Join by
MapReduce, Grouping and Aggregatio n by MapReduce,
Matrix Multiplication, Matrix Multiplication with One
MapReduce Step . Illustrating use of MapReduce with use of
real life databases and applications.
Self-learning Topics: Implementation of MapReduce
algorithms like Word count, Matrix -Vecto r and Matrix -
Matrix algorithm 07 CO3
IV Mining Big Data
Streams The Stream Data Model: A DataStream -Management System,
Examples of Stream Sources, Stream Queries, Issues in
Stream Processing. Sampling Data in a Stream : Sampling
Techniques. Filtering Streams: The Bloom Filter Counting
Distinct Elements in a Stream : The Count -Distinct Problem,
The Flajolet -Martin Algorithm, Combining Estimates, Space
Requirements . Counting Ones in a Window: The Cost of
Exact Counts, The Datar -Gionis -Indyk, Motwani Alg orithm,
Query Answering in the DGIM Algorithm.
Self-learning Topics: Streaming services like Apache
Kafka/Amazon Kinesis/Google Cloud DataFlow.
Standard spark streaming library.
Integration with IOT devices to capture real time stream data.
07 CO4
V Big Data Mining
Algorithms Frequent Pattern Mining : Handling Larger Datasets in Main
Memory Basic Algorithm of Park, Chen, and Yu. The SON
Algorithm and MapReduce. Clustering Algorithms: CURE
Algorithm. Canopy Clustering, Clustering with MapReduce
Classificat ion Algorithms: Overview SVM classifiers,
Parallel SVM, KNearest Neighbor classifications for Big
Data, One Nearest Neighbour.
Self-learning Topics: Standard libraries included with spark
like graphX, MLlib
07 CO5

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University of Mumbai, B. E. (Information Technology), Rev 2016 288 VI Big Data
Analytics
Applications Link Analysis : PageRank Definition, Structure of the web,
dead ends, Using Page rank in a search engine, Efficient
computation of Page Rank: PageRank Iteration Using
MapReduce, Topic sensitive Page Rank, link Spam, Hubs and
Authorities, HITS Algorithm.
Mining Social - Network Graphs : Social Networks as
Graphs, Types , Clustering of Social Network Graphs, Direct
Discovery of Communities, Counting triangles using Map -
Reduce.
Recommendation Engines: A Model for Recommendation
Systems, Content -Based Recommendatio ns, Collaborative
Filtering
Self-learning Topics: Sample applications like social media
feeds, multiplayer game interactions, retail industry, financial
data analysis. Use case like location data, real -time stock
trades, log monitoring etc 07 CO6

Text Books:

1. Anand Rajaraman and Jeff Ullman ―Mining of Massive Datasets‖, Cambridge University Press.
2. Alex Holmes ―Hadoop in Practice‖, Manning Press, Dreamtech Press.
3. Professional NoSQL Paperback, by Shashank Tiwari, Dreamtech Press
4. Rajkum ar Buyya, ,Rodrigo N. Calheiros and Amir Vahid Dastjerdi, ―Big Data Principles and Paradigms‖, Morgan Kaufmann

References Books :

1. Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, Bart Baesens , WILEY Big Data
Series.
2. Big Data Analytics with R and Hadoop by Vignesh Prajapati Paperback, Packt Publishing Limited
3. Hadoop: The Definitive Guide by Tom White, O'Reilly Publications

Online References:

1. https://nptel.ac.in/courses/106/104/106104189/
2. https://nptel.ac.in/courses/106106142/
3. https://nptel.ac.in/courses/106105186/

Assessment:

Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questi ons will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered .

Page 104

University of Mumbai, B. E. (Information Technology), Rev 2016 289







Course Code Course Name Theory Practical Tutorial Theory Practical/Oral Tutorial Total
ITDO8012 Reinforcement
Learning 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO8012 Reinforcement
Learning 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No Course Objectives
1 Define the key features of reinforcement learning that distinguishes it from AI and non -interactive machine
learning .
2 Introduce to statistical learning techniques where an agent explicitly takes actions and interacts with the world .
3 Implement in code common RL algorithms .
4 Describe multiple criteria for analyzing RL algorithms & evaluate algorithms on these metrics: e.g. regret, sample
complexity, computational complexity, empirical performance, convergence, etc .
5 Know how to implement dynamic programming as an efficient solution approach to an industrial control problem .
6 Explore solutions to the Exploration -Exploitation Dilemma .

Course Outcomes:
Sr.
No Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Learn how to define RL tasks and the core principles behind the RL, including
policies, value functions, deriving Bellman equations . L1,L2
2 Evaluate work with tabular methods to solve classical control problems . L1,L2,L3
3 Apply Markov Decision Processes to solve real -world problems . L1,L2,L3
4 Understand the dynamic programming for policy Evaluation . L1,L2
5 Implement reinforcement learning problems based on averaging sample returns using
Monte Carlo method . L1,L2,L3
6 Recognize current advan ced techniques and applications in RL . L1,L2,L3

DETAILED SYLLABUS:

Sr. No. Module Detailed Content Hours CO
Mapping

Page 105

University of Mumbai, B. E. (Information Technology), Rev 2016 290 0 Prerequisite Probability distributions and expected values, and basic linear
algebra (e.g., inner products). 02
I Introduction to
Reinforcement Learning:
Reinforcement Learning :
Key features and Elements of RL,
Types of RL, rewards.
Reinforcement Learning Algorithms : Q-Learning, State
Action Reward State Action (SARSA),
Self-learning Topics:
Deep Q Neural Network (DQN) , Applications of RL 04 CO1
II Bandit problems and
online learning:
An n -Armed Bandit Problem, Action -Value Methods
Tracking a Nonstationary Problem,
Optimistic Initial Values
Upper -Confidence -Bound Action Selection Gradient Bandits
Self-learning Topics:
Associative Search (Contextual Bandits) 07 CO2
III Markov Decision
Processes:
The Agent –Environment Interface,
Goals and Rewards, Returns, Markov properties, Markov
Decision Process, Value Functions and Optimal Value
Functions,
Self-learning Topics:
Optimality and Approximation 07
IV Dynamic Programming:
Policy Evaluation (Prediction), Policy Improvement, Policy
Iteration, Value Iteration, Asynchronous Dynamic
Programming, Generalized Policy Iteration
Self-learning Topics: 07 CO4
V Monte Carlo Methods and
Temporal -Difference
Learning
Monte Carlo Prediction, Monte Carlo Estimation of Action
Values, Monte Carlo Control,
TD Prediction, TD control using Q -Learning
Self-learning Topics:
Off -policy Prediction via Importance Sampling 07 CO5
VI Applications and Case
Studies Elevator Dispatching, Dynamic Channel Allocation, Job -Shop
Scheduling
Self-learning Topics: Study of applications. 05 CO6

Text Books:

1. Reinforcement Learning: An Introduction, by Richard S. Sutton and Andrew G. Barto
2. Alessandro Palmas , Dr. Alexandra Galina Petre , Emanuele Ghelfi , The Reinforcement Learning Workshop: Learn how
to Apply Cutting -edge Reinforcement Learning Algorithms to a Wide Range of Control Problems, 2020 Packt
publishing.
3. Phil Winder, Reinforcement Learning Industrial Applications with Intelligent Agents, O‘Reilly
4. Dr Engr S M Farrukh Akhtar, Practical Reinforcement Learning, Packt Publishing, 2 017.

References Books :

1. Maxim Lapan, Deep Reinforcement Learning Hands -On: Apply modern RL methods, with deep Q -networks, value
iteration, policy gradients, TRPO, AlphaGo Zero.
2. Csaba Szepesv´ari, Algorithms for Reinforcement Learning, Morgan & Claypool Publishers
3. Alberto Leon -Garcia, Probability, Statistics and Random Processes for Electrical Engineering, Third Edition, Pearson
Education, Inc.

Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests . Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test

Page 106

University of Mumbai, B. E. (Information Technology), Rev 2016 291  Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 m arks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered .

Page 107

University of Mumbai, B. E. (Information Technology), Rev 2016 292





Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ITDO8013 Theory
Course 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
ITDO8013 Simulation
and Modeling 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No Course Objectives
1 To introduce the discrete event simulation systems .
2 To discuss the modeling techniques of entities, queues, resources and entity transfers in the discrete event
environment .
3 To formulate and apply the statistical models in simulation and queuing theory .
4 To gain knowledge of random numbers, random variates and various statistical tests on random numbers .
5 To formulate and build valid models and perform simulation analysis of the system and analyze results
properly .
6 To familiarize with various applications of Simulatio n.

Course Outcom es:
Sr.
No Course Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the meaning of simulation and Identify the common applications of
discrete -event system simulation . L1,L2
2 Practice formulation and modeling skills . L1,L2,L3
3 Analyze events and inter -arrival time, arrival process, queuing strategies, resources
and disposal of entities using statistical models . L1,L2,L3,L4
4 Understand pseudo -random numbers and perform statistical tests to measure the
quality of pseudo -random numbers . L1,L2
5 Apply different distributions to fit the collected data and describe the process of
verification and validation of simulation models . L1,L2,L3
6 Describe various applications of simulation . L1,L2

Prerequisite: Probability and Statistics

DETAILED SYLLABUS:

Page 108

University of Mumbai, B. E. (Information Technology), Rev 2016 293
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Concepts of Probability: Probability mass
function, Probability density function, Mean,
Variance, Median, Mode 02 -
I Introduction to
Simulation SimulationDefinition, When Simulation is an
appropriate tool and when it is not, Advantages
and disadvantages of simulation, Areas of
application of simulation, System and its types,
Models and its types, Steps in simulation study
Self-learning Topics: Monte Carlo simulation 04 CO1
II Simulation
Examples and
General Principles Simulation Process, Simulation of Single -server
and multi -server queueing systems, Simulation
of (M, N) Inventory and Newspaper Seller
Problem, Simulation of Lead -time Demand
Concepts in Discrete Event Simulation, Event
Scheduling Algorithm, Manual Simulation of
Single Server and Dump Truck Problem using
Event Scheduling Algorithm
Self-learning Topics: Simulation of Reliability
Problem, Process Interaction Approach in
Simulation. 08 CO2
III Mathematical
,Statistical and
Queueing Models in
Simulation Statistical Models: Terminology and concepts,
Useful statistical models, Discrete Distributions
(Bernoulli‘s trial, Binomial and Negative
Binomial, Poisson Distributions), Continuous
Distributions (Exponential, Uniform, Erlang,
Triangular and Normal Distributions), Poisson
Process,
Queueing Models: Queuing Notations, Long Run
Performance Measures, M/M/1 and M/G/1
Queuei ng Systems
Self-learning Topics: 08 CO3
IV Random Numbers
and Variates Random Number Generation: Why are random
numbers required in simulation? Properties of
random numbers, Linear Congruential Method to
generate Random Numbers, Test for Uniformity:
Kolmogorov -Smirnov, Chi -Square, Test for
Independence: Runs up and runs down, Runs
above and below mean, Poker test), Random
Variate Generation: Inverse Transform
Technique, Direct Transformation for Normal
and Lognormal distribution, Acceptance
Rejection Technique
Self-learning Topics: Tests for Autocorrelation 08 CO4
V Analysis of
Simulation Data Steps in Input Modeling, Goodness -of-fit tests,
Selecting Input Model without data, Multivariate
and Time Series Models, Model Building
verification and validation, Verification of
simulation models, Naylor and Finger Approach
for calibration and Validation of simulation
models
Self-learning Topics: Input -Output Validation:
Using Historical Input Data 06 CO5

Page 109

University of Mumbai, B. E. (Information Technology), Rev 2016 294 VI Applications of
Simulation High -Level Computer -System Simulation and
Memory Simulation, Simulation of
Manufacturing and Material Handling Systems
Self-learning Topics: Simulation of Computer
Networks 03 CO6

Text Books:
1. J. Banks, J. S. Carson, B. L. Nelson and D. M. Nicol (2001), Discrete Event System Simulation, 3rd Ed., Prentice -Hall.
2. J. Banks, J. S. Carson, B. L. Nelson and D. M. Nicol (2001), Discrete Event System Simulation, 4th Ed., Prentice -Hall.

References Books :

1. A. M. Law and W. D. Kelton (2000), Simulation Modeling and Analysis, 4th Ed., McGraw Hill.
2. K. S. Trivedi (2001), Probability and Statistics with Reliability, Queuing and Computer Science Applications, Eastern
Economy Edition, Prentice -Hall (India).
3. Banks C M, Sokolowski J A, Principles of Modeling and Simulation, Wiley
4. Geoffrey Gordon, System Simulation, EEE
5. Narsing Deo, System Simulation with Digital Computer; PHI
Online References:

1. https://www.udemy.com/course/discrete -event -system -simulat ion/
2. https://www.tutorialspoint.com/modelling_and_simulation/index.htm


Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a total of six questions ea ch carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered .

Page 110

University of Mumbai, B. E. (Information Technology), Rev 2016 295



Course Code Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ITDO8014
Knowledge
Management 03 -- -- 03 -- -- 03

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO8014
Knowledge
Management 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No Course Objectives
1 Establish a foundation of key terms and concepts, historical events and contributions, organizational benefits, and
guiding principles on which to build greater understanding of knowledge management .
2 Appreciate the role and use of knowledge for individuals, as well as organizations and institutions .
3 Increase information and understanding about knowledge transfer using low - and high technology strategies .
4 Explore the future of knowledge management and its influence on our jobs, communities, and societ y.
5 Explore different tools for knowledge codification and knowledge transfer .
6 Discuss impact of knowledge management on product, people and organization, etc. with qualitative and
quantitative measures .

Course Outcomes:
Sr.
No Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Discuss KM, learning organizations, intellectual capital and related terminologies in
clear terms and understand the role of knowledge management in organizations . L1,L2,L3
2 Demonstrate an understanding of the history, concepts, and the antecedents of
management of knowledge and describe several successful knowledge management
systems . L1,L2,L3
3 Evaluate the impact of technology including telecommunications, networks, and
Internet/intranet role in managing knowledge . L4,L5
4 Discuss new jobs, roles and responsibilities resulting from the New or Knowledge
Economy Ponder KM‘s current and future impact on individuals, organizations and
society at large . L1,L2,L3
5 Apply different tools for knowledge transfer and Business Intelligence in knowledge
sharing . L1,L2,L3
6 Analyze different modes of knowledge conversion and testing tools for knowledge
codification . L1,L2,L3,L4

Prerequisite: An introductory course in IT/ IS

DETAILED SYLLABUS:

Page 111

University of Mumbai, B. E. (Information Technology), Rev 2016 296
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Meaning of data, information, knowledge and
expertise Meaning of epistemology, Types of
Knowledge -Subjective & Objective views of
knowledge, procedural Vs. declarative, tacit Vs.
explicit, general Vs. specific. 02
I Introduction to
Knowledge
Management What is Knowledge? Data, information and
knowledge, Knowledge management process, Types of
expertise – associational, motor skill, theoretical
Characteristics of knowledge – explicitness,
codifiability, teachability, specificity, Reservoirs of
knowledge, Meaning of Knowledge Management,
Forces Drivi ng Organizational issues in KM, KM
Systems & their role, Relevance of KM in today‘s
dynamic & complex environment, Future of
Knowledge Management
Self-Learning Topics: Study the various KM process. 07 CO1
II Knowledge
management
system life
cycle Challenges in Building KM Systems – Conventional
versus KM System Life Cycle (KMSLS) – Knowledge
Creation and Knowledge Architecture – Nonaka‘s
Model of Knowledge Creation and Transformation,
Knowledge Architecture.
Self-Learning Topics: Case study for KMS LS. 06 CO2
III KM Solutions
for capture,
sharing &
applications KM Processes, KM Systems, Mechanisms &
Technologies, Knowledge Capturing Techniques:
Brain Storming – Protocol Analysis – Consensus
Decision Making – Repertory Grid - Concept Mapping
–Blackboarding, Nominal Group Technique, Delphi
method.
Self-Learning Topics: Study various technologies
used in KM in industry. 06 CO5
IV Knowledge
codification Modes of Knowledge Conversion – Codification Tools
and Procedures – Knowledge Developer‘s Skill Sets –
System Testing and Deployment – Knowledge Testing
–Approaches to Logical Testing, User Acceptance
Testing – KM System Deployment Issues – User
Training – Post implementation.
Self-Learning Topics: Study different tools for testing
for KM. 06 CO6
V Knowledge
transfer and
sharing Transfer Methods – Role of the Internet – Knowledge
Transfer in e -world – KM System Tools – Neural
Network – Association Rules – Classification Trees –
Data Mining and Business Intelligence – Decision
Making Architecture – Data Management –
Knowledge Management Protocols – Managing
Knowledge Workers.
Self-Learning Topics: Case study for transfer
methods in KM. 06 CO3
VI KM Impact Dimensions of KM Impact – People, Processes,
Products & Organizational Performance Factors
influencing impact – universalistic & contingency
views Assessment of KM Impact – Qualitative &
quantitative measures, Identification of appropriate 06 CO4

Page 112

University of Mumbai, B. E. (Information Technology), Rev 2016 297 KM solutions, Competing with Business Analytics,
Caveats for managing K nowledge and Business
Intelligence, Corporate social Responsibility, Ethical
Legal and Managerial Issues: PAPA, Security and
controls.
Self-Learning Topics: Case study on KM impact.



Text Books:

1. Irma Becerra -Fernandez, Avelino Gonzalez, Rajiv Sabherwal (2004). Knowledge Management Challenges, Solutions,
and Technologies. Prentice Hall. ISBN: 0 -13-109931 -0.
2. Elias M. Awad, Hassan M. Ghaziri (2004). Knowledge Management. Prentice Hall. ISBN: 0 -13- 034820 -1
3. Donald Hislop, Knowledge Management in Organizations, Oxford 2nd Edition. Ian Watson (2002).
4. Shelda Debowski, Knowledge Management, Wiley India Edition
5. Keri E Pearlson, Carol S. Saunders, Strategic Management of Information System, Wiley India Ed ition
6.
References Books :

1. Madanmohan Rao (2004). Knowledge Management Tools and Techniques: Practitioners and Experts Evaluate KM
Solutions. Butterworth -Heinemann. ISBN: 0750678186.
2. Stuart Barnes (Ed.) (2002). Knowledge Management Systems Theory and Pr actice. Thomson Learning.
3. Kimiz Dalkir, Knowledge Management in Theory and Practice, Elsevier, Butterworth Hinemann.
4. Applying Knowledge Management: Techniques for Building Corporate Memories. Morgan Kaufmann. ISBN:
1558607609.

Online resources:

1. https://onlinecourses.nptel.ac.in/noc19_mg33/preview
2. https://www.udemy.com/course/knowledge -management/
3. https://www.coursehero.com/file/70272191/km -pdf-imppdf/
4. http://cs.unibo.it/~gaspari/www/teaching/slides_KM6.pdf


Assessment:
Internal Ass essment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question p aper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered .

Page 113

University of Mumbai, B. E. (Information Technology), Rev 2016 298


Course
Code Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ITDO802 1 User
Interface
Design 03 -- -- 03 -- -- 03

Course Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
ITDO8021 User
Interface
Design 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No Course Objectives
1 To stress the importance of good interface design .
2 To understand the importance of human psychology as well as social and emotional aspect in designing good
interfaces .
3 To learn the techniques of data gathering, establishing requirements, analysis and data interpretation .
4 To learn the techniques for prototyping and evaluating user experiences .
5 To understand interaction design process and evaluate design .
6 To bring out the creativity in each student – build innovative applications that are usable, effective and efficient
for intended users .

Course Outcomes:
Sr.
No Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify and criticize bad features of interface designs . L1,L2,L3
2 Predict good features of interface designs . L1,L2,L3
3 Illustrate and analyze user needs and formulate user design specifications . L1,L2,L3
4 Interpret and evaluate the data collected during the process . L1,L2,L3
5 Evaluate designs based on theoretical frameworks and methodological approaches . L1,L2,L3,L4,L5
6 Apply better techniques to improve the user interaction design interfaces . L1,L2,L3

Prerequisite : Software Engineering.

DETAILED SYLLABUS:

Page 114

University of Mumbai, B. E. (Information Technology), Rev 2016 299 Sr.
No. Module Detailed Content Hour
s CO
Mapping
0 Prerequisite Software Engineering concepts and any
programming Language
Self-learning Topics: Web design languages 02 NA
I Introduction to
Interaction
Design Good and Poor Design, What is Interaction
Design, The User Experience, The Process Of
Interaction Design, Interaction Design and the
User Experience, Necessity of UI/UX

Self-learning Topics: Study of Various
interactive day to day application 05 CO1
II Understanding
and
Conceptualizin
g Interaction
Cognitive
aspects and
Social,
Emotional
Interaction Understanding the Problem Space and
Conceptualizing Design, Conceptual Model,
Interface Types, Cognitive aspects, Social
Interaction and the Emerging Social Phenomena,
Emotions and the User Experience, Expressive
and Frustrating Interfaces, Persuasive
Technologies

Self-learning Topics: Study of Various
interactive Interface Types
05 CO2
III Data
Gathering,
Establishing
Requirements,
Analysis,
Interpretation
and
Presentation Establishing Requirements, Five Key Issues,
Techniques for Data Gathering, Data Analysis
Interpretation and Presentation, Task Description
and Task Analysis

Self-learning Topics: Any case study of how to
gather requirements .( eq.BE Project )
08 CO3
IV Process of
Interaction
Design,
Prototyping,
Construction. Interaction Design Process, Prototyping and
Conceptual Design, Interface Metaphors and
Analogies
Self-learning Topics: Study of two websites with
usability concepts. 07 CO4 / CO5
V Design rules
and Industry
standards Design principles, Principles to support Usability,
Standards and Guidelines, Golden rules and
Heuristics, ISO/IEC standards .The 15 Rules
Every UI/UX Designer Should Know .
Self-learning Topics:
Study experiments on industry standards and
design principles.
principles.https://xd.adobe.com/ideas/career -
tips/15 -rules -every -ux-designer -know/ 07 CO5

Page 115

University of Mumbai, B. E. (Information Technology), Rev 2016 300 VI Evaluation
Techniques and
Framework The Why, What, Where and When of Evaluation,
Types of Evaluation, case studies, DECIDE
Framework, Usability Testing, conducting
experiments, Field studies, Heuristic Evaluation
and walkthroughs, Predictive models.
Self-learning Topics: Evaluation of any GUI
with usability principles.
05 CO5/
CO6

Text Books:
1. Interaction Design, by J. Preece, Y. Rogers and H. Sharp. ISBN 0 -471-49278 -7.
2. Human Computer Interaction, by Alan Dix, Janet Finlay, Gregory D Abowd, Russell Beale
3.Alan Cooper, Robert Reimann, David Cronin, ―About Face3: Essentials of Interaction desi gn‖,
Wiley publication.
4.Wilbert O. Galitz, ―The Essential Guide to User Interface Design‖, Wiley publication.

References Books :
1. The UX Book, by Rex Hartson and Pardha S Pyla
2 .Donald A. Norman, ―The design of everyday things‖, Basic books.
3. Jeff Johnson, ―Designing with the mind in mind‖, Morgan Kaufmann Publication.
4. UI Design: Key to captivate User Understanding, by Nilakshi Jain, Dhananjay Kalbande

Online References:
1. https://onlinecourses.nptel.ac.in/noc21_ar05/preview
2. https://nptel.ac.in/courses/124/107/124107008/
3. https://nptel.ac.in/noc/courses/noc19/SEM1/noc19 -ar10/
4. https://nptel.ac.in/courses/107/103/107103083/
5. https://www.youtube.com/watch?v=6C2Ye1makdY&list=PLW -zSkCnZ -gD5TDfs1eL5EnH2mQ0f9g6B
6. https://xd.adobe.com/ideas/process/
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a t otal of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered .

Page 116

University of Mumbai, B. E. (Information Technology), Rev 2016 301


Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Tota
l
ITDO8022 Robotics 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO8022 Robotics 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No . Course Objectives
1 Learn the basic concepts of Robot .
2 Learn the concepts of Kinematics of Robotics .
3 Learn the different types of Actuators and Sensors in Robot Designing .
4 Learn the concepts of Motions, Velocities and Dynamic Analysis of Force .
5 Learn the concepts of Trajectory and Motion Planning .
6 Learn the different Programming Languages to program Robot .

Course Outcomes:
Sr.
No Course Outcomes Cognitive
levels of
attainment
as per
Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand different types of robot, its characteristics and applications . L1,L2
2 Analyse kinematics parameters of robotic manipulator . L1,L2,L3,L4
3 Identify actuators, sensors and control of a robot for different applications . L1,L2,L3
4 Apply the differential relationships of motion, velocities and dynamic analysis of
force . L1,L2, L3
5 Apply the concept of trajectory and motion planning in robot programming . L1,L2,L3
6 Use robot programming languages and acquire skills to program robots . L1,L2,L3

Prerequisite: Mathematical concepts of Geometry, Linear Algebra, Calculus, Basic Electronics

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Homogenous Coordinate System, Matrix
Representation and its Operations, Vector 02 --

Page 117

University of Mumbai, B. E. (Information Technology), Rev 2016 302 Algebra: Dot and Cross Products, Orthogonal and
Orthonormal Vectors
I Introduction and
Fundamentals of
Robotics Automation and its types, definition of Robotics
and a Robot, History of Robotics, Advantages and
Disadvantages of Robot, Robotic Manipulators,
Robot Motions, Robot Anatomy, Links and
Joints, Classification of Robo ts, Specification of
Robot, Applications of Robots
Self-learning Topics: Robot Coordinate System,
Economic and Social Aspects of Robotics 04 CO1
II Direct and Inverse
Kinematics Homogeneous transformation matrices, Inverse
transformation matrices, Forward and inverse
kinematic equations for position and orientation,
Denavit -Hartenberg Representation of Forward
Kinematic Equations of Robots, The Inverse
Kinematic Solution of Robots, Case Studies:
Three Axes Planar Articulated Robot Arm (Mini -
Drafter) and Four Axes Adept -1 SCARA robot
Self-learning Topics: Study of Five Axes Rhino
XR- Robot Arm and Six Axes Articulated
Intelledex 660 Robot Arm 08 CO2
III Actuators and
Sensors Characteristics of Actuating Systems, Comparison
of Actuating Systems, Hydraulic Devices,
Pneumatic Devices, Electric Motors,
Magnetostrictive Actuators, Sensor
Characteristics, Position Sensors, Velocity
Sensors, Acceleration Sensors, Force and
Pressure Sensors, Torque Sensors, Light and
Infrared Sensors, Touch and Tactile S ensors,
Proximity Sensors, Sniff Sensors, Vision
Systems, Voice Synthesizer
Self-learning Topics: Microprocessor Control of
Electric Motors, Microswitches, Range Finders,
Voice Recognition Devices 06 CO3
IV Motions, velocities
and dynamic
analysis of forc e Differential relationship, Jacobian, Differential
motions of a frame and robot, Inverse Jacobian,
Lagrangian mechanics, Moments of Inertia,
Dynamic equations of robots, Transformation of
forces and moment between coordinate frames
Self-learning Topics: Static Force Analysis of
Robots 08 CO4
V Trajectory and
Motion Planning Trajectory planning, Joint -space trajectory
planning, Cartesian -space trajectories, Concept of
motion planning, Bug Algorithms – Bug1, Bug2,
Tangent Bug
Self-learning Topics: Case Study based on real
life application of motion planning (eg. Chess
Game, Robotic Race, etc.) 05 CO5
VI Introduction to
Robot Programming Definition of Robot Program, Robot
Programming Techniques like Online
programming, Lead -through programming, Walk -
through programming, Offline programming,
Task programming, Motion Programming,
Robotic Programming Language: Overview,
Requirements for Stand ard Robot Language,
Introduction to Robot Languages like AL, AML, 06 CO6

Page 118

University of Mumbai, B. E. (Information Technology), Rev 2016 303 RAIL, RPL, VAL, etc.
Self-learning Topics: Example of Robot Program
using VAL.

Text Books:

1. Robert Shilling, ―Fundamentals of Robotics -Analysis and control‖, PHI, 2003.
2. Saeed B. Niku, ―Introduction to Robotics Analysis, Systems, Applications‖,3rd Edition, Wiley, 2019.
3. Saha, S.K., ―Introduction to Robotics‖, 2nd Edition, McGraw -Hill Higher Education, New Delhi, 2014.
4. Ashitava Ghoshal, ―Robotics -Fundamental Concepts and Analysis‖, O xford University Press, Sixth impression, 2010
5. Mukherjee S., ―Robotics Process Automation‖, 1st Edition, Khanna Publishing House, New Delhi, 2020.
References Books :

1. John J. Craig, ―Introduction to Robotics – Mechanics & Control‖, 3rd Edition, Pearson Edu cation, India, 2009
2. Mark W. Spong & M. Vidyasagar, ―Robot Dynamics & Control‖, 2nd Wiley India Pvt. Ltd., 2004
3. Aaron Martinez & Enrique Fernandez, ―Learning ROS for Robotics Programming‖, 1st Edition, Shroff Publishers, 2013
4. Howie Choset, Kevin M. Lynch, Seth Hutchinson, George Kantor, Wolfram Burgard, Lydia E. Kavraki and Sebastian
Thrun, ―Principles of Robot Motion –Theory, Algorithms and Implementations‖, Prentice -Hall of India, 2005
5. Fu, Gonzalez, Lee, ―Robotics: Control, Sensing, Vision and Intelligen ce‖, 1st Edition, Mc Graw Hill, India.
Online References:

1. https://swayam.gov.in/nc_details/NPTEL
2. https://www.udemy.com/course/robotics -course/
3. https://www.coursera.org/courses?query=robotics
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module r andomly
selected from all the modules)
A total of four questions need to be answered .

Page 119

University of Mumbai, B. E. (Information Technology), Rev 2016 304

Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Tota
l
ITDO802 3 ERP 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO8023 ERP 20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No . Course Objectives
1 To learn the basic concepts of ERP.
2 To learn different technologies used in ERP.
3 To learn the concepts of ERP Manufacturing Perspective and ERP Modules.
4 To learn what are the benefits of ERP .
5 To study and understand the ERP life cycle.
6 To learn the different tools used in ERP.

Course Outcomes:
Sr.
No Course Outcomes Cognitive
levels of
attainment
as per
Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the basic concepts of ERP. L1,L2
2 Identify different technologies used in ERP. L1,L2,L3
3 Understand and apply the concepts of ERP Manufacturing Perspective and ERP
Modules. L1,L2
4 Discuss the benefits of ERP . L1,L2,L3
5 Understand and implement the ERP life cycle. L1,L2
6 Apply different tools used in ERP. L1,L2,L3

Prerequisite: Basics of software .

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basics of software. 02 --

Page 120

University of Mumbai, B. E. (Information Technology), Rev 2016 305 I Introduction to
ERP Enterprise – An OverviewIntegrated Management
Information, Business Modeling,Integrated Data
Model
Self-Learning Topics: Study of advantages of
ERP. 04 CO1
II ERP Technologies Business ProcessingReengineering(BPR), Data
Warehousing, Data Mining, On -lineAnalytical
Processing(OLAP),Supply Chain Management
(SCM),Customer
RelationshipManagement(CRM), MIS -
Management Information System,DSS - Decision
Support System,EIS - Executive
InformationSystem
Self-Learning Topics: Study different ERP
technologies. 06 CO2
III ERP
Manufacturing
Perspective and
ERP Modules MRP - Material Requirement Planning, BOM -
Bill Of Material, MRP - Manufacturing Resource
Planning, DRP – Distributed Requirement
Planning, PDM - Product Data Management.
Finance, Plant Maintenance, Quality
Management, Materials Management.
Self-Learning Topics: Study d ifferent ERP
modules. 08 CO3
IV Benefits of ERP Reduction of Lead -Time, On -timeShipment,
Reduction in CycleTime, Improved Resource
Utilization, Better CustomerSatisfaction,
Improved SupplierPerformance, Increased
Flexibility,Reduced Quality, Costs, Improved
Information Accuracy and Design -making
Capability .
Self-Learning Topics: Study of benefits of ERP
for real time application. 08 CO4
V ERP Life cycle Pre-evaluation Screening, PackageEvaluation,
Project Planning Phase,Gap Analysis,
Reengineering, Configuration, Implementation
Team Training, Testing, GoingLive, End -user
Training, Post -implementation (Maintenance
mode).
Self-Learning Topics: ERP testing tools. 05 CO5
VI E-Commerce to E -
business E-Business structural transformation, Flexible
Business Design, Customer Experience, Create
the new techo enterprise, New generation e -
business leaders, memo to CEO, Empower your
customer, Integrate Sales and Service, Integrated
Enterprise
applications. Enterprise resource planning the E -
business Backbone Enterprise architecture,
planning, ERP usage in Real world, ERP
Implementation.
Self-Learning Topics: ERP Applications. 06 CO6

Text Books:

1. Enterprise Resource Planning - Alexis Leon, Tata McGraw Hill.
2. Enterprise Resource Planning – Diversified by Alexis Leon, TMH.
3. Enterprise Resource Planning - Ravi Shankar & S. Jaiswal , Galgotia.

Page 121

University of Mumbai, B. E. (Information Technology), Rev 2016 306
References Books :

1. Guide to Planning ERP Application, Annetta Clewwto and Dane Franklin, McGRaw -Hill,1997
2. The SAP R/3 Handbook, Jose Antonio, Mc Graw – Hill
3. E-Business Network Resource planning using SAP R/3 Baan and Peoplesoft : A PracticalRoadmap For Success By Dr. Ravi
Kalakota

Online References:

1. https://www.udemy.com/
2. https://www.sap.com/
3. www.oracle.com


Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be a nswered .

Page 122

University of Mumbai, B. E. (Information Technology), Rev 2016 307



Course Code Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ITDO8024 Cloud
Computing
and Services
03 -- -- 03 -- -- 03

Course Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ITDO8024 Cloud
Computing
and
Services
20 20 20 80 -- -- -- 100

Course Objectives:

Sr.No Course Objectives
1 Understand and analyze the basics of cloud computing, service models, deployment models and architecture .
2 Define and understand the concept of virtualization and related technologies .
3 Understand the different cloud computing services and their relevance‘s .
4 Describe the various services provided by Amazon Web Services cloud platform .
5 Understand and analyze the functionality of Openstack cloud platform & Severless computing .
6 Describe the aspects of Security & Privacy in cloud computing .

Course Outcomes:
Sr.
No Course Outcomes Cognitive
levels of
attainment
as per
Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Explain the basics concepts of cloud computing like service models, deployment
models and its architectur e. L1,L2,L3
2 Describe and apply virtualization in cloud computing . L1,L2,L3
3 Use and Analyze different cloud computing services . L1,L2,L3,L4
4 Understand and apply various services provided by Amazon Web Services cloud
platform . L1,L2,L3
5 Discuss the functionali ty of Openstack cloud platform & Severless computing . L1,L2,L3
6 Recognize and examine the security and privacy concerns in cloud computing . L1,L2,L3

Prerequisite : Computer Network, Operating System.

DETAILED SYLLABUS:

Page 123

University of Mumbai, B. E. (Information Technology), Rev 2016 308 Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Concepts of Computer Network, Network
Security and Operating System. 02
I Introduction to cloud
computing Introduction to cloud computing, need for cloud
computing and its components, cloud & other
similar configurations, cloud types: NIST and
Cloud Cube Model, characteristics of cloud
computing, deployment models, service models,
advantages and disadvantages of Cloud
Computing.
Self-learning Topics:
Study the recent trends in cloud computing
architectures and related technologies. 06 CO 1
II Virtualization Characteristics of virtualized environment,
structures of virtualization, implementation
levels of virtualization, mechanisms of
virtualization, pros and cons of virtualization,
virtualization vs cloud computing, Xen and
KVM architecture.
Self-learning Topics:
Comparison between different virtualization
platforms. 06 CO 2
III Cloud Computing
Services SPI Model of Cloud computing, Everything as a
Service (XaaS): Database as a Service, Storage
as a Service, Security as a Service, Collaboration
as a Service, Monitoring as a Service, Network
as a Service, Disaster Recovery as a service,
Identity management as a Service, Analytics as a
Service and Backup as a Service.
Self-learning Topics:
Study of different cloud computing platforms
providing XaaS services. 04 CO 3
IV Amazon Web
Service Cloud
Platform Introduction to the AWS Cloud, AWS core
services by categories.
Compute Service: Introduction to EC2, EC2
Instances, EC2 Amazon Machine Images,
Instance Types, Instance Lifecycle.
Storage Service: Introducing S3, working with
Buckets, setting bucket security, S3 event and
notification, bucket properties, w orking with
Elastic Block Store Volumes, Object Storage Vs
Block Storage, Archives versus backups,
Introduction to Glacier.
Virtual Private Cloud: Introduction, Subnet,
Elastic Network Interfaces, Internet Gateways,
Route Tables, Security Groups.
CloudWatc h:Introduction, CloudWatch Metrics,
CloudWatch Alarms.
Database as a Service: Introduction to Amazon
Relational Database Service (RDS), Database
Engines, Database Instance Classes, Backup and
Recovery, Non -relational (No -SQL) Databases,
Types of Non relati onal Databases, Introduction
to DynamoDB, Features, Partition and Hash 09 CO 4

Page 124

University of Mumbai, B. E. (Information Technology), Rev 2016 309 Keys.
Self-learning Topics:
Comparison of AWS services with other cloud
service platforms like Azure and GCP.
V Openstack Cloud
platform & Severless
Computing Open source Cloud Platform: Introduction to
Openstack cloud platform, Components and
modes of Operations, Architecture of Openstack
cloud platform.
Mobile Cloud Computing: Definition,
architecture, benefits and challenges of mobile
cloud computing.
Serverless Computin g: Introduction, Working
with Serverless environment,Basics of severless
events and functions, AWS Lambda.
Self-learning Topics:
To study different open source cloud computing
platforms and compare them based on different
XaaS services provided by them. 05 CO 5
VI Cloud Security &
Privacy What is security, why is it required in cloud
computing, Different types of security in cloud,
attacks, and vulnerabilities, IaaS security, PaaS
security, SaaS security, trust boundary, Audit
and reporting.
Introduction to Identity and access Management
(IAM), IAM Challenges, IAM Definition, IAM
Architecture and Practice , Relevant IAM
Standards and Protocols for Cloud Services.
Privacy: What Is Privacy? What Are the Key
Privacy Concerns in the Cloud?, Legal and
Regulator y Implications: Laws and Regulations,
Governance, Risk, and Compliance (GRC).

Self-learning Topics:
To assess and analyze how the security and
privacy is maintained in different cloud
computing platforms. 07 CO 6

Text Books:

1. Cloud computing Bible, Barrie Sosinsky, Wiley publication.
2. Cloud Computing Black Book, Kailash Jayaswal, Jagannath Kallalurchi, Donald J. Houde, Dr. Deven Shah, Dreamtech Press
3. Mastering Cloud Computing, Rajkumar Buyya, MGH publication
4. AWS certified solution Architect, Joe Baron et.al, Cybex publication
5. Cloud Security and Privacy, Tim Mather, Subra Kumaraswamy, and Shahed Latif, O‘Reilly Publication.
6. Cloud security: A comprehensive guide to secure cloud computing by ronold L Krutz and Russell Dean Vines, Wiley
publication.

Reference Books:

1. Distributed and Cloud Computing From Parallel Processing to the Internet of Things, Kai Hwang, Geoffrey C. Fox, Jack
Dongarra, Morgan Kaufmann Publication
2. Cloud Computing for Dummies, Judith Hurwitz, Wiley Publication
3. Cloud Application Architectures: Building Applications and Infrastructure in the Cloud, George Reese, O‘Reilly Publication.
4. Cloud computing security: foundation and challenges, John R Vecca, CRC Press

Online References:

Page 125

University of Mumbai, B. E. (Information Technology), Rev 2016 310
1. https://www.aws.amazon.com
2. https://www.nttel.ac.in


Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered .

Page 126

University of Mumbai, B. E. (Information Technology), Rev 2016 311


Course Code Course Name Credits
ILO801 1 Project Management 03


Objectives:
1. To familiarize the students with the use of a structured methodology/approach for each and every
unique project undertaken, including utilizing project management concepts, tools and techniques.
2. To appraise the students with the project management life cycle and make them knowledgeable about
the various phases f rom project initiation throughclosure.

Outcomes: Learner will be able to…
1. Apply selection criteria and select an appropriate project from different options.
2. Write work break down structure for a project and develop a schedule based onit.
3. Identify opportunities and threats to the project and decide an approach to deal with them
strategically.
4. Use Earned value technique and determine & predict status of theproject.
5. Capture lessons learned during project phases and document them for futurereference



Module
Detailed Contents
Hrs


01 Project Management Foundation:
Definition of a project, Project Vs Operations, Necessity of project management, Triple
constraints, Project life cycles (typical & atypical) Project phases and stage gate process.
Role of project manager. Negotiations and resolving conflicts. Project management in
various organization structures. PMknowledge
areas as per Project Management Institute (PMI).

5


02 Initiating Projects:
How to get a project started, Selecting project strategically, Project selection models
(Numeric /Scoring Models and Non -numeric models), Project portfolio process, Project
sponsor and creating charter; Project proposal. Effective project team, S tages of team
development & growth (forming, storming, norming &
performing), team dynamics.

6


03 Project Planning and Scheduling:
Work Breakdown structure (WBS) and linear responsibility chart, Interface
Co-ordination and concurrent engineering, Project cost estimation and budgeting, Top
down and bottoms up budgeting, Networking and Scheduling techniques. PERT, CPM,
GANTT chart. Introduction to ProjectManagement
Information System (PMIS).

8


04 Planning Projects:
Crashing project time, Resource loading and leveling, Goldratt's critical chain, Project
Stakeholders and Communication plan.
Risk Management in projects: Risk management planning, Risk identification
and risk register. Qualitative and quantitative risk assessment, Probability and impact
matrix. Risk response strategies for positive and negative risks

6

Page 127

University of Mumbai, B. E. (Information Technology), Rev 2016 312 05 5.1 Executing Projects:
Planning monitoring and controlling cycle. Information needs and reporting, 8

Page 128

University of Mumbai, B. E. (Information Technology), Rev 2016 313 engaging with all stakeholders of the projects.
Team management, communication and project meetings.
Monitoring and ControllingProjects:
Earned Value Management techniqu es for measuring value of work completed; Using
milestones for measurement; change requests and scope creep. Project audit.
ProjectContracting
Project procurement management, contracting and outsourcing,




06 Project Leadership andEthics:
Introduction to project leadership, ethics in projects.
Multicultural and virtual projects.
Closing theProject:
Customer acceptance; Reasons of project termination, Various types of project
terminations (Extinction, Addition, Integration, Starvation), Process of projec t
termination, completing a final report; doing a lessons learned analysis; acknowledging
successes and failures; Project management templates and other
resources; Managing without authority; Areas of further study.



6




REFERENCES:

1. Jack Meredith & Samuel Mantel, Project Management: A managerial approach, Wiley India, 7thEd.
2. A Guide to the Project Management Body of Knowledge (PMBOK ® Guide), 5th Ed,Project
Management Institute PA,USA
3. Gido Clements, Project Management, CengageLearning.
4. Gopalan, Projec t Management, , WileyIndia
5. Dennis Lock, Project Management, Gower Publishing England, 9 thEd.

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 129

University of Mumbai, B. E. (Information Technology), Rev 2016 314 Course Code Course Name Credits
ILO801 2 Finance Management 03


Objectives:
1. Overview of Indian financial system, instruments andmarket
2. Basic concepts of value of money, returns and risks, corporate finance, working capital and its
management
3. Knowledge about sources of finance, capital structure, dividendpolicy

Outcomes: Learner will be able to…
1. Understand Indian finance system and corporatefinance
2. Take investment, finance as well as dividenddecisions



Module
Detailed Contents
Hrs





01 Overview of Indian Financial System: Characteristics, Components and Functions of
Financial System.
Financial Instruments: Meaning, Characteristics and Classification of Basic Financial
Instruments — Equity Shares, Preference Shares, Bonds -Debentures, Certificates of
Deposit, and Treasury Bills.
Financial Markets: Meaning, Characteristics and Classification of Financial Markets
— Capital Market, Money Market and Foreign Currency Market Financial
Institutions: Meaning, Characteristics and Classification of Financial Institutions —
Commercial Banks, Investment -Merchan t Banks and Stock
Exchanges



06



02 Concepts of Returns and Risks: Measurement of Historical Returns and Expected
Returns of a Single Security and a Two -security Portfolio; Measurement of Historical
Risk and Expected Risk of a Single Security and a Two-security Portfolio.
Time Value of Money: Future Value of a Lump Sum, Ordinary Annuity, and Annuity
Due; Present Value of a Lump Sum, Ordinary Annuity, and Annuity
Due; Continuous Compounding and Continuous Discounting.


06



03 Overview of Corporate Finance: Objectives of Corporate Finance; Functions of
Corporate Finance —Investment Decision, Financing Decision, and Dividend Decision.
Financial Ratio Analysis: Overview of Financial Statements —Balance Sheet, Profit
and Loss Account, and Cash Flow Statement; Purpose of Financial Ratio Analysis;
Liquidity Ratios; Efficiency or Activity Ratios; Profitability Ratios;
Capital Structure Ratios; Stock Market Ratios; Limitations of Ratio Analysis.


09


04 Capital Budgeting: Meaning and Importance of Capital Budgeting; Inputs for Capital
Budgeting Decisions; Investment Appraisal Criterion —Accounting Rate of Return,
Payback Period, Discounted Payback Period, Net Present Value(NPV), Profitability
Index, Internal Rate of Return ( IRR), and Modified
Internal Rate of Return (MIRR)

10

Page 130

University of Mumbai, B. E. (Information Technology), Rev 2016 315 Working Capital Management: Concepts of Meaning Working Capital;
Importance of Working Capital Management; Factors Affecting an Entity‘s Working
Capital Needs; Estimation of Working Capital Requirements; Management of
Inventories; Management of Receivables; and Management of Cash and Marketable
Securities.



05 Sources of Finance: Long Term Sources —Equity, Debt, and Hybrids; Mezzanine
Finance; Sources of Short Term Finance —Trade Credit, Bank Finance, Commercial
Paper; Project Finance.
Capital Structure: Factors Affecting an Entity‘s Capital Structure; Overview of Capital
Structure Theories and Approaches — Net Income Approach, Net Operating Income
Approach; Traditional Approach, an d Modigliani -Miller Approach. Relation between
Capital Structure and Corporate Value; Concept of
Optimal Capital Structure


05

06 Dividend Policy: Meaning and Importance of Dividend Policy; Factors Affecting an
Entity‘s Dividend Decision; Overview of Dividend Policy Theories and Approaches —
Gordon‘s Approach, Walter‘s Approach, andModigliani -
Miller Approach
03



REFERENCES:

1. Fundamentals ofFinancialManagement,13thEdition(2015)byEugeneF.BrighamandJoelF. Houston;
Publisher: Cengage Publications, New Delhi.
2. Analysis for Financial Management, 10th Edition (2013) by Robert C. Higgins; Publishers:
McGraw Hill Education, NewDelhi.
3. Indian Financial System, 9th Edition (2015) by M. Y. Khan; Publisher: McGraw Hill
Education, New Delhi.
4. Financial Management, 11th Edition (2015) by I. M. Pandey; Publisher: S. Chand (G/L) &
Company Limited, NewDelhi.

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be propo rtional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 131

University of Mumbai, B. E. (Information Technology), Rev 2016 316 Course Code Course Name Credits
ILO801 3 Enterpreneurship Development and Management 03


Objectives:
1. To acquaint with entrepreneurship and management ofbusiness
2. Understand Indian environment forentrepreneurship
3. Idea of EDP,MSME

Outcomes: Learner will be able to…
1. Understand the concept of business plan andownerships
2. Interpret key regulations and legal aspects of entrepreneurship inIndia
3. Understand government policies forentrepreneurs



Module
Detailed Contents
Hrs


01 Overview Of Entrepreneurship: Definitions, Roles and Functions/Values of
Entrepreneurship, History of Entrepreneurship Development, Role of Entrepreneurship
in the National Economy, Functions of an Entrepreneur, Entrepreneurship and Forms of
Business Ownership
Role of Money and Capital Markets in Entrepreneurial Development:
Contribution of Gove rnment Agencies in Sourcing information for Entrepreneurship

04



02 Business Plans And Importance Of Capital To Entrepreneurship: Preliminary and
Marketing Plans, Management and Personnel, Start -up Costs and Financing as well as
Projected Financial Statements, Legal Section, Insurance, Suppliers and Risks,
Assumptions and Conclusion, Capital and its Importance to theEntrepreneur
Entrepreneurship And Business Development: Starting a New Business,
Buying an Existing Business, New Product Development, Business Growth and the
Entrepreneur Law and its Relevance to Business Operations


09

03 Women‘s Entrepreneurship Development, Social entrepreneurship -role and need, EDP
cell, role of sustainability and sustainable development forSMEs,
case studies, exercises 05


04 Indian Environment for Entrepreneurship: key regulations and legal aspects ,
MSMED Act 2006 and its implications, schemes and policies of the Ministry of MSME,
role and responsibilities of various government organisations, departments, banks etc.,
Role of State governments in terms of infrastructure developments and support etc.,
Public private partnerships, National Skill
development Mission, Credit Guarantee Fund, PMEGP, discussions, group exercises etc

08

05 Effective Management of Business: Issues and problems faced by micro and small
enterprises and effective management of M and S enterprises (risk
management, credit availability, technology innovation, supply chain
management, linkage with large industries) , exercises,e -Marketing
08

06 Achieving Success In The Small Business: Stages of the small business life cycle, four
types of firm -level growth strategies, Options – harvesting or closing small business
Critical Success factors of small business
05

Page 132

University of Mumbai, B. E. (Information Technology), Rev 2016 317 REFERENCES:

1. Poornima Charantimath, Entrepreneurship development - Small Business Enterprise, Pearson
2. Education Robert D Hisrich, Michael P Peters, Dean A Shapherd, Entrepreneurship, latest edition, The
McGrawHillCompany
3. Dr TN Chhabra, Entrepreneurship Development, Sun India Publications, NewDelhi
4. Dr CN Prasad, Small and Medium Enterprises in Global Perspective, New century Publications,
NewDelhi
5. Vasant Desai, Entrepreneurial development and management, Himalaya PublishingHouse
6. Maddhuri ma Lall, Shikah Sahai, Entrepreneurship, Excel Books
7. Rashmi Bansal, STAY hungry STAY foolish, CIIE, IIMAhmedabad
8. Law and Practice relating to Micro, Small and Medium enterprises, Taxmann PublicationLtd.
9. Kurakto, Entrepreneurship - Principles and Practices, ThomsonPublication
10. Laghu UdyogSamachar
11. www.msme.gov.in
12. www.dcmesme.gov.in
13. www.msmetraining.gov.in


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 133

University of Mumbai, B. E. (Information Technology), Rev 2016 318 Course Code Course Name Credits
ILO801 4 Human Resource Management 03


Objectives:
1. To introduce the students with basic concepts, techniques and practices of the human resource
management.
2. To provide opportunity of learning Human resource management (HRM) processes, related with the
functions, and challenges in the emerging perspective of today‘sorganizations.
3. To familiarize the students about the latest developments, trends & different aspe cts ofHRM.
4. To acquaint the student with the importance of inter-personal & inter -group behavioral skills in an
organizational setting required for future stable engineers, leaders andmanagers.

Outcomes: Learner will be able to…
1. Understand the concepts, as pects, techniques and practices of the human resourcemanagement.
2. Understand the Human resource management (HRM) processes, functions, changes and challenges in
today‘s emerging organizationalperspective.
3. Gain knowledge about the latest developments and tre nds inHRM.
4. Apply the knowledge of behavioral skills learnt and integrate it with in inter personal and intergroup
environment emerging as future stable engineers andmanagers.



Module
Detailed Contents
Hrs



01 Introduction to HR
 Human Resource Management - Concept, Scope and Importance,
Interdisciplinary Approach Relationship with other Sciences,
Competencies of HR Manager, HRMfunctions.
 Human resource development (HRD): changing role of HRM – Human
resource Planning, Technological change, Restru cturing andrightsizing,
Empowerment, TQM, Managing ethicalissues.


5






02 Organizational Behavior (OB)
 Introduction to OB Origin, Nature and Scope of Organizational Behavior,
Relevance to Organizational Effectiveness and Contemporary issues
 Personality: Meaning and Determinants of Personality, Personality
development, Personality Types, Assessment of Personality Traits for
Increasing SelfAwareness
 Perception: Attitude and Value, Effect of perception on Individual
Decision -making, Attitude andBehavior.
 Motivation: Theories of Motivation and their Applications for
Behavioral Change (Maslow, Herzberg,McGregor);
 Group Behavior and Group Dynamics: Work groups formal and informal
groups and stages of group development. Team Effectiveness: High perfo rming
teams, Team Roles, cross functional and self -directedteam.
 Casestudy





7

03 Organizational Structure &Design
 Structure, size, technology, Environment of organization; Organizational Roles
& conflicts: Concept of roles; role dynamics; role conflictsand
6

Page 134

University of Mumbai, B. E. (Information Technology), Rev 2016 319 stress.
 Leadership: Concepts and skills of leadership, Leadership and
managerial roles, Leadership styles and contemporary issues in
leadership.
 Power and Politics: Sources and uses of power; Politics atworkplace,
Tactics andstrategies.



04 Human resource Planning
 Recruitment and Selection process, Job -enrichment, Empowerment - Job-
Satisfaction, employeemorale.
 Performance Appraisal Systems: Traditional & modernmethods,
Performance Counseling, CareerPlanning.
 Training & Development: Identification of Training Needs, Training
Methods


5



05 Emerging Trends in HR
 Organizational development; Business Process Re -engineering (BPR), BPR
as a tool for organizational development , managing processes &
transformation in HR. Organizational Change, Culture,Environment
 Cross Cultural Leadership and Decision Making : Cross Cultural
Communication and diversity at work , Causes of diversity,managing
diversity with special reference to handicapped, women and age ing
people, intra company cultural difference in employee motivation.


6




06 HR & MIS
Need, purpose, objective and role of information system in HR, Applications in HRD in
various industries (e.g. manufacturing R&D, Public Transport, Hospitals, Hotels and
serviceindustries
Strategic HRM
Role of Strategic HRM in the modern business world, Concept of Strategy,
Strategic Management Process, Approaches to Strategic Decision Making;
Strategic Intent – Corporate Mission, Vision, Objectives and Goals
Labor Laws & Industrial Relations
Evolution of IR, IR issues in organizations, Overview of Labor Laws in India;
Industrial Disputes Act, Trade Unions Act, Shops and Establishments Act



10


REFERENCES:

1. Stephen Robbins, Organizational Behavior, 16th Ed,2013
2. V S P Rao, Human Resource Management, 3rd Ed, 2010, Excelpublishing
3. Aswathapa, Human resource management: Text & cases, 6th edition,2011
4. C. B. Mamoria and S V Gankar, Dynamics of Industrial Relations in India, 15th Ed, 2015, Himalaya
Publishing, 1 5thedition,2015
5. P. Subba Rao, Essentials of Human Resource management and Industrial relations, 5thEd, 2013,
HimalayaPublishing
6. Laurie Mullins, Management & Organizational Behavior, Latest Ed, 2016, Pearson Publications

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

Page 135

University of Mumbai, B. E. (Information Technology), Rev 2016 320 End Semester Theory Examination:
Some guidelines for setting up the question p aper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of t otal sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 136

University of Mumbai, B. E. (Information Technology), Rev 2016 280 Course Code Course Name Credits
ILO801 5 Professional Ethics and Corporat Social Responsibility (CSR) 03

Objectives:
1. To understand professional ethics inbusiness
2. To recognized corporate socialresponsibility

Outcomes: Learner will be able to…
1. Understand rights and duties ofbusiness
2. Distinguish different aspects of corporate socialresponsibility
3. Demonstrate professionalethics
4. Understand legal aspects of corporate socialresponsibility


Module
Detailed Contents
Hrs

01 Professional Ethics and Business: The Nature of Business Ethics; Ethical
Issues in Business; Moral Responsibility and Blame; Utilitarianism: Weighing Social
Costs and Benefits; Rights and Duties of Business 04


02 Professional Ethics in the Marketplace: Perfect Competition; Monopoly
Competition; Oligopolistic Competition; Oligopolies and Public Policy Professional
Ethics and the Environment: Dimensions of Pollution and Resource Depletion; Ethics
of Pollution Control; Ethics of Conserving
Depletable Resour ces

08


03 Professional Ethics of Consumer Protection: Markets and Consumer Protection;
Contract View of Business Firm‘s Duties to Consumers; Due Care Theory; Advertising
Ethics; Consumer Privacy
Professional Ethics of Job Discrimination: Nature of Job Discrimination;
Extent of Discrimination; Reservation of Jobs.

06

04 Introduction to Corporate Social Responsibility: Potential Business Benefits —Triple
bottom line, Human resources, Risk management, Supplier relations; Criticisms and
concerns —Nature of business; Motives; Misdirection.
Trajectory of Corporate Social Responsibility in India
05

05 Corporate Social Responsibility: Articulation of Gandhian Trusteeship Corporate
Social Responsibility and Small and Medium Enterprises (SMEs) in India, Corporate
Social Responsibility and Public -Private Partnership (PPP) in
India
08

06 Corporate Social Responsibility in Globalizing India: Corporate Social
Responsibility Voluntary Guidelines, 2009 issued by the Ministry of Corporate Affairs,
Government of India, Legal Aspects of Corporate Social
Responsibility —Companies Act, 2013.
08

Page 137

University of Mumbai, B. E. (Information Technology), Rev 2016 281 REFERENCES:

1. Business Ethics: Texts and Cases from the Indian Perspective (2013) by Ananda Das Gupta;
Publisher:Springer.
2. Corporate Social Responsibility: Readings and Cases in a Global Context (2007) by Andrew Crane,
Dirk Matten, Laura Spence; Publisher:Routledge.
3. Business Ethics: Concepts and Cases, 7th Edition (2011) by Manue l G. Velasquez; Publisher: Pearson,
NewDelhi.
4. Corporate Social Responsibility in India (2015) by BidyutChakrabarty, Routledge, NewDelhi.
Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example su pposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 138

University of Mumbai, B. E. (Information Technology), Rev 2016 282 Course Code Course Name Credits
ILO801 6 Research Methodology 03


Objectives:
1. To understand Research and ResearchProcess
2. To acquaint students with identifying problems for research and develop researchstrategies
3. To familiarize students with the techniques of data collection, analysis of data and interpretation
Outcomes: Learner will be able to…
1. Prepare a preliminary research design for projects in their subject matterareas
2. Accurately collect, analyze and reportdata
3. Present complex data or situationsclearly
4. Review a nd analyze researchfindings



Module
Detailed Contents
Hrs



01 Introduction and Basic Research Concepts
Research – Definition; Concept of Construct, Postulate, Proposition, Thesis,
Hypothesis, Law, Principle.Research methods vsMethodology
Need of Research in Business and SocialSciences
Objectives ofResearch
Issues and Problems inResearch
Characteristics of Research:Systematic, Valid, Verifiable, Empirical and Critical


09


02 Types of Research
Basic Research
AppliedResearch
Descriptive Research
Analytical Research
EmpiricalResearch
2.6 Qualitative and Quantitative Approaches

07

03 Research Design and Sample Design
Research Design – Meaning, Types andSignificance
Sample Design – Meaning and Significance Essentials of a good sampling Stages in
Sample Design Sampling methods/techniques SamplingErrors
07





04 Research Methodology
4.1 Meaning of Research Methodology
4.2. Stages in Scientific Research Process:
a. Identification and Selection of ResearchProblem
b. Formulation of ResearchProblem
c. Review ofLiterature
d. Formulation ofHypothesis
e. Formulation of researchDesign
f. Sample Design
g. Data Collection
h. Data Analysis
i. Hypothesis testing and Interpretation ofData




08

Page 139

University of Mumbai, B. E. (Information Technology), Rev 2016 283 j. Preparation of Research Report

05 Formulating Research Problem
5.1 Considerations: Relevance, Interest, Data Availability, Choice of data, Analysis of
data, Generalization and Interpretation of analysis
04

06 Outcome of Research
Preparation of the report on conclusionreached
Validity Testing & EthicalIssues
Suggestions andRecommendation
04




REFERENCES:

1. Dawson, Catherine, 2002, Practical Research Methods, New Delhi, UBS Publishers Distributors.
2. Kothari, C.R.,1985, Research Methodology -Methods and Techniques, New Delhi, Wiley
EasternLimited.
3. Kumar, Ranjit, 2005, Research Methodology -A Step -by-Step Guide for Beginners, (2nded), Singapore,
Pearson Education



Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or at least 6 assignment on complete syllabus or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 140

University of Mumbai, B. E. (Information Technology), Rev 2016 284 Course Code Course Name Credits
ILO801 7 IPR and Patenting 03

Objectives:
1. To understand intellectual property rights protectionsystem
2. To promote the knowledge of Intellectual Property Laws of India as well as International treaty
procedures
3. To get acquaintance with Patent search and patent filing procedure andapplications

Outcomes: Learner will be able to…
1. understand Intellectual Propertyassets
2. assist individuals and organizations in capacitybuilding
3. work for development, promotion, protection, compliance, and enforcement of Intellectual Property
andPatenting


Module
Detailed Contents
Hr



01 Introduction to Intellectual Property Rights (IPR) : Meaning of IPR, Different
category of IPR instruments - Patents, Trademarks,Copyrights, Industrial Designs, Plant
variety protection, Geographical indications,Transfer of technologyetc.
Importance of IPR in Modern Global Economic Environment: Theories of IPR,
Philosophical aspects of IPR laws, Need for IPR, IPR as an instrument of
development


05



02 Enforcement of Intellectual Property Rights: Introduction, Magnitude of problem,
Factors that create and sustain counterfeiting/piracy, International agreements,
International organizations (e.g. WIPO, WTO) activein IPR enforcement
Indian Scenario of IPR: Introduction, History of IPR in India, Overview of IP laws in
India, Indian IPR, Administrative Machinery, Major international treaties signed by
India, Procedure for submitting patent and Enforcement of IPR at
national level etc.


07
03 Emerging Issues in IPR: Challenges for IP in digital economy, e -commerce,
human genome,biodiversity and traditional knowledge etc. 05


04 Basics of Patents: Definition of Patents, Conditions of patentability, Patentable and non-
patentable inventions, Types of patent applications (e.g. Patent of addition etc), Process
Patent and Product Patent, Precautions while patenting, Patent specification Patent
claims, Disclosures and non -disclosures, Patent rights
and infringement, Met hod of getting a patent

07

05 Patent Rules: Indian patent act, European scenario, US scenario, Australia scenario,
Japan scenario, Chinese scenario, Multilateral treaties where India is a
member (TRIPS agreement, Paris convention etc.)
08

06 Procedure for Filing a Patent (National and International): Legislation and Salient
Features, Patent Search, Drafting and Filing Patent Applications, Processing of patent,
Patent Litigation, Patent Publicationetc, Time frameand
cost, Patent Licensing, Pate nt Infringement
07

Page 141

University of Mumbai, B. E. (Information Technology), Rev 2016 285 Patent databases: Important websites, Searching international databases


REFERENCE BOOKS:

1. Rajkumar S. Adukia, 2007, A Handbook on Laws Relating to Intellectual Property Rights in India, The
Institute of Chartered Accountants ofIndia
2. Keayla B K, Patent system and related issues at a glance, Published by National Working Group on
PatentLaws
3. T Sengupta, 2011, Intellectual Property Law in India, Kluwer LawInternational
4. Tzen Wong and Graham Dutfield, 2010, Intellectual Property and Human Development: Current Trends
and Future Scenario, Cambridge UniversityPress
5. Cornish, William Rodolph & Llewelyn, David. 2010, Intellectual Property: Patents, Copyrights, Trade
Marks and Allied Right, 7th Edition, Sweet &Maxwell
6. Lous Harn s, 2012, The enforcement of Intellactual Property Rights: A Case Book, 3rd Edition, WIPO
7. Prabhuddha Ganguli, 2012, Intellectual Property Rights, 1st Edition,TMH
8. R Radha Krishnan & S Balasubramanian, 2012, Intellectual Property Rights, 1st Edition, Excel Bo oks
9. M Ashok Kumar and mohd Iqbal Ali, 2-11, Intellectual Property Rights, 2nd Edition, Serial Publications
10. Kompal Bansal and Praishit Bansal, 2012, Fundamentals of IPR for Engineers, 1st Edition, BS
Publications
11. Entrepreneurship Development and IPR Unit, BITS Pilani, 2007, A Manual on Intellectual
PropertyRights,
12. Mathew Y Maa, 2009, Fundamentals of Patenting and Licensing for Scientists and Engineers, World
Scientific PublishingCompany
13. N S Rathore, S M Mathur, Priti Mathur, Anshul Rathi , IPR: Drafting,Interpretation of Patent
Specifications and Claims , New India PublishingAgency
14. Vivien Irish, 2005, Intellectual Property Rights forEngineers,IET
15. Howard B Rockman, 2004, Intellectual Property Law for Engineers and s cientists, Wiley -IEEE Press
Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or at least 6 assignment on complete syllabus or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 142

University of Mumbai, B. E. (Information Technology), Rev 2016 286 Course Code Course Name Credits
ILO801 8 Digital Business Management 03

Objectives:
1. To familiarize with digital business concept
2. To acquaint withE -commerce
3. To give insights into E-business and its strategies

Outcomes: The learner will be able to …..
1. Identify drivers of digitalbusiness
2. Illustrate various approaches and techniques for E -business andmanagement
3. Prepare E -business plan

Module Detailed content Hours





1 Introduction to Digital Business -

Introduction, Background and current status, E -market places, structures,
mechanisms, economics and impacts
Difference between physical economy and digital economy,

Drivers of digital business - Big Data & Analytics, Mobile, Cloud Computing,
Social media, BYOD, and Internet of Things(digitally intelligent
machines/services)
Opportunities and Challenges in Digital Business,




09







2 Overview of E -Commerce

E-Commerce - Meaning, Retailing in e -commerce -products and services,
consumer behavior, market research and advertisement
B2B-E-commerce -selling and buying in private e -markets, public B2B exchanges
and support services, e -supply chains, Collaborative Commerce, Intra business EC
and Corporate portals
Other E -C models and application s, innovative EC System -From E - government
and learning to C2C, mobile commerce and pervasive computing
EC Strategy and Implementation -EC strategy and global EC, Economics and
Justification of EC, Using Affiliate marketing to promote your e- commerce
busin ess, Launching a successful online business and EC project, Legal, Ethics
and Societal impacts ofEC






06

Page 143

University of Mumbai, B. E. (Information Technology), Rev 2016 287
3 Digital Business Support services : ERP as e –business backbone, knowledge
Tope Apps, Information and referral system
Application Development: Building Digital business Applications and
Infrastructure
06




4 Managing E -Business -Managing Knowledge, Management skills for e -
business, Managing Risks in e –business

Security Threats to e -business -Security Overview, Electronic Commerce Threats,
Encryption, Cryptography, Public Key and Private Key Cryptography, Digital
Signatures, Digital Certificates, Security Protocols over Public Networks: HTTP,
SSL, Firewall as Security Control, Public Key Infrastructure (PKI) for Security,
Prominent Cryptographic Applications



06


5 E-Business Strategy -E-business Strategic formulation - Analysis of
Company‘s Internal and external environment, Selection ofstrategy, E -
business strategy into Action, challenges and E -Transition (Process of
DigitalTransformation)

04
6 Materializing e -business: From Idea to Realization -Business plan
preparation

Case Studies and presentations
08


References:

1. A textbook on E -commerce , Er Arunrajan Mishra, Dr W K Sarwade,Neha Publishers &
Distributors,2011
2. E-commerce from vision to fulfilment, Elias M. Awad, PHI -Restricted,2002
3. Digital Business and E -Commerce Management, 6thEd, Dave Chaffey, Pearson, August2014
4. Introduction to E-business -Management and Strategy, Colin Combe, ELSVIER,2006
5. Digital Business Concepts and Strategy, Eloise Coupey, 2ndEdition,Pearson
6. Trend and Challenges in Digital Business Innovation, VinocenzoMorabito,Springer
7. Digital Business Discourse Erika Darics, April 2015, PalgraveMacmillan
8. E-Governance -Challenges and Oppor tunities in : Proceedings in 2nd International Conference theory and
practice of ElectronicGovernance
9. Perspectives the Digital Enterprise –A framework for Transformation, TCS consulting journal Vol.5
10. Measuring Digital Economy -A new perspective -DOI: 10.1787/9789264221796 -enOECD Publishing

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or at least 6 assignment on complete syllabus or course project.

Page 144

University of Mumbai, B. E. (Information Technology), Rev 2016 288 End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number
of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 145

University of Mumbai, B. E. (Information Technology), Rev 2016 289 Course Code Course Name Credits
ILO80 19 Environmental Management 03


Objectives:
1. Understand and identify environmental issues relevant to India and global concerns
2. Learn concepts ofecology
3. Familiarise environment relatedlegislations

Outcomes: Learner will be able to…
1. Understand the concept of environmentalmanagement
2. Understand ecosystem and interdependence, food chainetc.
3. Understand and interpret environmen t relatedlegislations



Module
Detailed Contents
Hrs

01 Introduction and Definition of Environment: Significance of Environment
Management for contemporary managers, Career opportunities.
Environmental issues relevant to India, Sustainable Development, The Energy
scenario.
10

02 Global Environmental concerns : Global Warming, Acid Rain, Ozone Depletion,
Hazardous Wastes, Endangered life -species, Loss of Biodiversity, Industrial/Man -
made disasters, Atomic/Biomedical hazards, etc.
06
03 Concepts of Ecology: Ecosystems and interdependence between living
organisms, habitats, limiting factors, carrying capacity, food chain, etc. 05

04 Scope of Environment Management, Role & functions of Government as a planning
and regulating agency.
Environment Quality Management and Corporate Environmental Responsibility
10
05 Total Quality Environmental Management, ISO -14000, EMS certification. 05

06 General overview of major legislations like Environment Protection Act, Air (P & CP)
Act, Water (P & CP) Act, Wildlife Protection Act, Forest Act, Factories Act, etc.
03


REFERENCES:

1. Environmental Management: Principles and Practice, C J Barrow, Routledge Publishers
London,1999
2. A Handbook of Environmental Management Edited by Jon C. Lovett and David G.Ockwell, Edward
ElgarPublishing
3. Environmental Management, T V Ramachandra and Vijay Kulkarni, TERIPress
4. Indian Standard Environmental Management Systems — Requirements With Guidance For Use,
Bureau Of Indian Standards, February2005
5. Environmental Man agement: An Indian Perspective, S N Chary and Vinod Vyasulu, Maclillan
India,2000

Page 146

6. Introduction to Environmental Management, Mary K Theodore and Louise Theodore,
CRC Press
7. Environment and Ecology, Majid Hussain, 3rd Ed. AccessPublishing.20 15



Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other
is either a class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in
question papers of end semester examination. In question paper weightage of each module will
be proportional to number of respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total sixquestion
2. All question carry equalmarks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module3)
4. Only Four question need to besolved.