ME IT 2022 23 final syllabus 1 Syllabus Mumbai University

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AC – 11 July, 2022
Item No. – 6.27 (R)




University of Mumbai








Revised Syllabus for
M.E. (Information Technology )
(Sem. - I to IV)
(Choice Based Credit System)




(With effect from the academic year 2022 -23)

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SemesterI

CourseCo
de CourseName TeachingScheme(ContactHours) Credits Assigned
Theory Pract. Tut. Theory Pract. Tut. Total
ME-ITC101 Data Science and
Engineering 3 -- -- 3 -- -- 3
ME-ITC102 Blockchain
Technology 3 -- 3 -- 3
ME-ITPE101 X ProgramElective 1 3 -- -- 3 -- -- 3
ME-ITPE102 X ProgramElective 2 3 -- -- 3 -- -- 3
IE101 X InstituteElective1 3 -- -- 3 -- -- 3
ME-ITL101 ProgramLab -I -
- 2 -- -- 1 -- 1
ME-ITSBL101 Skill Based Lab -I -
- 4$ -- -- 2 -- 2
Total 15 06 -- 15 03 -- 18

CourseCo
de

CourseName ExaminationSchem
e
Theory
Term
Work Pract
/Ora
l
Total InternalAssessment End
Sem.Ex
am Exam.
Duration
(inHrs) Test -1 Test -2 Avg
ME-ITC101 Data Science and
Engineering 20 20 20 80 3 -- -- 100
ME-ITC102 Blockchain
Technology 20 20 20 80 3 -- -- 100
ME-ITPE101 X ProgramElective 1 20 20 20 80 3 -- -- 100
ME-ITPE102 X ProgramElective 2 20 20 20 80 3 -- -- 100
IE101 X InstituteElective1 20 20 20 80 3 -- -- 100
ME-ITL101 ProgramLab -I -- -- -- -- -- 25 25 50
ME-ITSBL101 Skill Based Lab -I -- -- -- -- -- 50 50 100
Total -- -- 100 400 -- 75 75 650

$indicates workloadofLearner(NotFaculty),forSkillBasedLab
Note1: SkillBasedLab -
IandIIshallincludeactivity/project basedlearninglike
1) Miniprojectinengineeringdomainsrelatedtothespecializationorinterdisciplinarydomains
2) ProductDesign
3) ApplicationSoftwareDevelopment
4) Ideaproposalandvalidation


#ProgramElective

Every student is required to take one ProgramElective Course for Semester I and Semester
II.Different sets of courses will run in both the semesters. Students can take these courses from
the list of program electives,whicharecloselyalliedtotheirdisciplines.

# InstituteElective
Every student is required to take one Institute Elective Course for Semester I and Semester II,
which isnotcloselyalliedtotheirdisciplines.Differentsetsofcourseswillrunintheboththeseme sters.

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Course Code
Program Elective
(PE) Course Code
Institute Elective (IE)
SemesterI
ME-ITPE1011 Ethical Hacking and
Digital Forensics IE1011 ProductLifecycleManagement
ME-ITPE1012 Data Preparation and
Analysis
IE1012 ReliabilityEngineering
ME-ITPE1013 Metaverse IE1013 ManagementInformation System


ME-ITPE1014 Algorithm and
Complexity
IE1014 DesignofExperiments
ME-ITPE1021 Advances in Software
Engineering
IE1015 Operation Research
ME-ITPE1022 Ad-hoc Networks IE1016 CyberSecurityandLaws
ME-ITPE1023 Storage Area Network IE1017 DisasterManagementandMitigat
ionMeasures
ME-ITPE1024 ICT for Social Cause IE101 8 EnergyAudit andManagement
IE1019 Development Engineering

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SemesterII

$indicates workloadofLearner(NotFaculty),forSkillBasedLab

Note1: SkillBasedLab -IandIIshallincludeactivity/projectbasedlearninglike
1) Miniprojectinengineeringdomainsrelatedtothespecializationorinterdisciplinarydomains
2) ProductDesign
3) ApplicationSoftwareDevelopment
4) Ideaproposalandvalidation

#ProgramElective

Every student is required to take one ProgramElective Course for Semester I and Semester
II.Different sets of courses will run in both the semesters. Students can take these courses
from the list of program electives,whicharecloselyalliedtotheirdisciplines.
# InstituteElective
Every student is required to ta ke one Institute Elective Course for Semester I and Semester
II, which
isnotcloselyalliedtotheirdisciplines.Differentsetsofcourseswillrunintheboththesemesters.



CourseCo
de CourseName TeachingScheme(ContactHours) Credits Assigned
Theory Pract. Tut. Theory Pract. Tut. Tot
al
ME-ITC201 Web X.0 3 -- -- 3 -- -- 3
ME-ITC202 Cloud Computing
and Services 3 -- 3 -- 3
ME-ITPE 201X ProgramElective 3 3 -- -- 3 -- -- 3
ME-ITPE 202X ProgramElective 4 3 -- -- 3 -- -- 3
IE201 X InstituteElective2 3 -- -- 3 -- -- 3
ME-ITL201 ProgramLab -II -
- 2 -- -- 1 -- 1
ME-ITSBL 201 SkillBasedLab -II -
- 4$ -- -- 2 -- 2
Total 1
5 06 -- 15 03 -- 18

CourseCo
de

CourseName ExaminationSchem
e
Theory
Term
Work Pract
/Oral
Total InternalAssessment End
Sem.
Exam Exam.
Duration
(inHrs) Test-1 Test-2 Avg
ME-ITC201 Web X.0 20 20 20 80 3 -- -- 100
ME-ITC202 Cloud Computing
and Services 20 20 20 80 3 -- -- 100
ME-ITPE201 X ProgramElective 3 20 20 20 80 3 -- -- 100
ME-ITPE202 X ProgramElective 4 20 20 20 80 3 -- -- 100
IE201 X InstituteElective2 20 20 20 80 3 -- -- 100
ME-ITL201 ProgramLab -II -- -- -- -- -- 25 25 50
ME-ITSBL201 SkillBasedLab -II -- -- -- -- -- 50 50 100
Total -- -- 100 400 -- 75 75 650

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U SubjectCode Program Elective
(PE) SubjectCode Institute Elective (IE)
Semester
II
ME-ITPE2011

Web Application Security IE2011 ProjectManagement
ME-ITPE 2012

Machine and Deep
Learning IE201 2 FinanceManagement
ME-ITPE201 3
ARVR
IE201 3 Entrepreneurship Development
andManagement
ME-ITPE201 4

High Performance
Computing IE2014 HumanResourceManagement
ME-ITPE2021 Design Thinking IE2015 ProfessionalEthicsandCSR
ME-ITPE20 22 Internet of Everything IE2016 ResearchMethodology
ME-ITPE20 23 Information Retrieval IE2017 IPRandPatenting
ME-ITPE20 24 Green IT IE2018 DigitalBusiness Management
IE2019 EnvironmentalManagement

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U SemesterIII
CourseC
ode
CourseName Teaching
Scheme(ContactHo
urs) Credits Assigned
Theory Pract. Tut. Theory Pract. Tut. Total
ME-ITMP301 MajorProject:
Dissertation -I -- 20 -- -- 10 -- 10
Total 00 20 -- 00 10 -- 10

CourseC
ode

CourseName ExaminationScheme
Theory
Term
Work
Pract/
Oral
Total InternalAssessment End
Sem.
Exam Exam.
Duration
(inHrs) Test-1 Test-2 Avg
ME-ITMP301 MajorProject:
Dissertation -I -- -- -- -- -- 100 -- 100
Total -- -- -- -- -- 100 -- 100
OnlineCreditCourses

CourseC
ode
CourseName Teaching
Scheme(Contact
Hours) Credits Assigned
Theory Pract. Tut. Theory Pract. Tut. Total
ME-ITOCC301 OnlineCreditCourse -I -- -- -- -- -- -- 3
ME-ITOCC301 OnlineCreditCourse -II -- -- -- -- -- -- 3
Total -- -- -- 00 00 00 06

Note 2: It is mandatory to complete the Online Credit Courses (OCC) available on NPTEL / Swayam /MOOC or
similarplatform approved by university. The learner shall opt for one course each from OCC - I and OCC -
II. These
twocoursesshallbecompletedinanysemesterIorIIorI II,butnotlaterendoftheSemesterIII.Thecreditsearnedwith
OCC -IandOCC -IIshallbeaccountedinthethirdsemestergrade -
sheet.Thelearnershallbeallowedtotakeupthesecourses from his or her institute or organization / industry
where his / her major project is carried out. The studentsshall complete the courses and shall qualify the
exam conducted by the respective authorities/ instructor from theplatform. The fees for any such courses
and the corresponding examination shall be borne by the learner.
Universityshallmakeaprov isionthatcreditearnedwithOCC -IandOCC -
IIshallbeaccountedinthethirdsemestergrade -sheetwithactual namesofthe courses.
OnlineCreditCourse –I
The learner shall opt for the course in the domain of Research Methodology or Research & Publication
Ethics orIPR.The o ptedcourseshall beof3 creditsofequivalentnumberofweeks.
OnlineCreditCourse –II
The learner shall opt for the course recommended by Faculty Advisor/ Project Supervisor from the
institute. Theopted course shall be of3creditsofequivalentnumber ofweeks.

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SemesterIV
Course
Code
CourseName Teaching Scheme(
ContactHours) Credits Assigned
Theory Pract. Tut. Theory Pract. Tut. Total
ME-ITMP401 MajorProject:
Dissertation -II -- 32 -- -- 16 -- 16
Total -- 32 -- -- 16 -- 16

Course
Code

CourseName ExaminationScheme
Theory
Term
Work
Pract/
Oral
Total InternalAssessment End
Sem.
Exam Exam.
Duration
(inHrs) Test-1 Test-2 Avg
ME-ITMP401 MajorProject:
Dissertation -II -- -- -- -- -- 100 100 200
Total -- -- -- -- -- 100 100 200
Total Credits:68

Note3: TheDissertationsubmissionshallnotbepermittedtillthelearnercompletesallthecreditrequirementsofM
Ecourse.

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SemesterI


Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITC101 Data
Science and
Engineering 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
ME-ITC101 Data
Science
and
Engineering 20 20 20 80 -- -- -- 100

Sr. No. Course Objectives
The course aims:
1 To know the fundamental concepts of data science
2 To understand the role of basic mathematics and statistics in data science .
3 To understand the EDA process.
4 To introduce students to the basic concepts and techniques of Machine Learning.
5 Explore different methods of data visualization .
6 To enable students to analyze data science methods for real world problems .



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 Elaborate the concept of data science and related terminology. L2
2 Apply the concepts of mathematics and statistics to solve the data science problem. L3
3 Apply EDA process before using the data. L3
4 Apply machine learning techniques to solve the real world problems. L3, L4
5 Identify and use appropriate data visualization technique. L3
6 Analyze current trends in Data Science and REST API. L4

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DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO
Mappin
g
0 Prerequisite Knowledge of Basic Python/R Programming 02
I An
Introduction
to Data
Science

What is data science ? Basic terminology, Why data
science?, Example – Sigma Technologies , The data
science Venn diagram.
Types of Data : Structured versus unstructured data,
Quantitative versus qualitative data,
The four levels of data: The nominal level, ordinal level,
interval level and ratio level, The Five Steps of Data
Self-LearningTopics: Applications and Case Studies of
Data Science in various Industries 04 CO1

II Mathematics
for DS


Linear Algebra : Vector and Matrices
Probability: Dependence and Independence, Conditional
Probability, Bayes’s Theorem, Random Variables
Statistics: Basic Statistics, what are statistics? How do we
obtain and sample data? Obtaining data: Observational
and Experimental, Sampling data: Probability sampling,
Random sampling, Unequal probability sampling How do
we measure statistics: Measures of center, Measures of
variation, Measures of relative standing, The insightful
part – correlations in data, The Empirical rule
Self-learning Topics: Explore P andas and Numpy
libraries of Python 08 CO2

III EDA &
Feature
Engineering Data Wrangling:
Read the data, slicing and dicing the data, filter the data,
finding statistical inference, finding missing values,
Finding missing values or invalid values, checking if
dataset is imbalanced, checking datatypes - categorical Vs
numeric, use of group by fun ction
Data Preparation:
Identifying categorical features and converting their data
types, encoding categorical variables, sampling of
imbalance dataset, Transformation technique for skewed
distributions, scaling and normalization of data 06 CO3

IV Machine
learning


Learning with Regression: Linear Regression, Logistic
Regression.
Learning with Trees: Bayes Classification, Decision
Trees, Random Forest.
Clustering: Choosing distance metrics , Different
clustering approaches , hierarchical agglomerative
clustering, K -means DBSCAN – Relative merits of each
method – clustering tendency and quality. 08 CO4

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U Advanced Algorithm :Gradient Boosting Algorithm
Self-Learning Topics : Real world case studies on
machine learning
V Data
Visualization
Data Visualization Need and Importance: Find
distribution features, Identify the outliers, Univariate,
bivariate and multivariate analysis, correlation plots.
Data Visualization Options : Interactive graphics,
Plotting: Scatter Plots, Bar Plo ts, choosing right plots, 3D
visualization
Self-Learning Topics : Explore matplotlib and seaborn
library 06 CO5

VI Case Studies
in Data
Science
Case Study 1 – Predicting stock prices based on social
media:
Text sentiment analysis, Exploratory data analysis,
Regression route, Classification route
Case Study 2 - The case of Lending club
05 CO6


Text Books
1. Sinam Ozdemir, “Principles of Data Science”, Packt Publication,2016.
2. Davy Cielen, Arno D.B. Meysman, Mohamed Ali, “Introducing Data Science”, 2016
3. Ethem Alpaydın, “Introduction to Machine Learning”, MIT Press
4. Dan Toomey, “R for Data Science”, Packt Publication,2014

References:
1. Tom M.Mitchell, “Machine Learning”, McGraw Hill
2. Joel Grus. “Data Science from Scratch. First Principles With Python. ” O’Reilly Media, 2015.
3. Jake Vander Plas, “Python Data Science Handbook”, O’Reilly publication
4. Frank Kane, “Hands -On Data Science and Python Machine Learning”, P ackt Publication
5. Armando Fandango, “Python Data Analysis”, Second Edition, Packt publication.
6. Alberto Boschetti, Luca Massaron, “Python Data Science Essentials S econd Edition”, Packt
Publication

Online References:
1. https://onlinecourses.nptel.ac.in/noc22_cs32/preview
2. https://www.coursera.org/specializations/jhu -data-science
3. https://www.cour sera.org/learn/machine -learning
4. https://home.csulb.edu/~jchang9/files/jonathan_guzman_honors_thesis.pdf

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum 02
Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestion s to be set each of 20 marks, out of
these any four questions to beattempted by students. Minimum 80% syllabus should be covered
inquestionpapersofendsemesterexamination.

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Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITC102 Blockchain
Technology 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
ME-ITC102 Blockchain
Technology 20 20 20 80 -- -- -- 100
Course Objectives

Sr.No The course aims:
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.


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. L2
2 Interpret the knowledge of the Bitcoin network, nodes, keys, wallets and
transactions . L3
3 Implement smart contracts in Ethereum using different development
frameworks. L3
4 Develop applications in permissioned Hyperledger Fabric network. L3
5 Interpret different Crypto assets and Crypto currencies L3
6 Analyze the use of Blockchain with AI, IoT and Cyber Security using case
studies. L4

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DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Hash functions, Public – Private keys, SHA,
ECC, Digital signatures, 02
I Introduction to
DLT and
Blockchain Fundamental concepts of Distributed systems ,
Distributed Ledger Technologies (DLTs)
Introduction, Types of Blockchains
Blockchain: Origin, Phases, Components
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 5 CO1
II Consensu s and
Mining What is Bitcoin and the history of Bitcoin,
Bitcoin Transactions, Bitcoin Concepts: keys,
addresses and wallets, Bitcoin Transactions,
validation of transactions, PoW consensus
Bitcoin Network : Peer -to-Peer Network
Architecture, Node Types and Roles, Incentive
based Engineering, The Extended Bitcoin
Network, Bitcoin Relay Networks, Network
Discovery, Full Nodes, Exchanging
“Inventory”, Simplified Payment Verification
(SPV) Nodes, SPV Nodes and Privacy,
Transaction Pools, Blockchain Forks
Self-learning Topics: Study and compare
different consensus algorithms like PoA, PoS,
pBFT 8 CO2
III Permissionless
Blockchain:
Ethereum Components, Architecture of Ethereum, Miner
and mining node, Ethereum virtual machine,
Ether, Gas, Transactions, Accounts, Patricia
Merkle Tree, Swarm, Whisper and IPFS,
Ethash, End to end transaction in Ethereum,
Smart Contracts : Smart Contract programming
using solidity, Metamask (Ethereum Wallet),
Setting up development environment, Use cases
of Smart Contract, Smart Contracts:
Opportunities and Risk.
Smart Contract Deployment : Introduction to
Truffle, Use of Remix and test networks for
deployment
Other Permissionless Blockchain platforms
Introduction : IOTA, Hashgraph, EOS, etc.
Self-learning Topics: Smart contract
development using Java or Python 9 CO3
IV Permissioned
Blockchain :
Hyperledger Introduction to Framework, Tools and
Architecture of Hyperledger Fabric Blockchain.
Components : Certifi cate Authority, Nodes, 7 CO4

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Kafka, RAFTDesigning Hyperledger
Blockchain
Other Permissioned Blockchain platforms
Introduction : CORDA, Quoram, etc.
Self-learning Topics: Fundam entals of
Hyperledger Composer
V Crypto assets and
Cryptocurrencies Fungible and Nonfungible tokens, ERC20 and
ERC721 standards , comparison between ERC20
& ERC721, ICO, STO, Different Crypto
currencies
Self-learning Topics: Defi, Metaverse, Types
of cryptocurrencies 4 CO5
VI Blockchain
Applications &
Research Areas Blockchain in IoT, AI , Cyber Security ,
Research Areas : Interoperability, Privacy,
Performance, Oracles, Security of smart
contracts and platforms
Self-learning Topics: Applications of
Blockchain in various domains Education,
Energy, Healthcare, real -estate, logistics, supply
chain 4 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, Bui ld 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 Inno vative Investor’s Guide to Bitcoin and Beyond, Chris Burniske & Jack Tatar.

Reference:
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 Modi, Packt p ublication.
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

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U 2. www.sway am.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: https://andersbrownworth.com/blockchain/
8. Blockchain Demo: Public / Private Keys & Signing:
https://andersbrownworth.com/blockchain/public -private -keys/
Assessment:

Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class t est (on minimum 02
Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks, out of
these any four questions to beattempted by students. Minimum 80% syllabus should be covered
inquestionpapersofendsemesterexamination.

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Course Code Course Name Theory Practical Tutorial Theory Pract ical/
Oral Tutorial Total
ME-ITPE1011 Ethical Hacking
& Digital
Forensics 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
ME-ITPE1011 Ethical
Hacking &
Digital
Forensics 20 20 20 80 -- -- -- 100

Course Objectives

Sr.No The course aims:
1 To understand computer forensic technology.
2 To identify types of computer forensic systems.
3 To explore the procedures for identification, preservation, and extraction of digital evidence.
4 To explore the electronic evidence, identification of forensic data.
5 To learn how to investigate attacks on mobile platforms.
6 To explore various hacking techniques.


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 computer forensic technology. L2
2 To discuss the types of computer forensics systems. L2
3 Understand the process of collection, analysis and recovery of the digital evidence L2, L4
4 Understand the process of computer analysis . L2
5 Identify various security aspects with respect to mobile technology.
L1
6 Understand variou s hacking tools and techniques. L2

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DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO Mapping

Prerequisite Ethical Hacking terminology, Legal implication of
hacking, Impact of hacking. 2
I Overview of
computer
Forensics
Technology
Introduction to computer
forensics, use of forensics in law enforcement,
employment proceedings,
computer Forensics services. Types of computer
Forensics Technology - Military, law, spyware and
Adware, Biometrics security systems
Self-learning Topics:
Relevant law to combat computer crime –Information
Technology Act 5 CO1
II Foot
Printing &
Social
Engineering
Information gathering Methodologies, Competitive
Intelligence, DNS
Enumerations, Social Engineering attacks.
Types of Computer Forensics systems:
Internet security, IDS, Firewall, Public key.
Self-learning Topics: Types of IDS and Firewall 6 CO2
III Incident and
Incident
Response
and Storage
Introduction to Incident, Incident Response
Methodology, Steps, Activities in
Initial Response Phase after detection of an incident.
Initial Response and Forensic Duplication:
Initial Response & Volatile Data Collection from
Windows system, Initial
Response & Volatile Data Collection from Unix system,
Forensic Duplication: Forensic duplication as
Admissible Evidence, Forensic
Duplication Tool Requirements.
Digital Forensics: Introduction – Evidential potential of
digital devices: closed
vs. open systems, evaluating digital evidence potential,
Device handling:
seizure issues, device identification, networked devices
and contamination.
Self-learning Topics: dd, WinHex, Helix3Pro 7 CO3
IV Network
Forensics
Collecting Network Based Evidence, Investigating
Routers, Network protocols,
Email Tracing, Internet Fraud.
Self-learning Topics: tcpdump, snort 6 CO4
V Mobile
Phone
Forensics
Crime and mobile phones, evidence, forensic
procedures, files present in SIM
card, device data, external memory dump, evidences in
memory card, operators
systems.
Self-learning Topics: Wireshark, Autopsy, SIFT. 6 CO5
VI Hacking
Scanning & Enumeration:
Port Scanning, Network Scanning, Vulnerability 7 CO6

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U Scanning, NMAP Scanning
tool, OS Fingerprinting, Enumeration.
System Hacking:
Password cracking techniques, Key loggers, Escalating
privileges, Hiding Files,
Steganography Technologies, Countermeasures.
Sniffe rs & SQL Injection:
Active and passive sniffing, ARP Poisoning, Session
Hijacking, DNS Spoofing,
Conduct SQL Injection attack, Countermeasures.
Self-learning Topics : IP Spoofing, Buffer Overflow,
Password attacks.
Text Books:
1. Kevin Mandia, chirs Proise, “Incident Response and Computer Forensic”
2. Marjie T Britz, “Computer Forensics and Cyber Crime: An Introduction”, Pearson Education,
2nd Edition
3. Peter Stepheson,”Investigating Computer Crime: A handbook for corporate investigation”
4. Nilakshi Jain, Dhananjay Kalbande, “Digital Forensic: The fascinating world of Digital
Evidences” Wiley India Pvt Ltd 2017.
References:
1. Mari E -Helen Maras, “Computer Forensics: Cybercriminals, Laws, and Evidence”, Jones & Bartlett
Learning; 2nd Edition, 2014.
2. Maji d Yar, “Cybercrime and Society”, SAGE Publications Ltd, Hardcover, 2nd Edition
3.Cyber Forensics: A Field Manual for Collecting, Examining, and Preserving Evidence of Computer.
4. Handbook of Computer Crime Investigation, edited by Eoghan Casey.


Assessme nt:

Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum 02
Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks, out of
these any four questions to beattempted by students. Minimum 80% syllabus should be covered
inquestionpapersofendsemesterexamination.

Page 21

U

Course C ode Course Name Theory Practical Tutorial Theory Practical/
Oral Tutori
al Total
ME-ITPE10 12 Data
Preparation and
Analysis 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
ME-ITPE10 12 Data
Preparati
on and
Analysis 20 20 20 80 -- -- -- 100

Course Objectives :

Sr. No. Course Objectives

The course aims:
1 To know the fundamental concepts of data science
2 To understand the EDA process.
3 To explore different methods of data visualization .
4 To understand the role of statistics and machine learning in data science .
5 To learn data ethics associated with data management.
6 To enable students to analyze the recent trends in data collection and analysis techniques for real world
problem.

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 core concept and technologies related with data. L2
2 Apply EDA process before using the data. L3
3 Identify and use appropria te data visualization techniques. L1
4 Apply the concepts of statistics and machine learning techniques to solve the
real world problem. L3
5 Identify the data ethics to be followed while providing solution to real world
problem. L1
6 Analyze recent trends available f or data collection and analysis. L4

Page 22

U



DETAILED SYLLABUS:

Module Detailed Contents Hrs
1 Introduction
Introduction to core concepts and technologies, Types of data - Example applications.
Applications of Data Science - Recent trends in various data collection and analysis
techniques.
Self-learning Topics : study applications of data science. 3
2 Data Gathering and Preparation
Understanding how to create the data set, Data collection methods. Sources of data -
Data collection and APIs - Exploring and fixing data - Data storage and management
Self-learning Topics : Study and list the different APIs 7
3 Data Cleaning
Importance of data ‘cleaning’, validity and quality. Data Quality, Addressing Data
Quality Issues, Consistency checking, Heterogeneous and missing data, Data
Transformation and Segmentation
Self-learning Topics : Identify the issues in data cleaning. 7
4 Data visualization
Designing visualizations, Visualization Tools(Area Plots, Histograms ,Bar Charts, Pie
Charts, Box Plots, Scatter Plots, Waffle Charts, Word Clouds), Visualizing Geospatial
Data, visualizing time series data, Importance of data visualization Dashboards
Self-learning Topics Case study on data visualization 7
5 Data Analysis
Introduction -Terminology and concepts - Introduction to statistics - Central tendencies
and distributions – Variance - Distribution properties, Basic machine learning
algorithms - Linear regression – SVM - Naive Bayes.
Self-learning Topics : case study on data analysis 7
6 Ethics in data management
Principles of data ethics, The Five Cs: consent, clarity, consistency, control (and
transparency), and consequences (and harm)
Developing ethical and professional safeguards, Doing good data analysis, Owners of
the data, Valuing different aspects of privacy, Getting informed consent
Self-learning Topics : case study on data management. 8


Text Books
1. Sinam Ozdemir, “Principles of Data Science”, Packt Publication,2016.
2. Davy Cielen, Arno D.B. Meysman, Mohamed Ali, “Introducing Data Science”, 2016
3. Ethem Alpaydın, “Introduction to Machine Learning”, MIT Press
4. Dan Toomey, “R for Data Science”, Packt Publication,2014

References:
1. Tom M.Mitchell, “Machine Learning”,McGraw Hill
2. Joel Grus. “Data Science from Scratch. First Principles With Python.” O’Reilly Media, 2015.
3. Jake Vander Plas, “Python Data Science Handbook”, O’Reilly publication
4. Frank Kane, “Hands -On Data Science and Python Machine Learning”, Packt Publication
5. Armando Fandango, “Python Data Analysis”, Second Edition, Packt publica tion.
6. Alberto Boschetti, Luca Massaron, “Python Data Science Essentials Second Edition”, Packt Publication
7. Katherine O’Keefe , Daragh O Brien , “Ethical Data and Information Management: Concepts, Tools and
Methods ”, Kogan Page

Page 23

U Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum 02
Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks, out of
these any four questions to beattempted by students. Minimum 80% syllabus should be covered
inquestionpapersofendsemesterexamination.

Page 24

U

Course Code Course
Name Theory Practical Tutorial Theory Pract ical/
Oral Tutorial Total
ME-ITPE10 13
Metaverse
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
ME-ITPE10 13
Metaverse
20 20 20 80 -- -- -- 100

Course Objectives

Sr.No The course aims:
1 To study the concepts of Metaverse.
2 To study Metaverse and Web 3.0, Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality
(MR), NFT in Blockchain.
3 To study the Metaverse technologies and protocols.
4 To study and identify the required infrastructure for Metaverse.
5 To study various case studies of Metaverse.
6 To study of Metaverse Immersive technology and Interfaces.

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 To Understand the concepts of Metaverse. L2
2 To understand and study Metaverse and Web 3.0, Virtual Reality (VR),
Augmented Reality (AR), and Mixed Reality (MR), NFT in Blockchain. L2, L3
3 To Understand the Metaverse technologies and protocols. L2
4 To Identify the required infrastructure for Metaverse. L1
5 To Understand different case studies of Metaverse. L1
6 To Understand Metaverse Immersive technology and Interfaces L2

Page 25

U


DETAILED SYLLABUS :

Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Basic Concepts of Blockchain Technology. 02
I Introduction: What is the Metaverse? Evaluation of
Technology: Web, AR VR, 3D spaces,
Immersive learning , Blockchain , Decentralised
commerce
Self-learning Topics : Study different technology
in Metaverse with application. 03 CO1
II Fundamental
Concepts of AR,
VR, MR and
Blockchain: Building bl ock technology of metaverse , How
Gaming + Web 3.0 + Blockchain are Changing
the Internet: Future of Internet: How Metaverse
is different from Internet, Potential of Metaverse
characteristics that characterise metaverse The
Different Shapes of the Metaverse: Games,
NFTs (assets), Blockchain Protocols,
Crypto currencies, etc

Self-learning Topics : Case study on Metaverse
and ARVR 07 CO2
III Metaverse
Technologies
and Protocols: Metaverse technologies, principles, affordances
and challenges
Blockchain Protocols and Platforms Involved in
the Metaverse
Metaverse -Related Tokens
Blockchain NFT need for metaverse: working
principle of blockchain, NFT based virtual assets
in metaverse, case study
How NFTs are Unlocking the Metaverse
Potential working of ERC721 NFT

Self-learning Topics : Case study on Metaverse
and Blockchain

06 CO3
IV Metaverse
Infrastructure: Access the metaverse, necessary
hardwareUnderstanding Decentraland , native
token MANA, creating own Avatar. Using
metamask to access Decentraland, owning land
to have direct access of metaverse .

Self-learning Topics : Case study on Metaverse
and Infrastructure

06 CO4

Page 26

U V Case studies of
Metaverse: Various usecase of metaverse
Industries Disrupted by the Metaverse: Fashion,
Marketing, Brands, Finance, Gaming,
Architecture, Virtual Shows/Concerts, Art
Galleries and Museums
Virtual Business and market, Investing In the
Metaverse and Profit
Asset Classes Inside the Metaverse
Metaverse Land Ownership - Property
Investment
Self-learning Topics : Case study on Metaverse
application 07 CO5
VI Metaverse
Immersive
technology and
Interfaces: 3d Reconstruction, AI technology to analyses 3D
Scan Virtual Reality (VR) and Augmented
Reality (AR), Mixed Reality (MR) and Extended
Reality (XR), Metaverse vs VR what is
difference, IoT to bridge gap between physical
world and internet
Metaverse Interf aces: Personal Computer,
Mobile Phone, AR Glasses, VR Goggles,
Neuralink
Self-learning Topics : Case study on Metaverse
and MR
08 CO6

Text & Reference Books:
1. Mystakidis, Stylianos, “ Metaverse”,Journal=Encyclopedia,2022, https://www.mdpi.com/2673 -8392/2/1/31
2. All One Needs to Know about Metaverse: A Complete Survey on TechnologicalSingularity, Virtual Ecosystem,
and Research Agenda, Technical Report · October 2021

Online References:
1. https://www.udemy.com/course/complete -metaverse -course -everything -about -ar-vr-and-nfts/
Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum 02
Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks, out of
these any four questions to beattempted by students. Minimum 80% syllabus should be covered
inquestionpapersofendsemesterexamination.

Page 27

U
Course Code Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ME-ITPE1 014 Algorithm
and
Complexity 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
ME-
ITPE10 14 Algorithm
and
Complexity 20 20 20 80 -- -- -- 100

Course Objectives

Sr.No The course aims:
1 To analyze asymptotic performance of algorithms using space and time complexities. .
2 To teach problem formulation and problem solving skills and write rigorous correctness proofs for
algorithms.
3 To acquire knowledge and gain familiarity with major applied algorithms.
4 To apply important algorithmic design paradigms and methods of analysis.
5 To solve complex problems in real -life applications.
6 To synthesize efficient algorithms in common engineering design situations.


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 Analyze various algorithms with practical applications along with their
resource requirements. L4
2 Explore advanced design and analysis techniques. L2, L 4
3 Explain major graph algorithms and their analyses. L2
4 Analyze linear programming and string matching algorithms. L4
5 . Identify NP -complete problems and offer solutions to solve such problems. L1
6 Analyze approximation algorithms. L4


DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping

Page 28

U 0 Prerequisite Role of algorithms in computingAlgorithms as a
technology 02
I Introduction to
algorithm and
complexity Design and analysis fundamentals of algorithms
Performance analysis and space and time
complexities
Growth of functions: Asymptotic analysis —Big
oh, omega, and theta notations
Mathematical background for algorithm and
complexity
Recurrence equations and method of solving
recurrences, i.e., substitution method, recursion -
tree method and master method
Self-learning topics:
Probabilistic analysis and randomized algorithms
Sorting and order statistics (i.e., heap sort and
quick sort) 05 CO1
II Advanced design
and analysis
techniques Dynamic programming: Matrix -chain
multiplication, longest common subsequence, 0/1
Knapsack problem, Travelling salesman problem
Greedy algorithms: An activity -selection
problem, elements of the greedy strategy,
Huffman codes
Self-learning topics :
Amortized analysis 08 CO2
III Graph algorithms Introduction
Single -source shortest path: Bellman –Ford
algorithm, Dijkstra’s algorithm
All-pairs shortest path: Floyd –Warshall
algorithm, Johnson’s algorithm for sparse graphs
Maximum flow: Flow networks, Ford –Fulkerson
algorithm, maximum bipartite matching
Self-learning topics:
Breadth -first search and Depth -first search
Minimum spanning trees 08 C03
IV Linear
programming and
string matching Linear programming: Standard and slack forms,
formulating problems as linear programs,
simplex algorithm, duality, and initial basic
feasible solution . String matching: Naïve string -
matching algorithm, Rabin –Karp algorithm,
string matching with finite automata, and Knuth –
Morris –Pratt algorithm
Self-learning topic s:
DFT and FFT , 08 C04

Page 29

U V NP-completeness Polynomial time
NP-completeness and reducibility
NP-complete problems: Clique problem,
Hamiltonian -cycle problem
Self-learning topics:
 Polynomial -time verification 04 C05
VI Approximation
algorithms  Vertex -cover problem
 Travelling salesman problem
 Set-covering problem
 Subset -sum problem
Self-learning topics:
 Randomization and linear programming 04 C06

Text Books:
1. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, “Introduction to Algorithms”,
PHI, India, Third Edition.
2. Herbert S. Wilf, “Algorithms and Complexity”, University of Pennsylvania, Taylor & Francis Group,
2020.
3. Ellis Horowitz, Sartaj Sahni, and Sanguthevar Rajasekaran, “Computer Algorithms”, Computer Science
Press.

References:
1. S. K. Basu, “Design Methods and Analysis of Algorithm”, PHI.
2. Harsh Bhasin, “Algorithms: Design and Analysis”, Oxford University Press.
3. Vijay V. Vazirani, “Approximation Algorithms”, Springer.

Online Reference:
1. Design and Analysis of Algorithms, Link: https://nptel.ac.in/courses/106101060


Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 30

U Course Code Course Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ME-ITPE 1021
Advances in
Software
Engineering 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
ME-ITPE 1021







Advances in
Software
Engineering 20 20 20 80 -- -- -- 100


Course Objectives

Sr.No The course aims:
1 To familiarize students with advance topics in software engineering
2 Understand limitations and advantages of process models
3 Familiarize with agile development
4 Know importance of process improvement
5 Understand software quality
6 Understand software engineering principles


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 process models L2
2 Apply agile development L3
3 Analyze requirements for complex projects L4
4 Create architectural design L6
5 Evaluate quality of software L5
6 Understand importance of process improvement L2

Page 31

U
DETAILED SYLLABUS:

Sr.
No. Module Detailed content Hours CO-PO
Mapping
Prerequisite: Introduction – Basic knowledge of software
engineering principles, Programming skills,
Proficiency in any programming language.
02
I Process Models Generic process Model, Prescriptive process model,
Specialized process model.
Self-learning topics: Personal and Team Process
Models
05 CO1
II Agile development What is agile process, Extreme programming, ASD,
Scrum, DSDM, Crystel FDD, LSD, AM, AUP
Self-learning topics: Extreme Programming (XP),
Scrum
4 CO2
II
I Principles that
guide practice
and
Understanding
requirements Core principles, principles thar guide framework
activities, Requirements engineering, establishing
groundwork, eliciting requirements, building
requirements model, negotiating requirements,
Validating requirements.
Self-learning topics: Prioritizing requirements (Kano
diagram) - real life application case study.
4 CO3
IV Architectural
Design Software architecture, Architectural genres,
Architectural styles, Architectural design, Design
patterns, Pattern based software design,
Architectural patterns, User interface design
patterns.
Self-learning topics: Software Architecture Design
Tools
8 CO4
V Quality
Management Quality concepts, Review techniques, Software
quality assurance, testing strategies, Formal modeling,
and verification, product metrics.
Self-learning topics: Software Testing real life case
study using tools like JIRA
8 CO5
VI
Software process
improvement
What is SPI, The SPI process, CMMI, SPI
frameworks, SPI ROI, SPI trends, cleanroom
software engineering .
Self-learning topics: Software Process Improvement
and Capability Determination (SPICE)
8 CO6

Page 32

U Textbook
1. Software Engineering, A Practitioner’s Approach, Seventh Edition, Roger s. Pressman

Reference Book.
1. An integrated approach to Software Engineering, Pankaj Jalote
2. Software Engineering, Tenth Edition, Ian Sommerville

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% s yllabus should
be covered inquestionpapersofendsemesterexamination.

Page 33

U CourseCode Course
Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
ME-ITPE 1022
Adhoc
Networks 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
ME-ITPE 1022
Adhoc
Networks 20 20 20 80 -- -- -- 100


Course Objectives

Sr.No The course aims:
1 Understand the basic concepts of ad -hoc networks
2 Explain the MAC Protocols.
3 Be familiar with ad -hoc routing protocol .
4 Gain knowledge of different multicast routing in ad -hoc network
5 Learn the Transport layer – security protocols
6 Be aware of the applications and Recent Developments in Ad Hoc Networks


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 the basic concepts of ad -hoc networks. L1
2 Classify and Explain the MAC Protocols. L2
3 Classify and Explain the ad -hoc routing protocols L2
4 Describe the different multicast routing in ad -hoc network L2
5 Describe the Transport layer – security protocols L2
6 List and Explain applications and Recent Developments in Ad Hoc
Networks L4

DETAILED SYLLABUS:

Sr.
No. Module Detail C ontent Hours CO
Mapping
Prerequisite: Introduction – Fundamentals of Wireless
Communication Technology – The
Electromagnetic Spectrum –Radio
Propagation Mechanisms. 2

Page 34

U I Introduction Wireless Network. Characteristics of the
Wireless channel. Cellular and Ad -Hoc
Wireless Networks, Applications of Ad -
HocWireless Networks/MANET/Wireless
Sensor Network/VANET.Wireless
Internet Challenges for Wireless Sensor
Networks, Enabling Technologies for
Wireless Sensor Networks. Mobility,
Hidden and Exposed terminal Problems,
Characteristics of an Ideal Routing
Protocol for Ad -Hoc Wireless Networks
Self Study Topic: Read recent
articles on top wireless technology
trends, 5G 7 CO1
II Medium
access
protocols MAC Protocols: design issues, goals and
classification. Contention based
protocols - with reservation, scheduling
algorithms, protocols using directional
antennas. Multichannel MAC Protocol,
Multichannel CSMA MAC Protocol,
Power Control MAC Protocol for Ad
Hoc Networks IEEE standards: 802.11a,
802.11b, 802.11g, 802.11p, 802.15.
HIPER LAN
Self Study Topic: Wo rk on the
implementation and evaluation of the
MAC protocol standards using a
WSM simulation tool 8 CO2
III Ad hoc
routing
protocols Introduction : Issues in Designing a
Routing Protocol for Ad Hoc Wireless
Networks , Classifications of Routing
Protocols : Table –Driven Routing Protocols
– Destination Sequenced Distance Vector
(DSDV) , Wireless Routing Protocol
(WRP) , Cluster Switch Gateway Routing
(CSGR) , Source –Initiated On –Demand
Approaches , Ad hoc On – Demand
Distance Vector Routing (AODV) ,
Dynamic Sourc e Routing (DSR) ,
Temporally Ordered Routing Algorithm
(TORA) ,Signal Stability Routing (SSR) –
Location –Aided Routing (LAR) – Power –
Aware Routing (PAR) – Zone Routing
Protocol (ZRP).
Self Study Topic: Work on the
implementation and evaluation of the
Ad hoc ro uting protocols standards
using a WSM simulation tool s. 8 CO3

Page 35

U IV Multicast
routing in
ad-hoc
networks Introduction – Issues in Designing a
Multicast Routing Protocol ––
Classification of Multicast Routing
Protocols – Tree–Based Multicast
Routing Protocols – Mesh –Based
Multicast Routing Energy –Efficient
Multicast Routing Protocol
Self Study Topic: Work on the
implementation and evaluation of
the Multicast routing in ad -hoc
networks using a WSM simulation
tool
5




CO4
V Transport
layer –
security
protocols Introduction – Issues in Designing a
Transport Layer Protocol for Ad hoc
Wireless Networks – Design Goals of a
Transport Layer Protocol for Ad hoc
Wireless Networks –Classification of
Transport Layer Solutions – TCP over
Ad hoc Wireless Networks, Security in
Ad-hoc Wireless Networks
Self Study Topic:Work on the
implementation and evaluation of the
Multicast routing in ad -hoc networks
using a WSM simulation tool
5




CO5
VI Applicatio
ns and
Recent
Developm
ents in Ad
Hoc
Networks



Applications and
Opportunities:Academic Environment
Applications , Defense Applications ,
Industrial Environment Applications ,
Healthcare Applications , Search and
Rescue Applications , Vehicular Ad
Hoc Networks
Highlights of the Most Recent
Developments in th e Field
Self Study Topic: Read recent articles
on Top wireless technology
applications and developments. 4






CO6
Text book
1. S. Sarkar, T. Basavraju and C. Puttamdappa, “Ad hoc mobile wireless networks principles,
protocols and applications” , second edition, CRC Press, 2016.
2. Al-Sakib Khan Pathan, Muhammad Mostafa Monowar, Zubair Md. Fadlullah, “Building Next -
Generation Converged Networks: Theory and Practice, CRC Press, 2013.
3. Stefano Basagni, Marco Conti, Silvia Giordano, Ivan Stojmenovic, “Mobile Ad Hoc
Networking: The Cutting Edge Directions”, John Wiley 2013.
4. Feng Zhao & Leonidas J. Guibas, “Wireless Sensor Networks - An Information Processing
Approach", Elsevier, 2007

Page 36

U References
1. C. K. Toh, “Ad Hoc Mobile Wireless Networks Protocols and Systems”, Prentice Hall, PTR,
2001.
2. Charles E. Perkins, “Ad Hoc Networking”, Addison Wesley, 2000
3. C. Siva Ram Murthy and B. S. Manoj, “Ad Hoc Wireless Networks Architectures and Protocols”,
Prentice Hall, PTR, 2004
4. Holger Karl & Andreas Willig, " Protocols And Architectures for Wireless Sensor Networks" ,
John Wiley, 2005

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblem sorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 37

U Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITPE1 023
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
ME-
ITPE 1023
Storage
Area
Network 20 20 20 80 -- -- -- 100


Course Objectives

Sr.No The course aims:
1 Understand and analyze the basics of storage network, storage technologies and various storage
architectures.
2 Define and understand virtualization with respect to storage network.
3 Understand SAN Management and its various aspects.
4 Describe disaster recovery for storage network and understand strategies, parameters and Quality of
Service for Business Continuity in storage infrastructure.
5 Understand and analyze security aspects for storage area network.
6 Be aware of the applications and Recent Developments in Ad Hoc Networks


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 storage technologies and storage architectures. L1
2 Describe and apply virtualization in storage network. L1
3 Apply SAN Management with its various parameters . L3
4 Understand and apply disaster recovery and Business Continuity in storage
network. L2
5 Understand and apply storage security and its importance. L2
6 Apply various storage network concepts like Implementation, SAN L3

Page 38

U Management , Virtualization, Disaster Recovery and S ecurity to design
storage area network for an organization.


DETAILED SYLLABUS :
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite
Basics of Networking and storage devices,
Local File systems, Network File systems
and file servers, Shared Disk File systems,
Direct attached storage (DAS) 2 --
I Need for Storage
Network Basics of Storage N etwork :- Intelligent
Storage Systems (ISS), Data protection
(RAID implementation methods).
RAID arrays ,RAID technologies, RAID
levels, RAID impact on disk
performance & RAID comparison,
SCSI, SAN: FC SAN FC Protocol Stack,
IP Storage, Infiniband, Virtual Interfaces,
Comparison of NAS, FC SAN and iSCSI
SAN.
Self-learning Topics:
Limitations of tradition al server centric
architecture, Storage centric architecture
and its advantages. Netw ork Attached
Storage (N AS)


09
CO1
II Storage
Virtualization
Definit ion, Storage virtualization on b lock
and file level , Storage virtualization on
various levels of Storage network,
Symmetric and Asymmetric Virtualization.
Basics of Software Defined Storage and
it’s types
Self-learning Topics: VSAN 06 CO2
III Managing SAN Storage Management tasks, What Gets
Managed in SAN? Zoning, Virtualization:
Allocating Capacity rather than Disk, SAN
Management and Quality of online storage
device: Storage capacity, Data availability
and I/O performance, SAN Management
and Asset Utiliz ation,
Self-learning Topics: Storage planning
and capacity planning 05 CO3
IV Business
Continuity Strategies of Business Continuity: High
availability, Disaster Recovery, Continuous
business operation
Parameters of Business Continuity:
Availability, characteristics of Availability
(MTBF,MTTR and MTTF), characteristics 06 CO4

Page 39

U of failure (RTO and RPO), Network
Recovery Objective (NRO)
Quality of Service for Business
Continuity : Service level Agreements
(SLAs),High availability versus disaster
recovery, The seven -Tier Model, Tier 0 to
Tier 7
Self-learning Topics: General
Conditions, BC Terminology
V Storage Security Overview of Storage Security : Define
storage security, Storage security
framework: Security attributes
(Confidentiality, Integrity, Availability,
Accountability),
Security Elements: Assets(Information,
Hardware, Software, Network
Infrastructure), Threats, Vulnerabilities
Securit y Controls: Technical (
implemented in hardware, software and
firmware), Non -Technical:
Administrative(Policies, Standards),
FC SAN security, Basic SAN Security
Mechanisms, Securing Switch Ports
Self-learning Topics: NAS security 06 CO5
VI Designing
Storage Area
Network A case study to design a storage area
network for an organization considering
the following guidelines:
SAN Implementation, SAN Management ,
SAN Virtualization, SAN Disaster
Recovery and S ecurity
Self-learning Topics:Study th e Storage
Area Network Design of your
college/industry campus. 05 CO6




Text Books:
1. Ulf Troppens, Rainer Erkens, Wolfgang Muller -Friedt, Rainer Wolafka, Nils Haustein, “Storage Networks
Explained: Basics and Application of Fibre Channel SAN, NAS, ,iSCSI, Infiniband and FCoE”, Second
Edition, Wiley
2. Richard Barker and Paul Massiglia, “ Storage Area Network Essentials A Complete Guide to
Understanding and Implementing SANs”, Wiley.
3. EMC Education Services, “Information Storage and Management,” Second Edition, Wiley

4. Martin Hosken, "VMware Software -Defined Storage: A Design Guide to the Policy -Driven, Software -
Defined Storage Era"


References:
1.Vaishali D. Khairnar and NilimaM.Dongre ," Storage Network Management and Retrieval", Wiley
2. Robert Spalding, “ Storage Networks: The Complete Reference ”, McGraw Hill Education

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U 3. W. Curtis Preston, “ Using SANs and NAS ”, O‟Reilly


Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcoursepr oject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 41

U

Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-
ITPE 1024 ICT for
Social cause 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
ME-
ITPE 1024
ICT for Social
cause 20 20 20 80 -- -- -- 100



Course Objectives

Sr.No The course aims:
1
To appreciate various theoretical and disciplinary perspectives towards developing ICT system for
development of society .
2
To illustrate different ways by which information can be communicated.
3 To demonstrate an understanding for acquiring data securely for developing an ICT system.
4
To illustrate data storage techniques and formulate knowledge from the raw data.
5
To formulate policies and strategies for ICT system.
6
To design various application using ICT .


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
To identify opportunities and challenges for developing ICT systems. L1
2
To identify and access the ways by which information can be communicated. L1

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U 3
To identify methods of capturing data securely for developing an ICT system. L1
4
To store and analyze the data captured and generate knowledge from the raw
data. L4
5
To devise policies and strategies for ICT system. L4
6
To design various application using ICT , L6

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Introduction to ICT
2
I Introduction and
Basics of ICT Review of ICT history and growth,
importance of ICT in societal
developmentidentifying opportunities
for using ICT,
learning from failures Drivers and
barriers for ICT development
ICT in developing countries –
opportunities for developments and
challengesCreating an ICT – handling
text, data and media .
Self-learning Topics : Application of
ICT
4 CO1
II
Communication
Techniques in
ICT Radio and TV Techniques,
Mobile Techniques – CDMA, Mobile
wireless WiMAX, Advanced wireless
technologies, BluetoothSatellite
Techniques – architecture AND working
principles GPS/GPRS Cloud computing
–Introduction, cloud services, Cloud
service providers,
collaborative techniques like sharing
ideas through blogs, forums, online
communities etcsafe transmission of
data
Self-learning Topics :Study different
ICT t echniques. 8 CO2

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U III
Data acquisition
in ICT Recognition systems RFID,OMR
Location recognitionData acquisition
process for MEMS devicesSensors –
Programming, communication with
cloud.
Acquiring data from internet and social
media.Formation of social groups and
interaction analysis Facebook, Twitter,
Blogs, Forums, mailing lists
etccontrolling access to confidential
information

Self-learning Topics : Case study on
data acquisition in ICT 7 CO3
IV
Data and
Knowledge
Management in
ICT Data storage and management
content management system
identity management
Knowledge elicitationKnowledge
representation and visualization
techniquesKnowledge Engineering
MethodologyAuditing knowledge
managementData storage and disposal
of dataLinking knowledge management
to business performance
Self-learning Topics : case study on
Data and Knowledge Management in
ICT 7 CO4
V
Defining policies
for administering
ICT ICT policies and e -Strategies,
approach to ICT policy formulation and
e-Strategy development,
e-Readiness assessment,
identifying priority areas and developing
action plans.
National Policy on ICT in India.
Self-learning Topics : study ICT
policy. 6 CO5
VI
ICT applications Study of ICT applications in various
domains such as Agriculture,
Healthcare,Education,social
studies,Finance,Law,life science.
Self-learning Topics : Study of ICT
applicationsin different area. 5 CO6

Text Books:
1. Lechman, E. (2015). ICT Diffusion in Developing Countries: Towards a New Concept of Technological
Takeoff. Germany: Springer International Publishing.,

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U 2. Affordability Issues Surrounding the Use of ICT for Development and Poverty Reduction. (2018).
United States: IGI Global.
3. Koh, S. C. L., Maguire, S. (2009). Information and Communication Technologies Management in
Turbulent Business Environments. United Kingdom: Information Science Reference.,
4. The Development Dimension ICTs for Development: Improving Policy Coherence. (2010). Ukraine:
OECD Publishing.,
5. Gorica, K., Kordha Tolica, E., Sevrani, K. (2015). Information Society Development Through ICT
Market Strategies: Albania Versus Other Developing Countries. Germ any: Springer International
Publishing .
6. ICT Futures :Delivering Pervasive Realtime And Secure Services Edited By Paul Warren , John
Davies, David Brown , Wiley Publication
7. ICT Policy Formulation and e -Strategy Development Strategy Development - A Comprehensive
Guidebook by Richard Labelle, Asia -Pacific Development Information Programme
Online References:
1. BLI-224: ICT Fundamentals - https://onlinecourses.swayam2.ac.in/nou22_lb08/preview
Assessment:
Internal Assessment Test :

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 45

U

Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ME-ITL101 Program Lab-I -- 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
ME-
ITL101 Program Lab-I -- -- -- -- 25 25 50
Lab Objectives:

Sr. No Lab Objectives
1 To understand the concept of maths in data science
2 To understand the concept of ML algorithms
3 To understand the concept of data visualization
4 To develop and deploy smart contracts on local Blockchain
5 To deploy smart contracts on Ethereum test network.
6 To develop and publish smart contracts crypto currency
Lab Outcomes:
Sr.
No Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
1 Understand and apply the concept of maths in Data Science L1,L2,L3
2 Understand and apply the concept of ML algorithms L1,L2,L3
3 Understand and apply the concept of data visualization L1,L2,L3
4 Understand and apply the concept of smart contracts on local Blockchain L1,L2,L3
5 Understand deploy and publish smart contracts on Ethereum test network L1,L2,L3,L4
6 Understand develop and pyblish smart contracts L6

Prerequisite: Computer Networks.

DETAILED SYLLABUS:

Page 46

U Sr.
No. Module Detailed Content Hours LO
Mapping
I Mathematics for DS
Explore Pandas and Numpy
libraries of Python . 05 LO1
II Machine Learning
Algorithms Learning with Regression: Linear
Regression, Logistic Regression.
Learning with Trees: Bayes
Classification, Decision Trees,
Random Forest.
04 LO2
III Data Visualization Data Visualization Options :
Interactive graphics, Plotting:
Scatter Plots, Bar Plots, choosing
right plots, 3D visualization
04 LO3
IV Local Blockchain Introduction to Truffle, establishing
local Blockchain using Truffle .
05 LO4
V Smart Contracts Solidity programming language,
chain code (Java/JavaScript/Go),
deployment on Truffle local
Blockchain 04 LO4,LO5
VI Deployment and
publishing smart
contracts on
Ethereum test
network Ethereum Test networks
(Ropsten/Gorelli/Rinkeby),
deployment on test networks,
Web3.js/Web3.py for interaction with
Ethereum smart contract
04 LO6

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. Sinam Ozdemir, “Principles of Data Science”, Packt Publication,2016.
5. Davy Cielen, Arno D.B. Meysman, Mohamed Ali, “Introducing Data Science”, 2016
6. Ethem Alpaydın, “Introduction to Machine Learning”, MIT Press
7. Dan Toomey, “R for Data Science”, Packt Publication,2014

References:
1. Tom M.Mitchell, “Machine Learning”, McGraw Hill
2. Joel Grus. “Data Science from Scratch. First Principles With Python. ” O’Reilly Media, 2015.
3. Jake Vander Plas, “Python Data Science Handbook”, O’Reilly publication
4. Frank Kane, “Hands -On Data Science and Python Machine Learning”, P ackt Publication
5. Armando Fandango, “Python Data Analysis”, Second Editi on, Packt publication.
6. Alberto Boschetti, Luca Massaron, “Python Data Science Essentials S econd Edition”, Packt Publication

Page 47

U Online References:
1. https://onlinecourses.nptel.ac.in/noc22_cs32/preview
2. https://www.coursera.org/specializations/jhu -data-science
3. https://www.coursera.org/learn/machine -learning
4. https://home.csulb.edu/~jchang9/files/jonathan_guzman_honors_thesis.pdf





Term Work:

Term Work shall consist of at least 10 practical based on the above list. Also Term Wor k Journal must include
Assignement as mentioned in above syllabus.

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

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

Page 48

U Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ME-ITSBL1 01 DeVops & Adv-
DeVops Lab
(SBL -I) -- 4 -- -- 2 -- 02

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
ME-
ITSBL1 01 DeVops & Adv -
DeVops Lab
(SBL -I) -- -- -- -- 50 50 100
Lab Objectives:

Sr.
No Lab Objectives
1 To understand DevOps practices which aims to simplify Software Development Life Cycle
2 To be aware of different Version Control tools like GIT, CVS or Mercurial
3 To Integrate and deploy tools like Jenkins and Maven, which is used to build, test and deploy
applications in DevOps environment
4 To understand DevOps practices and cloud native environments to achieve continuous
software delivery pipelines and automated operations that address the gap between IT
resources and growing cloud complexity.
5 To Use Kubernetes services to structure N -tier applications.
6 To understand that security and speed in software development are not inversely -related
objectives Internalizing the contribution of tools and automation in DevSecOps
Lab Outcomes:
Sr.
No Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
1 To understand the fundamentals of DevOps engineering and be fully
proficient with DevOps terminologies, concepts, benefits, and
deployment options to meet your business requirements L1,L2
2 To obtain complete knowledge of the “version control system” to
effectively track changes augmented with Git and GitHub L1,L2
3 To understand the importance of Jenkins to Build and deploy Software
Applications on server environment L1,L2
4 To understand the fundamentals of Cloud Computing and be fully
proficient with Cloud based DevOps solution deployment options to
meet your business requirements L1,L2
5 To deploy single and multiple container applications and manage
application deployments with rollouts in Kubernetes L1,L2,L3

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U 6 To identify and remediate application vulnerabilities earlier and help
integrate security in the development process using SAST Techniques. L1,L2,L3

Prerequisite: Operating System, Linux Administration, Java /Web Application Programming, and Software
Engineering.
.
DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours LO Mapping
I Introduction to
Devops Understanding of the process to be followed during
the development of an application, from the
inception of an idea to its final deployment. Learn
about the concept of DevOps and the practices and
principles followed to implement it in any
company’s softwa re development life cycle.
Learn about the phases of Software Lifecycle. Get
familiar with the concept of Minimum Viable
Product (MVP) & Cross -functional Teams.
Understand why DevOps evolved as a prominent
culture in most of the modern -day startups to
achieve agility in the software development process
Self-Learning Topics: Scrum, Kanban, Agile 04 LO1
II Git In this module you will learn:
 GIT Installation, Version Control, Working
with remote repository
 GIT Cheat sheet
 Create and fork repositories in GitHub
 Apply branching, merging and rebasing
concepts.
 Implement different Git workflow strategies
in real -time scenarios
 Understand Git operations in IDE

Self-Learning Topics: AWS Codecommit,
Mercurial, Subversion, Bitbucket, CVS 04 LO1, LO2
III Continuous
Integration using
Jenkins In this module, you will know how to perform
Continuous Integration using Jenkins by building
and automating test cases using Maven / Gradle /
Ant.
 Introduction to Jenkins (With Architecture)
 Introduction to Maven / Gr adle / Ant.
 Jenkins Management Adding a slave node
to Jenkins
 Build the pipeline of jobs using Maven /
Gradle / Ant in Jenkins, create a pipeline
script to deploy an application over the
tomcat server 04 LO1, LO3

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U Self-Learning Topics: Travis CI, Bamboo,
GitLab, AWS CodePipeline
IV DevOps on Cloud Learn about various cloud services and service
providers, also get the brief idea of how to
implement DevOps over Cloud Platforms.
 Introduction to high availability architecture
and auto -scaling
 Set up the DevOps infrastructure on the
cloud
 Work and set up IDE on Cloud9
 Deploy projects on AWS using Code
Build, CodeDeploy, and CodePipeline
Self-Learning Topics: AWS Codestar 06 LO4
V Kubernetes In this module, you will learn how Kubernetes
automates many of the manual processes
involved in deploying, managing, and scaling
containerized applications.
 Install and configure Kubernetes
 Spin Up a Kubernetes Cluster
 Check the Nodes of Your Kubernetes Cluster
 Installing kubectl to manage cluster and deploy
Your First Kubernetes Application
Self-Learning Topics:
 Using Services and Ingresses to Expose
Deployments
 Perform logging, monitoring, services, and
volumes in Kubernetes.
04 LO4,LO5
VI DevOps Security In this module, you will learn to identify and
remediate application vulnerabilities earlier and
help integrate security in the development
process using tools like SonarQube / Gitlab /
 Perform static analysis on application
source code and binaries.
 Spot potential vulnerabilities before
deployment
 Analysis of java / web -based project
 Jenkins SonarQube / Gitlab Integration
Self-Learning Topics: Snyk, OWASP ZAP, 04 LO6

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U Analysis Core Plugin
Text books
1. DevOps Bootcamp, Sybgen Learning
2. Karl Matthias & Sean P. Kane, Docker: Up and Running, O'Reilly Publication.
3. Len Bass,Ingo Weber,Liming Zhu,”DevOps, A Software Architects Perspective”, AddisonWesley -Pearson
Publication.
4. John Ferguson Smart,” Jenkins, The Definitive Guide”, O'Reilly Publication.
5. Mastering Puppet 5: Optimize enterprise -grade environment performance with Puppet, by Ryan Russell -
Yates Packt Publishing (September 29, 2018)
6. AWS Certified SysO ps Administrator Official Study Guide: Associate Exam by Stephen
Cole (Author), Gareth Digby (Author), Chris Fitch (Author), Steve Friedberg (Author), Shaun Qual
7. AWS Certified Solutions Architect Official Study Guide: Associate Exam by Joe Baron
8. Terraform: Up & Running - Writing Infrastructure as Code , Second Edition by Yevgeniy Brikman ,
O'Reilly
9. Kubernetes: Up and Running - Dive into the Future of Infrastructure, Second Editionby Brendan
Burns ,O'Reilly
10. Going Serverless with AWS Lambda: Leveraging the latest services from the AWS cloud by Ajay
Pherwani , Shroff/X -Team;
11. Learning Nagios, Packt Publishing.



References:
1. Sanjeev Sharma and Bernie Coyne,” DevOps for Dummies”, Wiley Publication
2. Httermann, Michael, “DevOps for Developers”, Apress Publication.
3. Joakim Verona, “Practical DevOps”, Pack publication
4. Puppet 5 Essentials - Third Edition: A fast -paced guide to automating your infrastructure by Martin
Alfke Packt Publishing; 3rd Revised edition (September 13, 2017)
5. Learning Aws - Second Edition: Design, build, and deploy responsive applications using AWS by Amit
Shah Aurobindo Sarkar
6. Mastering Aws Lambda by Yohan Wadia Udita Gupta

Guidelines for 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 t han 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 cover
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 students 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/ supervisor.

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U  Students shall convert the best solution into working model using various components of their domain
areas and demonstrate.
 The solutio n 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
developme nt within the students through the open source Mini Projects .
Guidelines for Assessment of Mini Project:
Term Work
 The review/ progress monitoring committee shall be constituted by head of departments of each
institute. The progress of mini project to be e valuated on continuous basis, minimum two reviews in
each semester.
 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.
 Distribution of Term work marks for both semesters shall be as below;
o Marks awarded by guide/ supervisor based on log book : 30
o Marks awarded by review committee : 10
o Quality of Project Report :05


Term Work:

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

Term Work Marks : 50 Marks (Total marks) = 45 Marks (Mini -project) + 5 Marks (Attendance)

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

Page 53

U Course Code Course Name Credits
IE1011 Product Life Cycle Management 03


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 techniques 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 wit h 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, N ew 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

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U 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 Proc ess, 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 question paper.Minimum 80% syllabus should be covered in question papers
of en d 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 mixe d 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 Ma nagement”, Springer, Dreamtech,
ISBN:3540257314
4. Michael Grieve, “Product Lifecycle Management: Driving the next generation of lean thinking”, Tata
McGraw Hill, 2006, ISBN:0070636265

Page 55

U Course Code Course Name Credits
IE1012 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 d ifferent 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, Weibull 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 56

U 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 sho uld 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 Wile y & 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 57

U Course Code Course Name Credits
IE1013 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 system s TransformBusiness
2. Identify the impact information systems have on anorganization
3. Describe IT infrastructure and its components and its currenttrends
4. Understand the principal tools and technologies for accessing information from databases to improve
busin ess 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 58

U 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.


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, Pr entice
Hall,2008

Page 59

U Course Code Course Name Credits
IE1014 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 60

U

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 designexamples
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 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. 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 61

University of Mumbai, B. E. (Information Technology), Rev 2016 220 Course Code Course Name Credits
IE1015 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, includin g strong duality and complementaryslackness.
2. Perform sensitivity analysis to determine the direction and magnitude of change 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 applications 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 T heorem, Dual
Simplex Method, Sensitivity Analysis Transportation Problem : Formulation, solution,
unbalanced Transportation problem. Finding basic feasible solutions – Northwest corner
rule, least cost method and Vogel’s approximation method. Optimality tes t: the stepping
stone method and MODImethod.
Assignment Problem : Introduction, Mathematical Formulation of the Problem,
Hungarian Method Algorithm, Processing of n Jobs Through Two Machines and m
Machines, Graphical Method of Two Jobs m Machines Problem R outing 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 62

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, Li mitations 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 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. 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 63

University of Mumbai, B. E. (Information Technology), Rev 2016 222 Course Code Course Name Credits
IE1016 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,
Registry Settings for Mobile Devi ces, 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 Policies and Measures in Mob ile
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 64

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 65

University of Mumbai, B. E. (Information Technology), Rev 2016 224 Course Code Course Name Credits
IE1017 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 and 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 disaster 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 66

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 a gencies 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 Dasgup ta, 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.
(Learners are expected to refer reports published at national and International level and updated
information available on authentic websites)

Page 67

University of Mumbai, B. E. (Information Technology), Rev 2016 226 Course Code Course Name Credits
IE1018 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 perf ormance 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 68

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 Four 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 andSons
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 Pres s
7. Handbook of Energy Audits, Albert Thumann, W. J. Younger, T. Niehus, CRCPress
8. www.energymanagertraining.com
9. www.bee -india.nic.in

Page 69

University of Mumbai, B. E. (Information Technology), Rev 2016 228 Course Code Course Name Credits
IE1019 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 programme
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
develop ment. 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; Sustainable ru ral development 07

Page 70

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 an d
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 i n 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, NewDelhi
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 71

University of Mumbai, B. E. (Information Technology), Rev 2016 230 9. How, E., Normative Ethics in Planning, Journal of Planning Literature, Vol.5, No.2, pp.1 23-150
10. Watson, V. Conflicting Rationalities: -- Implications for Planning Theory and Ethics, Planning Theory and
Practice, Vol. 4, No.4, pp.395 –407

Page 72

University of Mumbai, B. E. (Information Technology), Rev 2016 230


SemesterII

Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITC201
WEB X.0 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
ME-ITC201
WEB X.0
20 20 20 80 -- -- -- 100

Course Objectives:
Sr.No The course aims:
1 To understand the digital evolution of web technology.
2 To learn TypeScript and understand how to use it in web applications.
3 To learn the fundamentals of Node.js.
4 To make Node.js applications using the express framework.
5 To enable the use of AngularJS to create web applications that depend on the Model -View -
Controller Architecture.
6
To gain expertise in a leading document -oriented NoSQL database, designed for speed, scalability,
and developer agility using MongoDB and Mongoose.

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 related to web analytics and semantic
web. L1, L2
2 Understand how TypeScript can help you eliminate bugs in your code
and enable you to scale your code. L1, L2
3 Develop back -end applications using Node.js. L1,L2,L3
4 Construct web based Node.js applications using Express. L1,L2,L3
5 Understand AngularJs framework and build dynamic, responsive
single -page web applications. L1,L2,L3

Page 73

University of Mumbai, B. E. (Information Technology), Rev 2016 230 6 Apply MongoDB for frontend and backend connectivity using
Mongoose and REST API. L1, L2, L3


DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Introduction to HTML5,CSS3, Basics of
JavaScript 02 -
I Introduction to
WebX.0
Evolution of WebX.0; Web Analytics 2.0 :
Introduction to Web Analytics, Web
Analytics 2.0, Clickstream Analysis, Strategy
to choose your web analytics tool, Measuring
the success of a website; Web3.0 and
Semantic Web : Characteristics of Semantic
Web, Compon ents of Semantic Web,
Semantic Web Stack, N -Triples and Turtle,
Ontology, RDF and SPARQL
Self-learning Topics : Semantic Web Vs AI,
SPARQL Vs SQL.
04 CO1
II TypeScript Overview, TypeScript Internal Architecture,
TypeScript Environment Setup, TypeScript
Types, variables and operators, Decision
Making and loops, TypeScript Functions,
TypeScript Classes and Objects, TypeScript
Inheritance and Modules
Self-learning Topics : Javascript Vs
TypeScript
06 CO2
III Node.js
Introducing the Node.js -to-Angular Stack
(MEAN Stack), Environment setup for
Node.js , First app, Asynchronous
programming, Callback concept, Event loops,
REPL, NPM, Event emitter, Buffers, Streams,
Networking module, File system, Web
module.
Self-learni ng Topics: Node.js with
MongoDB. 06 CO3
IV Express Introduction to Express ,Installing
Express,Creating First Express
application,The application, request, and
response objects,Configuring
Routes,Understanding Middleware,cookies,
Session, Authentication
Self-learning Topics: ExpressJs Templates 06 CO4
V Introduction to
AngularJS
Overview of AngularJS, Need of AngularJS
in real websites, AngularJS modules,
AngularJS built -in directives, AngularJS
custom directives, AngularJS 06 CO5

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University of Mumbai, B. E. (Information Technology), Rev 2016 230 expressions,AngularJS Data Binding,
AngularJS filters, AngularJS controllers,
AngularJS scope, AngularJS dependency
injection, AngularJS Services, Form
Validation, Routing.
Self-learning Topics: MVC model, DOM
model.
VI MongoDB and
Building
REST API
using
MongoDB
MongoDB : Understanding MongoDB,
MongoDB Data Types, Administering User
Accounts, Configuring Access Control,
Adding the MongoDB Driver to Node.js,
Connecting to MongoDB from Node.js,
Accessing and Manipulating Databases,
Manipulating MongoDB Documents from
Node.js, Accessing MongoDB from Node.js,
Using Mongoose for Structured Schema and
Validation.
Mongoose: Installation and connecting to
MongoDB, understanding and extending
Mongoose Schema, Define custom model
methods and validation, Mongoose
Middleware and DBRef.
REST API : Examining the rules of REST
APIs, Evaluating API patterns, Handling
typical CRUD functions (Create, Read,
Update, Delete), Using Express and
Mongoose to interact with MongoDB, Testing
API endpoints.
Self-learning Topics : MongoDB vs SQL
Databases 09 CO6

Text Books:
1.Boris Cherny, “Programming TypeScript - Making Your Javascript Application Scale”, O’Reilly Media
Inc.
2. Amos Q. Haviv, “MEAN Web Development” , PACKT Publishing
3.Brad Dayley, Brendan Dayley, Caleb Dayley, “Node.js, MongoDB and Angular Web Development:The
definitive guide to using the MEAN stack to build web applications”, 2nd Edition, Addison -Wesley
Professional
5. Adam Bretz and Colin J. Ihrig, “Full Stack JavaScript Development with MEAN”, SitePoint.
4. Dr. Deven Shah, “Advanc ed Internet Programming”, StarEdu Solutions.
References:
1. Simon Holmes Clive Harber, “Getting MEAN with Mongo, Express, Angular, and Node”, Manning
Publications.
2. Yakov Fain and Anton Moiseev, “TypeScript Quickly”, Manning Publications.
Online Referenc es:
1.https://www.coursera.org
2. https://udemy.com
3. https://www.tutorialspoint.com/meanjs/meanjs_overview.htm

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University of Mumbai, B. E. (Information Technology), Rev 2016 230
Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorco urseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 76

University of Mumbai, B. E. (Information Technology), Rev 2016 230

Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITC202 Cloud
Computing
and Services 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practica
l Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
ME -ITC202 Cloud
Computing
and Services 20 20 20 80 -- -- -- 100


Course Objectives:
Sr.No The course aims:
1 To learn the perspective of cloud computing and virtualization
2 Tounderstand the idea behind mobile cloud computing
3 To determine the meaning of mobile offloading
4 To assess the concept of green cloud computing
5 To explore the resource allocation techniques and various business models
6 To analyze various cloud and mobile computing environments for real world application

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 concepts behind cloud computing and virtualization . L2
2 Apply the knowledge of mobile cloud computing to various applications L3
3 Determine the various techniques of loading in cloud computing applications. L4
4 Design applications to make the systems energy efficient. L6
5 Select the required cloud computing resources and develop a business model. L1,L2,L3
6 Apply various techniquesto develop various high ended mobile cloud computing
applications L3

Page 77

University of Mumbai, B. E. (Information Technology), Rev 2016 230 DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite
Cloud Computing models, Virtualization,
Primary and Secondary services offered by
the cloud. 02 --
I Introduction to
Cloud Computing
and virtualization Virtualization: Need for virtualization,
Features and types of virtualization,
Hypervisors and its types.

Cloud Computing : Introduction to Cloud
Computing, Layers and Types of Clouds,
Features of Cloud computing system , Cloud
Infrastructure Managemen t, Infrastructure as
a Service , Platform as a Service , software
as a service, Challenges and Risks,
Secondary services.
Self-learning Topics:
Case study on Service model
Dockers, OSGi (Application level
virtualization library) 06 CO1
II Mobile cloud
computing
Mobile cloud computing: Need for Mobile
cloud computing system, Definition,
Architecture, Challenges, Characteristics
and Benefits of Mobile cloud computing.
Mobile cloud computing service framework
Mobile cloud solutions, Mobile cloud
servic e models, Mobile Cloud computation,
Mobile Cloud storage, Mobile Cloud
security and privacy, Mobile Cloud
Computing context awareness, Mobile as a
service consumer, Mobile as a service
provider, Mobile as service broker.
Self-learning Topics:
Mobile cloud computing platforms and
software. 06 CO2
III Offloading in
Mobile Cloud
Computing

Definition of offloading, composition,
migration
Introduction to offloading , Offloading
Decision, Types of Offloading, Topologies
of Offloading, Offloading in Cloud
Computing and in Mobile Cloud Computing:
Similarities and Differences, Adaptive
Computation Offloading from Mobile
Devices, Cloud Path Sele ction for
Offloading, Mobile Data Offloading Using
Opportunistic Communication, Three -Tier
Architecture of Mobile Cloud Computing,
Requirements of Data Offloading,
Performance Analysis of Offloading
Techniques Multi -Cloud Offloading in 06 CO3

Page 78

University of Mumbai, B. E. (Information Technology), Rev 2016 230 Mobile Cloud computi ng environment,
Mobile cloud computing offloading models

Self-learning Topics:
Mobile cloud offloading framework:
clonecloud, Thinkair, MAUI, Cuckoo,
weblet
IV Green Mobile
Cloud Computing Introduction , Requirements and issues ,
Devices used, Computational offloading,
Resource management, Service
provisioning, Green location sensing,
Energy saving.

Self-learning Topics:
Measures taken by IT industries towards
green computing and challenges in adopting
green computing. 06 CO4
V Resource
allocation and
business model for
mobile cloud
computing Resource allocation in mobile cloud
computing: Simple, dynamic and adaptive
resource allocation models. Challenges and
issues in resource allocation, Techniques in
mobile cloud computing.
Mobile clou d computing business models:
Advantages, issues and applications.
Business Models for social mobile cloud

Self-learning Topics:
Business model requirements, cloud
computing business model 06 CO5
VI Applications of
Mobile cloud
computing Mobile cloud media computing applications:
Location identification, Human Tracking,
Mobile learning applications, Cloud
streaming applications, Vehicle monitoring
and Biometric applications.
Tips for creating cloud mobile applications,
Context aware mobil e computing system,
Self-learning Topics:
Cross cloud communication applications,
Elastic application models 07 CO6

Text Books:
1. Cloud Computing: Principles and Paradigms,Rajkumar Buyya , James Broberg,Andrzej M. Goscinski
2. Cloud computing by Kailesh Jayaswal,jagannath kallakurchi, donald j Houde
3.Mobile cloud computing : foundation and service model by Dijiang Huang and Huijun Wu
4. Mobile computing architecture, algorithm and application by Debashis De
References:
1. Cloud computing Bible by barrie Sosinsky.
2. Cloud computing by Dr Kumar Saurabh

Page 79

University of Mumbai, B. E. (Information Technology), Rev 2016 230

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbe compulsory class test (on minimum 02
Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks, out of
these any four questions to beattempted by students. Minimum 80% syllabus should be covered
inquestionpapersofendsemesterexamination.

Page 80

University of Mumbai, B. E. (Information Technology), Rev 2016 230
Course
Code Course
Name Theory Practical Tutorial Theory Pract ical/
Oral Tutorial Total
ME-
ITPE 2011 Web
Application
Security 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
ME-
ITPE 2011 Web
Application
Security 20 20 20 80 -- -- -- 100

Course Objectives:
Sr.No The course aims:
1 To reveal the underlying in web application.
2 To understand the browser security principles.
3 To understand web applications vulnerabilities.
4 To understand web application mitigations.
5 To identify and aid in fixing any security vulnerabilities during the web development process.
6 To understand the security principles in developing a reliable web application.

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 To understand the security principles in developing a reliable web application L2
2 Identify the various types of security issues in web browser. L3
3 Identify the various types of threats in developing a web application. L4
4 Identify the various types of mitigation measures of web applications. L6
5 Apply the security principles in developing a reliable web application. L1,L2,L3

Page 81

University of Mumbai, B. E. (Information Technology), Rev 2016 230 6 1. Use industry standard tools for web application security.
L3

Prerequisite: Introduction to Information & Network Security.


DETAILED SYLLABUS :
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Overview of Web Applications:
Introduction history of web applications
interface ad structure benefits and drawbacks of
web applications Web application Vs Cloud
application 2
I Web Application
Security
Fundamentals Security Fundamentals: Input Validation -
Attack Surface Reduction Rules of Thumb -
Classifying and Prioritizing Threads
Self-learning Topics:
Cookies, Access Control. 4 CO1
II
Browser Security
Principles Origin Policy - Exceptions to the Same -
Origin Policy - Cross -Site Scripting and
Cross -Site Request Forgery - Reflected XSS
- HTML Injection
Self-learning Topics: HTTPS, HTTP Proxies . 4 CO2
III Web Application
Vulnerabilities Understanding vulnerabilities in traditional
client server application and web
applications, client state manipulation,
cookie based attacks, SQL injection, cross
domain attack (XSS/XSRF/XSSI) http
header injection. SSL vulnerabilities and
testing - Proper encryption use in web
application - Session vulnerabilities and
testing - Cross -site request forgery
Self-learning Topics: SSH Tunneling
Cleaning traces ,Cleaning the event log
Advanced phishing attacks 8 CO3
IV Web Application
Mitigations HTTP request, HTTP response, rendering
and events , html image tags, image tag
security, issue, java script on error ,
Javascript timing , port scanning , remote
scripting , running remotecode, frame and
iframe , browser sandbox, policy goals, same
origin policy, libra ry import, domain
relaxation
Self-learning Topics: Nikto, OWASP ZAP . 7 CO4
V
Secure Website
Design Secure website design: Architecture and Design
Issues for Web Applications, Deployment
Considerations Input Validation, Authentication,
Authorization, Configuration Management, Sen -
sitive Data, Session Management, Cryptography,
Parameter Manipulation, Exc eption Manage -
ment, Auditing and Logging, Design Guidelines, 8 CO5

Page 82

University of Mumbai, B. E. (Information Technology), Rev 2016 230 Forms and validity, Technical implementation
Self-learning Topics: Wapiti , SQL Map
VI Cutting Edge
Web Application
Security Clickjacking - DNS rebinding - Flash
security - Java applet sec urity - Single -sign-
on solution and security - IPv6 impact on
web security
Self-learning Topics:
https://owasp.org/www -
community/Free_for_Open_Source_Applica
tion_Security_Tools 6 CO6
Text Books:
1. Sullivan, Bryan, and Vincent Liu. Web Application Security, A Beginner’s Guide. McGraw Hill Profe
ssional, 2011.
2. Stuttard, Dafydd, and Marcus Pinto. The Web Application Hacker’s Handbook: Finding and Exploiting
Security Flaws. John Wiley Sons, 2011

References:
1. OReilly Web Security Privacy and Comme rce 2nd Edition 2011
2. Professional Pen Testing for Web application, Andres andreu, wrox press
3. Carlos Serrao, Vicente Aguilera, Fabio Cerullo, “Web Application Security”
Springer; 1st Edition.

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquesti ons to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 83

University of Mumbai, B. E. (Information Technology), Rev 2016 230


Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITPE 2012 Machine and
Deep
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
ME-ITPE 2012 Machine and
Deep
Learning 20 20 20 80 -- -- -- 100

Course Objectives:
Sr.No The course aims:
1 To introduce the basics of machine learning and foster their abilities in applying different machine
learning algorithms to real world problems.
2 To introduce the concept of Bay esian and computational learning.
3 To define and apply metrics to measure the performance of various learning algorithms.
4 To become familiar with Deep Learning Concepts and Architectures.
5 To become familiar with various deep learning networks
6 To explore trends and applications of Deep learning.

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, choose and apply different machine learning algorithms to real world
problems. L2

Page 84

University of Mumbai, B. E. (Information Technology), Rev 2016 230 2 Apply Bayesian and computational learning in deriving effective learning rules. L3
3 Evaluate performance of learning algorithms.
L4
4 Understand the basics of Deep Learning L6
5 Describe the architecture of various deep networks L1,L2,L3
6 Identify various trends and applications of Deep Learning
L3

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Data Mining , Linear Algebra, Calculus and
Basics of Probability 02 -
I Introduction
to Machine
Learning Introduction to Machine Learning, Machine
learning types, Supervised Learning :
Linear Regression(LR) and Logistic
Regression (LogR), Support Vector
Machine(SVM), Decision tree ,
Unsupervised Learning : k-means and
hierarchical clustering, choosing the
number of clusters ; Methods of
Dimensionality reduction : subset selection,
Principal component analysis (PCA),
Feature embedding
Self-learning Topics: Implementation of
the above algorithm, Dimensionality
Reduction using Feature extraction, Feature
selection 5 CO1

Page 85

University of Mumbai, B. E. (Information Technology), Rev 2016 230 II Bayesian and
computation
learning: Bayesian Theorem, Concept learning,
Maximum likelihood and least square error
hypothesis , maximum likelihood
hypothesis for predicting probability,
minimum length description, Bayesian
optimal classifier,Gibbs Algorithm,NB
classifier, Learning to classify text, Bayesian
Belief Ne twork(BBN),
EM algorithm, Probably Learning an
Approximately Correct Hypothesis, sample
complexity for finite and infinite hypothesis
space, The mistake bounds model of
learning . Self-learning Topics:
Implementation of NB classifier 5 CO2
III Advanced
ML
Classification
Techniques
and Model
Evaluation Metrics for Classification: Model
evaluation, Holdout Method and Random
Sub sampling, Cross -Validation, Bootstrap,
Model Selection Using Statistical Tests of
Significance, Comparing Classifiers Based
on Cost –Benefit and ROC Curves.
Ensemble Classifiers : Introduction to
Ensemble Methods, Bagging, Boosting, XG
boost, Ada boost, Random forests,
Improving classification accuracy of Class -
Imbalanced Data,Model performance
improvement using Hyper parameter tuning.
Self-learning Topics: Improving the
performance of classifiers 8 CO3
IV Introduction
to Deep
Learning
Introduction to Deep Learning, Machine
Learning Vs Deep Learning, Working of
Deep Learning, Perceptrons, Artificial
Neural Network (ANN), Architecture of
Neural network ,Problems and use cases(
examples), single layer and Multilayer
networks, back propagation and
regularization ,batch normalization.
Self-learning Topics: Issues in ANN 6 CO3, CO4

Page 86

University of Mumbai, B. E. (Information Technology), Rev 2016 230 V Deep
Networks Introduction to Convolution Neural
Network (CNN), Components of CNN
,Architecture of CNN, Properti es of CNN,
Applications of CNN; Recurrent Neural
Network (RNN): Introduction to RNN,
Simple RNN, LSTM Implementation, Deep
RNN;
Autoencoder : Introduction,Architecture,
Applications, properties and
hyperparameters, Types of
autoencoder :Denoising autoencoder , Sparse
Autoencoder, Contractive Autoencoder.
Self-learning Topics: Restricted
Boltzmann Machine (RBM) 6 CO5
VI Trends and
applications
in Deep
Learning Generative adversarial networks (GAN);
Transfer learning; Deep Learning for text
and voice(Natural Language Processing);
Deep Learning for image and
video(Computer vision)
Self-learning Topics: ImageNet Large
Scale Visual Recognition Challenge
(ILSVRC). 7 CO6
Text Books:
1. Ethem Alpaydin -Introduction to Machine Learning -The MIT Press:
2. Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville published by MIT Press
3. Anuradha Srinivasaraghavan, Vincy Joseph, “Machine Learning”, Wiley.
4. Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) by
Jiawei Han, Micheline Kamber and Jian Pei
References:
1..Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning by
Chris Albon . O'Reilly Media; 1st edition
2.Deep learning with Python, Second Edition by Francois Chollet ,Manning Publications
3. Hands –On Machine Learning with Scikit –Learn and TensorFlow by Aurelien Geron ,O'Reilly Media
4. Tom M. Mitchell. Machine Learning, McGraw -Hill Education
Online References:

Page 87

University of Mumbai, B. E. (Information Technology), Rev 2016 230 1.https://nptel.ac.in/courses/106106139
2.https://machinelearningmastery.com/practical -machine -learning -problems/
1.https://www.deeplearningbook.org/
2.https://ww w.tensorflow.org/tutorials/images/transfer_learning
Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcoursep roject.

EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexami nation.

Page 88

University of Mumbai, B. E. (Information Technology), Rev 2016 230





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
ME-ITPE 2013
ARVR
20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand the concepts of Augmented Reality , VR and related technologies.
2 To understand the AR tracking system and use of computer vision in AR /VR/MR.
3 To describe the technology for multimodal user interaction and authoring in AR.
4 To use different AR toolkits and apply them to develop AR applications.
5 To demonstrate AR Applications using Mobile AR Toolkits and SDKs.
6 To understand the use of AR/MR in interdisciplinary immersive applications.

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 , VR and Mixed Reality
Technologies. L1, L2
2 Apply concepts of Computer Vision for tracking in AR , VR and MR
Systems. L3
3 Model different interfaces and authoring in AR/MR. L3
4 Design AR/MR applications using open source platforms and toolkits. L6
5 Design Mobil e based AR Applications. L6
6 Apply insights of AR/MR in different applications. L3






Course Code Course Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITPE 2013
ARVR 03 -- -- 03 -- -- 04

Page 89

University of Mumbai, B. E. (Information Technology), Rev 2016 230
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 ,
Virtual 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 . What is VR, Modern VR
Experiences. Bird’s Eye View, Geometry Virtual
Words. Light and optics.

Self-Learning Topics : How AR /VR/MR are related to
Ubiquitous Computing, Multidimensional Systems. 05 CO1
II Trac king and
Computer Vision for
AR, VR and MR Multimodal Displ ays; Visual Perception; Spatial
Display Model; Visual Displays; Tracking, Calibration
and Registration; Coordinate Systems; Characteristics
of Tracking Technology; Stationary Tracking Systems;
Mobile Sensors; Optical Tracking; Sensor Fusion;
Marker Trackin g; Multiple Camera Infrared Tracking;
Natural Feature Tracking by Detection; Incremental
Tracking; Simultaneous Localization and Tracking;
Outdoor Tracking . Visual Perception, Visual
Rendering, Motion in real and virtual worlds.

Self-Learning Topics : Ind oor Tracking, Full Body
Tracking 07 CO2
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
Solutions, Plug -in Approaches, Web Technology

Self-Learning T opics : Case Study on Object
Annotation in Real Time, Avatar Modeling. 06 CO3
IV Software
Architecture in AR
and AR
Development
Toolkits AR Application Requirements, Software Engineering
Requirements, Distributed Object Systems, Data Flow,
Scene Graphs; Developer Support: Parameter
Configuration, Declarative Scripting, Procedural
Scripting, Mixed Language Programming, Runtime
Reconfiguration, Choosing an AR Platforms and
Toolkits; AR Non -programming Frameworks, AR
Programming Frameworks, Programming AR us ing
ARToolkit.

Self-Learning Topics : Commercial AR Frameworks,
AR Related Markup Languages 06 CO4

Page 90

University of Mumbai, B. E. (Information Technology), Rev 2016 230 V Mobile AR Types of Mobile Apps, AR Browsers for Smartphones,
Point of Interests (POI) in Mobile AR, POI Authoring
and Publishing Tools, AR Applications fo r Android,
AR Games for Android,Mobile AR Toolkits and SDKs,
Developing Mobile AR Applications, AR Application
Development for Android Smartphone

Self-Learning Topics : AR Applications for iOS, AR
Games for iOS, AR Application Development for iOS
Smartphon e 08 CO5
VI Applications of
AR/MR and Human
Factors, Legal and
Social
Considerations Applications of AR/MR in: Edutainment, Medical,
Military, Production and Manufacturing, Navigation,
Astronomical Observation, E -commerce; What are
Human Factors, Physical Side Effects, Visual Side
Effects, Legal Considerations, Moral and Ethical
Considerations.
Self-Learning Topics : Applications of AR/MR in Civil
Construction and Architecture, Collaboration,
Information Control and Big Data Visualization 05 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, “Understandi ng Augmented Reality – Concepts and Applications”, Morgan Kaufmann,
Elsevier, 2013 Edition
4. Steven M. LaVelle,” Virtual Reality”, Cambridge University press, 2019

References :
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 Applica tion Development”,
PACKT Publishing, 2013 Edition.
Online Resources:
Sr. No. Website Name
1. www.nptel.ac.in
2. www.coursera.org

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.
EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by student s. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 91

University of Mumbai, B. E. (Information Technology), Rev 2016 230
Course Code Course Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-
ITPE 2014 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
ME-
ITPE 2014 High Performance
Computing 20 20 20 80 -- -- -- 100


Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To learn fundamental concepts of parallel processing
2 To learn utilization of high performance computing resources using programming frameworks
3 To learn usage of modern processor technology as a high performance computing platform
4 To learn and appreciate core design issues in parallel computing
5 To study application of high performance computing to practical problems
6 To understand factors limiting performance of high performance computing systems

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 Memorize and Understand classes of parallel computer architectures and GPU
architecture L1, L2
2 Understand standardized, multi -platform communication methods for parallel
programming . L2
3 Understand CUDA architectural details L2
4 Analyze fundamental issues in parallel computing L2
5 Study and develop basic applications using OpenCL L1
6 Design and Develop GPU based solutions to solve computationally intensive
problems in various fields L6

Page 92

University of Mumbai, B. E. (Information Technology), Rev 2016 230

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO Mapping
0 Prerequisite Concepts of Computer Organization and
Architecture , Concepts of Operating System ,
Concepts of Distributed Computing 2
I Introduction to
Parallel
Processing
Concepts
Introduction to Parallel Processing, Parallel
Architecture, Parallel Platforms, Performance
measures Processor Architecture, Interconnect,
communication, Memory Organization , GPU
Architecture: Evolution of GPU Architectures,
Typical GPU architecture, CPU - GPU
interaction, Address Spaces, Software
Architecture
Self-learning Topics:
NPTEL Course on GPU Architectures and
Programming 6 CO1
II Parallel
Programming
with MPI,
OpenMP Building blocks of MPI, Overlapping
communication and computation, collective
communication operations
OpenMP Threading Building blocks; An
Overview of Mem ory Allocators, Parallel
programming model
2.3 Combining MPI and OpenMP, Shared
memory programming
Self-learning Topics:
NPTEL Course on Introduction to parallel
programming with OpenMP and MPI
8 CO2
III CUDA: GPU
Parallel
Development
Environment Compute Unified Device Architecture (CUDA)
Architecture, CUDA programming model,
execution modelThread organization: Concept
of threads, Blocks, grid, thread index
generation, warp
Scheduling - Memory Handling with CUDA:
Shared Memory, Global Memory, Constant
Mem ory and Texture Memory
Self-learning Topics:
http://www.nvidia.com/object/cuda_home_new.
html 8 CO3, CO6
IV Fundamental
Design Issues in
Parallel
Computing
Synchronization, Scheduling, Job Allocation,
Job Partitioning , Dependency Analysis,
Mapping Parallel Algorithms to Parallel
Architectures , Performance Analysis of
Parallel Algorithms 6 CO4
V OpenCL Basics OpenCL Standard , Kernels – Host Device
Interaction – Execution Environment , Memory 6 CO5, CO6

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University of Mumbai, B. E. (Information Technology), Rev 2016 230 Model , Basic OpenCL Examples
Self-learning Topics: http://www.openCL.org
VI Fundamental
Limitations
Facing Parallel
Computing
Bandwidth Limitations, Latency Limitations
Latency Hiding/Tolerating Techniques and
their limitation ,
Self-learning Topics:
Case study of HPC 3 CO4, CO6
Text Books:
1. “Advanced Computer Architecture: Parallelism, Scalability, Programmability”, by Kai Hwang,
McGraw Hill 1993
2. “Parallel Programming in C with MPI and OpenMP”, Michael J. Quinn, McGraw -Hill International
Editions, Computer Science Series, 2008.
3. “Introduction to Parallel Computing”, AnanthGrama, Anshul Gupta, George Karypis, Vipin Kumar ,
Pearson Education, Second Edition, 2007
4. Petascale Computing: Algorithms and Applications, David A. Bader (Ed.), Chapman & Hall/CRC
Computational Science Series, © 2007
5. “CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs (Applications of GPU
Computing)”, Shane Cook, First Edition, Morgan Kaufmann, 2012.

References:
1. Petascale Computing: Algorithms and Applications, D avid A. Bader (Ed.), Chapman & Hall/CRC
Computational Science Series, © 2007.
2. “CUDA by Example: An Introduction to General Purpose GPU Programming”, Addison - Wesley,
2010.
3. “High Performance Computing: Paradigm and Infrastructure”,Lawrence Yang, Minyi Guo, Wiley,
2006
Online References:
1. https://cuda -tutorial.readthedocs.io/en/latest/
2. CUDA: docs.nvidia.com/cuda

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.
EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syl labus should
be covered inquestionpapersofendsemesterexamination.

Page 94

University of Mumbai, B. E. (Information Technology), Rev 2016 230

Course Code Course Name Theory Practical Tutorial Theory Practical/Oral Tutorial Total
ME-ITPE2021 DesignT
hinking 03 -- -- 03 -- -- 03



Course Code

Course
Name ExaminationScheme
TheoryMarks
Term
Work

Practical

Oral

Total Internalassessment
End
Sem.Ex
am Test1 Test
2 Avg.of 2
Tests
ME-ITPE 2021 DesignT
hinking 20 20 20 80 -- -- -- 100


Course Objectives:
Sr.
No
. Course Objectives
The course aims:
1
Tostresstheimportanceofgooddesign.
2 Torecognizethelatestandfutureissuesandchallengesininnovation.
3 Toexposethestudentwithstateoftheartperspectives,ideas,concepts,andsolutionsrelatedtothedesignandinnovationusingdesignthinking principles.
4 Todevelopanadvancedinnovationandgrowthmindsetformofproblemidentificationandreframing,andinsightgeneration.
5 Toprovideasocialandthinkingspacefortherecognitionofinnovationchallengesandthedesignofcreativesolutions.
6 Toproposeaconcrete,feasible,viableandre levantinnovationproject/challengewithImplementation

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 Understandgoodfeaturesofdesigns. L2
2 Understandimportanceofinnovationindaytodaylife L2
3 Illustrate and analyze user needs and formulate design and
innovationusingdesignthinkingprinciples. L4
4 Interpretandevaluatethedatacollectedduringtheprocessof
problemidentificationandreframing,andinsightgeneration. L5
5 Evaluate designs based on theoretical frameworks and
methodologicalapproaches. L5

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University of Mumbai, B. E. (Information Technology), Rev 2016 230
6 Design innovativeapplicationsthatareusable, effective and
efficientforintendedusers L6


DETAILED SYLLABUS:

Sr.
No. Module DetailedContent Hours CO
Mapping
0 Prerequisite Software Engineering concepts and
anyprogrammingLanguage 2
I Introductio
ntodesign GoodandPoorDesign,WhatisInteractionDesign,T
heUserExperience,The Process Of Interaction
Design,
InteractionDesignandtheUserExperience,Necessi
tyofUI/UX,
Self-learningTopics: Study of Various
interactivedaytodayapplication 5 CO1
II DesignThi
nking Back
ground
Definition ofdesign thinking, business uses
ofdesign thinking,variety of approaches within
the design thinkingdiscipline, design thinking
mindset

Self-
learningTopics: Designthinkinginbusinessapplic
ation 5 CO2
III Design FundamentalConcepts: 8 CO3
Thinking Empathy, ethnography, divergent
thinking
Approach convergentthinking,visualthinking,assumption
testing,prototyping,andvalidationwithindesign
Thinking ,
DesignThinkingResources
Human resource, preferred space
prepared,
materials commonly used, dynamic
between
designthinkingteamsandtheorganization
3.3DesignThinkingProcesses
Designthinkingapproaches,DoubleDiamond
approach,d.School5 -Stageapproach,Growth
approach,roleofprojectmanagementwithin
designthinking
Self-learningTopics: StudyofVariousresources

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University of Mumbai, B. E. (Information Technology), Rev 2016 230
fordesignthinking


IV DesignThi
nking
inPractice 4.1 ProcessStagesofDesigningforGrowth
4.2 DesignThinkingToolsandMethods
needtousetoolsandmethods,visualization,journey
mapping,valuechainanalysis,mindmapping,brain
storming,conceptdevelopmentassumptiontesting,
rapidprototypingcustomerco -
creation,learninglaunch.
Self-
learningTopics: Studyofconceptdevelopment
withanyapplication 7 CO4 / CO5
V UX
Evaluation,
TheInteract
ion
Cycle and
theUser
Action UX Goals, Metrics and Targets, UX
EvaluationTechniques. -Formative vs summative
,Analysis,Theinteractioncycle,Theuseractionfra
mework adding a structured knowledge
basetotheinteractioncycle,Interactioncycleand
useractionframeworkcontentcategories,Role 7 CO5
Framework ofaffordanceswithintheUAF,Practicalvalue
oftheUAF.
Self-learningTopics: StudyofUIandUXgoals
withanyapplication
VI DesignThi
nking Appl
ication This section explores practical case study related
toproduct development in a design thinking
effort.Anydomainispreferable.

Self-
learningTopics: Studyofanydomainapplication 5 CO5/
CO6


TextBooks:
1. “Designing for growth: A design thinking tool kit for managers”, by Jeanne Liedtka
and TimOgilvie.,2011,ISBN978 -0-231-15838 -1
2. “The design thinking playbook: Mindful digital transformation of teams, products,
services,businesses and ecosystems”, by Michael Lewrick, Patrick Link, Larry
Leifer., 2018, I SBN978 -1-119-46747 -2
3. “Presumptive design: Design provocations for innovation”, by Leo Frishberg and
CharlesLambdin.,2016,ISBN:978 -0-12-803086 -8
4. “Systemsthinking:Managing chaos and complexity: A platform for designing
businessarchitecture.”, “Chapter Seve n: Design Thinking”, by Jamshid Gharajedaghi,
2011, ISBN978 -0-12-385915 -0
5. InteractionDesign, byJ.Preece,Y.RogersandH.Sharp.ISBN0 -471-49278 -7.
6. Human Computer Interaction, byAlan Dix, JanetFinlay, Gregory DAbowd,Russell
Beale

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University of Mumbai, B. E. (Information Technology), Rev 2016 230

Page 98

University of Mumbai, B. E. (Information Technology), Rev 2016 230 References:
1. KarmicDesignThinkingbyProf.BalaRamadurai,availableat Amazon (paperback), Amazon(e -book),
Flipkart,Pothi,halfpricebooks.in.
2. Design: Creation ofArtifacts inSociety byProf. KarlUlrich, U. Penn
3. ChangebyDesignbyTimBrown.

4. TheUXBook,byRexHartsonandPardhaSPyla
5. DonaldA. Norman,“The design ofeveryday things”,Basic books.
6. JeffJohnson,“Designingwiththemindinmind”,MorganKaufmannPublication.


Online
References: https://nptel.ac.in/courses/110106124 https://onlinec
ourses.nptel.ac.in/noc22_mg32/preview https://onlinecourses.nptel
.ac.in/noc21_ar05/preview https://nptel.ac.in/courses/124/107/1241
07008/ https://nptel.ac.in/noc/courses/noc19/SEM1/noc19 -
ar10/ https://nptel.ac.in/courses/107/103/107103083/
https://www.youtube.com/watch?v=6C2Ye1makdY&list=PLW -zSkCnZ -gD5TDfs1eL5EnH2mQ0 f9g6B
https://xd.adobe.com/ideas/process/

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.
EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 99

University of Mumbai, B. E. (Information Technology), Rev 2016 230



Course
Code
Course
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total

ME-ITPE 2022


Internet of
Everything 03 -- -- 03 -- -- 03
Examination Scheme
Theory Examination
Term
Work
Pract
Oral Internal Assessment End
Sem
Exam Test 1 Test
2 Avg
20 20 20 80 -- -- --


Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To describe the concepts of Objects in IOT, IOT Identifier, IOT Technologies.
2 Discuss and elaborate RFID architecture, RFID Tag and Reader along with the protocols used to
solve the RFID issues faced in RFID applications.
3 . Describe the connecting and networking nodes in a secure communication with the help of
protocols such as MQTT, CoAP, and REST.
4 . Explain Hadoop MapReduce and demonstrate its usage for real time batch data Analysis using
Apache Oozie, Apache Spark and Apache Storm.
5 Summarize the use of ML algorithms in IoT Based application in Healthcare and Smart
Transportation.
6 Elaborate and show how the analysis and the evaluation is carried out over the data received
through sensors in IOE to ensure security in IOE applications .

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 Objects in IOT, list the IOT Identifiers and know the different
technologies.
Self-Learning Topics : History of IOT, Compare IOT & IOE L1
2 Explain RFID architecture, list the Components, identify RFID Tag and
Reader along with the protocols used to solve the RFID issues faced in RFID
applications .
Self-Learning Topics: Binary search Algorithms L2
3 Design applications using the communication protocols such as MQTT,
CoAP, and REST.
Self-Learning Topics: Industrial WSN Standards L6
4 Use Hadoop MapReduce for real time batch data Analysis using Apache L3

Page 100

University of Mumbai, B. E. (Information Technology), Rev 2016 230 Oozie, Apache Spark and Apache Storm.
Self-Learning Topics: Apache Hadoop Setup
5 Recall the ML algorithms used in IoT Based applications in Healthcare and
Smart Transportation.
Self-Learning Topics: Deep Learning in IOT L1
6 Analysis and evaluate the data received through sensors in IOE and Security
in IOE applications .
Self-Learning Topics: Trust based Recommender Systems inIoT L4


Sr. No. Module Detailed Contain Hours CO Mapping
0 Prerequisi
tes: IOT Lab, Sensor Lab, Wireless Network. 2
1. Introductio
n to IOE Introduction and History of IOT, Objects in IOT
IOT Identifier, IOT Technologies
Self-Learning Topics: History of IOT, Compare
IOT & IOE
5 CO1
2. Radio -
frequency
identificati
on (RFID)
Technolog
y Introduction to RFID and Principles of RFID
RFID Components and RFID Tag and Reader
RFID Transponder and RFID architecture
RFID Middleware
Protocols: Tree protocols, Tree splitting
algorithms, Binary search Algorithms
RFID Challenges and Applications
Self-Learning To pics: Binary search Algorithms 7 CO2
3. Wireless
Sensor
Networks Connecting and networking nodes, Securing
communication, standards, IP Addressing
Protocols - MQTT, CoAP, REST
Self-Learning Topics : Industrial WSN Standards 6 CO3
4. Hadoop
MapReduc
e Introduction to Hadoop MapReduce,
Architecture of Hadoop and Hadoop Ecosystem
Hadoop MapReduce for Batch Data Analysis
Apache Oozie, Apache Spark, Apache Storm
Real-time Data Analysis Using Apache Storm
Self-Learning Topics: Apache Hadoop Setup 7 CO4
5 IoT
with
ML Machine Learning in IoT Based Healthcare
Applications, General Architecture of H -IoT
Overview of Algorithms and Security of health
data, Machine Learning in IoT Based Smart
Transportation, ML algorithms to support Smart
Transportation
Self-Learning Topics : Deep Learning in IOT 6 CO5
6. Security
in IoE Common Challenges in OT Security. How IT
and OT Security Practices and Systems Vary
Formal Risk Analysis Structures: OCTAVE and
FAIR Convergence of IoE and Blockchain its
security challenges
Self-Learning Topics: Trust based Recommender 6 CO6

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University of Mumbai, B. E. (Information Technology), Rev 2016 230 Systems in IoT







Text
Books



1.Hakima Chaouchi, Internet of Things connecting objects to the web. Wiley.

2. Arshdeep Bhaga and Vijay Madisetti, Internet of Things - A Hands -on-Approach.

3. David Hanes, Gonzalo Salgueiro, Patrick Grossetete, Rob Barton, Jerome Henry, “IoT
Fundamentals – Networking Technologies, Protocols, a nd Use Cases for the Internet Of Things”, 1 st
Edition, Pears on Education, Cisco Press, 2017

Reference Books


1. Samuel Greengard, The Internet of Things (MIT Press).
2. Hakima Chaouchi, The Internet of Things - Connecting objects to the web. Wiley
Publications.
3. Herve chabanne, RFID and the Internet of Things. Wiley Publications.
Reference Papers

1. H. K. Bharadwaj et al., "A Review on the Role of Machine Learning in Enabling IoT
Based Healthcare Applications," in IEEE Access, vol. 9, pp. 38859 -38890, 2021, doi:
10.1109/ACCESS.2021.3059858.
2. Zantalis, F.; Koulouras, G.; Karabetsos, S.; Kandris, D. A Review of Machine Learning
and IoT in Smart Transportation. Future Internet 2019, 11, 94.
https://doi.org/10.3390/fi11040094
3. L. Wei, J. Wu, C. Long and Y. -B. Lin, "The Convergence of IoE and Blockchain:
Security Challenges," in IT Professional, vol. 21, no. 5, pp. 26 -32, 1 Sept. -Oct. 2019, doi:
10.1109/MITP.2019.2923602.


Useful Links :
1 https://nptel.ac.in/courses/106/105/106105166/
2 https://nptel.ac.in/courses/108/108/108108098/
3 https://nptel.ac.in/courses/106/105/106105195/
4 https://www.coursera.org/specializations/IoT

Assessment:
Internal Assessment Test:

Page 102

University of Mumbai, B. E. (Information Technology), Rev 2016 230 Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.
EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestio ns to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 103

University of Mumbai, B. E. (Information Technology), Rev 2016 230


Course Code Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITPE 2023 Information
Retrieval 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
ME-ITPE 2023 Information
Retrieval 20 20 20 80 -- -- -- 100



Course Objectives:
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 understand application of IR principles in data structures.
4 . To apply text processing techniques and operations in information retrieval system.
5 To understand text search techniques.
6 To make the students understand various techniques of searching multimedia elements.

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
2 Evaluate the taxonomy of different information retrieval models. L5
3 Apply IR principles to locate relevant information large collections of data. L3
4 Design different document clustering algorithms. L6
5 Apply their knowledge of searching techniques to documents . L3
6 Apply various multimedia elements with the right techniques L3

Page 104

University of Mumbai, B. E. (Information Technology), Rev 2016 230 DETAILED SYLLABUS:
Sr.
No. Module Data sDetailed Content Hours CO Mapping
0 Prerequisite Data Structures 2
I Introduction Introduction to Information Retrieval
Systems ,Definition of Information Retrieval
System - Objectives of Information Retrieval
Systems - Functional, Information versus
Data Retrieval, A Taxonomy of Information
Retrieval Models. The Retrieval Process - Ad
Hoc and Filtering. Classic Information
Retrieval :Basic Concepts, Boolean Model
,Vector Model .
Brief Comparison of Classic Models
,Alternative Set Theoretic Models :Fuzzy
Set Model, Search engines and Web
browsers
Self-learning Topics: Corpus linguistics ,
Brown Corpus 5
CO1
II Retrieval System
Functions and
Indexing
Search Capabilities - Browse Capabilities -
Indexing Process –Automatic Indexing -
Statistical Indexing – Natural Language –
Concept Indexing - Hypertext Linkages -
Information Extraction
Self-learning Topics: Part of speech. 7 CO2
III Query Languages
and Data structures
in Information
Retrieval Query Languages for IR
● Keywords
● Boolean Queries
● Context Queries
● Natural Language Queries
● Structural Queries
Stemming Algorithms - Inverted File
Structure - N-Gram Data Structures -
PAT Data Structure - Signature File
Structure - Hypertext and XML Data
Structures - Hidden Markov Models
Self-learning Topics: Advanced Query
Operations , Automatic Local Analysis,
Automati c Global Analysis
6 CO3
IV Document and
Term Clustering Introduction to Clustering - Thesaurus
Generation - Item Clustering - Hierarchy of
Clusters
Self-learning Topics: Text Compression,
Comparing Text Compression Technique 4 CO4
V Search
Techniques Search Statements and Binding - Similarity
Measures and Ranking - 8 CO5

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University of Mumbai, B. E. (Information Technology), Rev 2016 230 Relevance Feedback - Selective
Dissemination of Information Search -
Weighted Searches of Boolean Systems -
Searching the INTERNET and Hypertext –
Introduction to Text Search T echniques -
Software Text
Search Algorithms.
Self-learning Topics: cross -language
retrieval
VI Visualization &
Multimedia
Information
Retrieval Introduction to Information Visualization -
Cognition and Perception and vision -
Information Visualization Technologies and
techniques .Spoken Language Audio
Retrieval –Non-Speech Audio Retrieval -
Graph Retrieval - Imagery Retrieval - Video
Retrieval, 3D retrieval, music retrieval
Self-learning Topics: LIRE (Luce -ne Image
Retrieval)
7 CO6

Text Books:
1. Modern Information Retrieval, Ricardo Baeza -Yates,berthier Ribeiro - Neto, ACM Press - Addison
Wesley
2. Information storage and retrieval by Robert R Korthage, wiley publication.
3. Information Retrieval Systems: Theory and Implementation, Gerald Kowaski, Kluwer
AcademicPublisher.
4. Michael W. Berry “ Survey of Text Mining: Clustering, Classification and Retrieval”, Springer
Verlag,
References:
1. Introduction to Information Retrieval By Christopher D. Manning and Prabhakar Raghavan,
Cambridge Universi ty Press.
2. Information Storage & Retrieval By Robert Korfhage – John Wiley & Sons
3. Introduction to Modern Information Retrieval. G.G. Chowdhury. NealSchuman.
4. Text Information Retrieval Systems. C.T. Meadow, B.R. Boyce, D.H. Kraft, C.L. Barry.
Online References:
1) https://nlp.stanford.edu/IR -book/
2) https://en.wikipedia.org/wiki/Information_retrieval

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum
02 Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.
EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks,
out of these any four questions to beattempted by students. Minimum 80% syllabus should
be covered inquestionpapersofendsemesterexamination.

Page 106

University of Mumbai, B. E. (Information Technology), Rev 2016 271 Course Cod e Course
Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
ME-ITPE 2024 Green IT 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
ME-ITPE 2024 Green IT
20 20 20 80 -- -- -- 100



Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand what Green IT is and How it can help improve environmental Sustainability
2 To understand the principles and practices of Green IT.
3 To understand how Green IT is adopted or deployed in enterprises.
4 . To understand how data centers, cloud computing, storage systems, software and networks can be
made greener.
5 To measure the Ma turity of a Sustainable ICT world.
6 To implement the concept of Green IT in Information Assurance in Communication and Social
Media and all other commercial field.

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 awareness among stakeholders and promote green agenda and green
initiatives in their working environments leading to green movement L1
2 Identify IT Infrastructure Management and Green Data Center Metrics for
software development L1
3 Recognize Objectives of Green Network Protocols for Data communication L1
4 Use Green IT Strategies and metrics for ICT development. L3
5 Illustrate various green IT services and its roles L3
6 Use new career opportunities available in IT profession, audits and others with
special skills. L3

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University of Mumbai, B. E. (Information Technology), Rev 2016 272

DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO Mapping
0 Prerequisite Environmental Studies 2
I Introduction Environmental Impacts of IT, Holistic Approach to
Greening IT, Green IT Standards and EcoLabeling,
Enterprise Green IT Strategy , Green IT: Burden or
Opportunity?
Hardware: Life Cycle of a Device or Hardware, Reuse,
Recycle and Dispose.
Software: Introduction, EnergySaving Software
Techniques, Evaluating and Measuring Software Impact
to Platform Power 6 CO1
II Software
development
and data
centers Sustainable Software, Software Sustainability Attributes,
Software Sustainability Metrics, Sustainable Software
Methodology, Data Centres and Associated Energy
Challenges, Data Centre IT Infrastructure, Data Centre
Facility Infrastructure: Implications for Energy
Efficiency, IT Infrastructure Management, Green Data
Centre Metrics 6 CO1 CO2
III Data storage
and
communicatio
n Storage Media Power Characteristics, Energy
Management Techniques for Hard Disks, System -Level
Energy Management, Objectives of Green Network
Protocols, Green Network Protocols and Standards 6 CO1 CO3
IV Information
systems, green
it strategy and
metrics Approaching Green IT Strategies, Business Drivers of
Green IT Strategy, Business Dimensions for Green IT
Transformation, Multilevel Sustainable Information,
Sustainability Hierarchy Models, Product Level
Information, Individual Level Information, Functional
Level Information, Organizational Level Information,
Regional/City Level Information, Measuring the Maturity
of Sustain able ICT. 6 CO1 CO4
V Green it
services and
roles Factors Driving the Development of Sustainable IT,
Sustainable IT Services (SITS), SITS Strategic
Framework, Sustainable IT Roadmap, Organizational and
Enterprise Greening, Information Systems in Greening
Enterprises, Greening the Enterprise: IT Usage and
Hardware, Inter -organizational Enterprise Activities and
Green Issues, Enablers and Making the Case for IT and
the Green Enterprise. 6 CO1 CO4
CO5
VI Managing and
regulating
green it Strategizing Green Initiatives, Implementation of Green
IT, Information Assurance, Communication and Social
Media, The Regulatory Environment and IT
Manufacturers, Nonregulatory Government Initiatives,
Industry Associations and Standards Bodies, Green
Building Standards, Gre en Data Centres, Social
Movements and Greenpeace 7 CO1 CO5
CO6

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University of Mumbai, B. E. (Information Technology), Rev 2016 273 Text Books:
1. San Murugesan, G. R. Gangadharan, Harnessing Green IT,WILEY 1st Edition -2018
2. Mohammad Dastbaz Colin Pattinson Babak Akhgar, Green Information Technology A Sustainable

Assessment:
Internal Assessment Test:

Assessmentconsistsoftwotestsoutofwhich;oneshouldbecompulsory class test (on minimum 02
Modules) and the other iseitheraclasstestorassignmentonliveproblemsorcourseproject.
EndSemesterExamination:
Someguidelinesforsettingthequestionpapersareas,sixquestions to be set each of 20 marks, out of
these any four questions to beattempted by students. Minimum 80% syllabus should be covered
inquestionpapersofendsemesterexamination.

Page 109

University of Mumbai, B. E. (Information Technology), Rev 2016 274



Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ME-ITL201 Program Lab-II -- 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
ME-
ITL201 Program Lab-II -- -- -- -- 25 25 50
Lab Objectives:

Sr. No Lab Objectives
1 AngularJS Framework for Single Page Web Applications.
2 AJAX for Rich Internet Applications.
3 REST API and MongoDB for Frontend and Backend Connectivity.
4 To understand the concept of cloud computing and virtualization.
5 To understand the concept of mobile computing.
6 To understand the concept of mobile offloading.
Lab Outcomes:
Sr.
No Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
1 Implement Single Page Applications using AngularJS Framework. L1, L2, L3
2 Develop Rich Internet Applications using AJAX. L1, L2, L3
3 Create REST Web services using MongoDB. L1, L2, L3, L4
4 Understand and apply the concept of cloud computing and virtualization L1,L2,L3
5 Understand and apply the concept of mobile computing L1,L2,L3
6 Understand and apply the concept of mobile offloading L1,L2,L3

Prerequisite: Computer Networks, HTML/HTML5, CSS/CSS3, JavaScript, Python


DETAILED SYLLABUS:

Page 110

University of Mumbai, B. E. (Information Technology), Rev 2016 275 Sr.
No. Module Detailed Content Hours LO
Mapping
I AngularJS Perform Any 2 from the following
1. Create a simple HTML
“Hello World” Project using
AngularJS Framework and
apply ng -controller, ng -
model and expressions.
2. Events and Validations in
AngularJS. (Create
functions and add events,
adding HTML validators,
using $valid property of
Angular, etc.)
3. Create an application for
like Students Record using
AngularJS
05 LO1
II Rich Internet
Application using
AJAX Perform Any 3 from the following
1. Write a JavaScript program
for a AJAX.
2. Write a program to use
AJAX for user validation
using and to show the result
on the same page below the
submit button.
3. Design and develop small
web application using
AJAX, HTML and JSP.
04 LO2
III MongoDB and
Building REST
API using
MongoDB Perform Any 1 from the following
1. Build a RESTful API using
MongoDB.
2. Build a TypeScript REST
API using MongoDB.
04 LO3
IV Cloud computing
and virtualization 1) Demonstrate database as a cloud
computing service
2) Demonstrate memory
virtualization in single machine
3) Demonstrate virtualization by
using VMware
4) Demonstrate the installation of
open source cloud platform
05 LO4
V Mobile cloud
computing 5) 5)Demonstrate how to built
ML/AL capabilities on cloud for 04 LO5

Page 111

University of Mumbai, B. E. (Information Technology), Rev 2016 276 mobile applications
6) 6) Explain how mobile offline data
synchronization can be done using
any cloud platform

VI Mobile offloading ) Demonstrate how cloud can be used
to implement push notifications for
mobile apps.
8) Demonstrate how cloud platform
can be used to device testing of mobile
apps
9) Demonstrate the user sign -up and
sign-in management using any cloud
platform
10) Demonstrate how server less
architecture can be used to build APIs
for mobile applications
11) Demonstrate how speech
recognition can be implemented for
mobile apps using cloud platform
12) Demonstrate how the user
engagements and analytics of mobile
apps can be managed by cloud services
13) Demonstrate and explain how
cloud can be used for content delivery
on mobile phones
04 LO6

Text Books:
1. John Hebeler, Matthew Fisher, Ryan Blace, Andrew Perez -Lopez, “Semantic Web Programming”, Wiley
Publishing, Inc, 1st Edition, 2009.
2. Boris Cherny, “ Programming TypeScript - Making Your Javascript Application Scale”, O’Reilly Media Inc.,
2019 Edition.
3. Adam Bretz and Colin J. Ihrig, “Full Stack JavaScript Development with MEAN”, SitePoint Pty. Ltd., 2015
Edition.
4. Simon Holmes Clive Harber, “Getting MEAN with Mongo, Express, Angular, and Node”, Manning
Publications, 2019 Edition.
5. Dr. Deven Shah, “Advanced Internet Programming”, StarEdu Solutions, 2019 Edition.
6. Miguel Grinberg, “Flask Web Development: Developing Web Applications with Python”, O’Reilly, 2018
Edition.
7. Cloud Computing: Principles and Paradigms,Rajkumar Buyya , James Broberg,Andrzej M. Goscinski
8. Cloud c omputing by Kailesh Jayaswal,jagannath kallakurchi, donald j Hou de
9. Mobile cloud computing : foundation and service model by Dijiang Huang and Huijun Wu
10. Mobile computing architecture, algorithm and application by Debashis De



References:
1. John Davies, Rudi Studer and Paul Warren, “Semantic Web Technologies Trends and Research in Ontology -
based Systems”, Wiley, 2006 Edition.
2. Yakov Fain and Anton Moiseev, “TypeScript Quickly”, Manning Publications, 2020 Edition.
3. Steve Fenton, “Pro TypeScript: Application - Scale Javascript Development”, Apress, 2014 Edition.

Page 112

University of Mumbai, B. E. (Information Technology), Rev 2016 277 4. Brad Dayley , Brendan Dayley, Caleb Dayley, “Node.js, MongoDB and Angular Web Development: The
definitive guide to using the MEAN stack to build web applications”, 2nd Edition, Addison -Wesley
Professional, 2018 Edition.
5. Cloud computing Bible by barrie Sosinsky.
6. Cloud computing by Dr Kumar Saurabh

Term Work:

Term Work shall consist of at least 10 practical based on the above list. Also Term Wor k Journal must include Assignement as
mentioned in above syllabus.

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

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

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University of Mumbai, B. E. (Information Technology), Rev 2016 278 Teaching Scheme (Contact
Hours)
Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical
& Oral Tutorial Total
ME-ITSBL2 01 Design
Thinking Lab
(SBL) -- 4 -- -- 2 -- 02

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
ME-
ITSBL2 01 Design Thinking
Lab (SBL) -- -- -- -- 50 50 100
Lab Objectives:

Sr. No Lab Objectives
1 Understand the design thinking process.
2 Understand and prepare a detail journey map for your problem.
3 Understand and design a mock -up and innovation model of your problem.
4 Understand the different technologies and apply it.
5 Understand and create a prototype
6 Use testing software by apply different test modes.
Lab Outcomes:
Sr.
No Lab Outcomes Cognitive levels
of attainment as
per Bloom’s
Taxonomy
1 Understand and apply the design thinking process. L1,L2,L3
2 Prepare a detail journey map for your problem. L1,L2,L3
3 Design a mock -up and innovation model of your problem. L6
4 Understand the different technologies and apply it. L1,L2
5 create a prototype for your problem L6
6 Use testing software by apply different test modes. L1,L2,L3,L4

Prerequisite: Any programming language .
DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours LO
Mapping
I Introduction Concept of design thinking, what
is design thinking, core elements
of design thinking. Key principles 06 LO1

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University of Mumbai, B. E. (Information Technology), Rev 2016 279 and mindset. Mindset & attitudes.
Five different phases of Design
thinking.

II Deconstructing
stereotypes through
creative
collaboration &
Immersion. . Structure of the project
Focus: gender equality
Results of the creative collaboration .
Immersion , Reframing , Exploratory
Research , Desk Research . 04 LO2
III A step -by-step guide A thousand and one methods
Facilitate your team
Be curious!
Be compassionate!
Be creative!
Be constructive! 04 LO3
IV Analysis and
Synthesis Insight Cards , Affinity
Diagram , Conceptual Map ,
Guiding Criteria , Personas ,
Empathy Map , User’s journey ,
Blueprint. 06 LO4
V Ideation Brainstorming , Co-creation
workshop , Idea Menu , Decision
Matrix. 05 LO4,LO5
VI Prototyping and
tesing Paper Prototyping , Volumetric
Model , Staging , Storyboard,
Service Prototyping . Use tools
for testing. 05 LO6

Text & Refernces Books:
1. An introduction to design thingking, standard.
2. A practical guide for design thinking, 2019
3. Design thinking a guide book
4. Design Thinking Business Innovation.
5. Handbook of Design Thinking tips and tools for how to design thinking.
6. Design Thinking Handbook, Eli Woolery.


Guidelines for Mini Project as per above sylla bus.
 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 state ment 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 cover weekly
activity o f 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 students during mini pro ject activity;however, focus shall be on self -
learning.

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University of Mumbai, B. E. (Information Technology), Rev 2016 280  Students in a group shall understand contribute to open source 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 using open source tools to be compiled in
standard format of University of Mumb ai.
 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 Mini Project:
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 focus shall also be on each indivi dual 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 : 30
o Marks awarded by review committee : 10
o Quality of Project Report :05


Term Work:

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

Term Work Marks : 50 Marks (Total marks) = 40 Marks (Mini -project) + 5 Marks (Attendance)

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

Page 116

University of Mumbai, B. E. (Information Technology), Rev 2016 281 Course Code Course Name Credits
IE2011 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 ab out
the various phases from 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 fu turereference



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
05 5.1 Executing Projects:
Planning monitoring and controlling cycle. Information needs and reporting, 8

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University of Mumbai, B. E. (Information Technology), Rev 2016 282 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, Project 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 assignmen t 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 th en part (b)
will be from any module other than module3)
4. Only Four question need to besolved.

Page 118

University of Mumbai, B. E. (Information Technology), Rev 2016 283 Course Code Course Name Credits
IE2012 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 corporatefin ance
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 Mar ket and Foreign Currency Market Financial
Institutions: Meaning, Characteristics and Classification of Financial Institutions —
Commercial Banks, Investment -Merchant 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; Effic iency 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 119

University of Mumbai, B. E. (Information Technology), Rev 2016 284 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, and Modigliani -Miller Approach. Relation between
Capital Structure and Corpora te 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 pr oblems 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 120

University of Mumbai, B. E. (Information Technology), Rev 2016 285 Course Code Course Name Credits
IE2013 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 gover nment 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 Government 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 121

University of Mumbai, B. E. (Information Technology), Rev 2016 286 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 Prasa d, Small and Medium Enterprises in Global Perspective, New century Publications,
NewDelhi
5. Vasant Desai, Entrepreneurial development and management, Himalaya PublishingHouse
6. Maddhurima 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 122

University of Mumbai, B. E. (Information Technology), Rev 2016 287 Course Code Course Name Credits
IE2014 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 trends 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, Restructuring 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 I ndividual
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 performing
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

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University of Mumbai, B. E. (Information Technology), Rev 2016 288 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 ageing
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, Co ncept 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, 15thedition,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 124

University of Mumbai, B. E. (Information Technology), Rev 2016 289 End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examinatio n. 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 exam ple 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 125

University of Mumbai, B. E. (Information Technology), Rev 2016 280 Course Code Course Name Credits
IE2015 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 Resources

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 Respons ibility 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 126

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 Manuel 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 pr oblems 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 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.

Page 127

University of Mumbai, B. E. (Information Technology), Rev 2016 282 Course Code Course Name Credits
IE2016 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 and 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

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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 Edu cation



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 129

University of Mumbai, B. E. (Information Technology), Rev 2016 284 Course Code Course Name Credits
IE2017 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 130

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, B ITS 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 scientists, Wiley -IEEE Press
Asses sment :

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 131

University of Mumbai, B. E. (Information Technology), Rev 2016 286 Course Code Course Name Credits
IE2018 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 itsstrategies

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 132

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 133

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 134

University of Mumbai, B. E. (Information Technology), Rev 2016 289 Course Code Course Name Credits
IE2019 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 environment relate dlegislations



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 Management: An Indian Perspective, S N Chary and Vinod Vyasulu, Maclillan
India,2000

Page 135

University of Mumbai, B. E. (Information Technology), Rev 2016 290

6. Introduction to Environmental Management, Mary K Theodore and Louise Theodore, CRC Press
7. Environment and Ecology, Majid Hussain, 3rd Ed. AccessPublishing.2015



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 t he 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 136

University of Mumbai, B. E. (Information Technology), Rev 2016 291 8. Introduction to Environmental Management, Mary K Theodore and
Louise Theodore, CRC Press
9. Environment and Ecology, Majid Hussain, 3rd Ed. AccessPublishing.2015



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.
5. Question paper will comprise of total sixquestion
6. All question carry equalmarks
7. 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)
8. Only Four question need to besolved.

\I Process
Models Generic process Model , Prescriptive
process model, Specialized process model. 4
II Agile
development What is agile process, Extreme
programming, ASD, Scrum, DSDM, Crystel
FDD, LSD, AM, AUP 4
III Principle
s that
guide
practice
and
Understa
nding
requirem
ents Core principles, principles thar guide
framework activities, Requirements
engineering, establishing groundwork,
eliciting requirements, building requirements
model, negotiating requirements, Validating
requirements. 4

Page 137

University of Mumbai, B. E. (Information Technology), Rev 2016 292
Textbook
2. Software Engineering, A Practitioner’s Approach, Seventh Edition, Roger s.
Pressman

Reference Book.
3. An integrated approach to Software Engineering, Pankaj Jalote
4. Software Engineering, Tenth Edition, Ian Sommerville

Assessment

Internal: Assessment consists of two tests out of which; one should be compulsory class
test (on minimum 03 Modules) and the other is either a class test or assignment or
seminar or paper reading.

End Semester Examination: End semester examination will be on complete syllabus for
80 marks.



IV Archi tect
ural
Design Software architecture , Architectural genres,
Architectural styles, Architectural design,
Design patterns, Pattern based software
design, Architectural patterns, User interface
design patterns. 8
V Quality
Manage
ment Quality concepts, Review techniques ,
Software quality assurance, testing strategies,
Formal modeling, and verification, product
metrics. 8
VI Software
process
improve
ment What is SPI, The SPI process, CMMI, SPI
frameworks, SPI ROI, SPI trends, cleanroom
software engineering 8