TE Comp engg Sem V VI1_1 Syllabus Mumbai University


TE Comp engg Sem V VI1_1 Syllabus Mumbai University by munotes

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

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

for information.

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AC: 29/06/2021
Item No : 6.15




























UNIVERSITY OF MUMBAI



Bachelor of Engineering
in
Computer Engineering
Second Year with Effect from AY 2020 -21
Third Year with Effect from AY 2021 -22
Final Year with Effect from AY 2022 -23
(REV - 2019 ‘C’ Scheme) from Academic Year 2019 – 20
Under
FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year 2019 –2020)

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Sr. No. Heading Particulars
1 Title of the Course Third Year Engineering
( Computer Engineering)

2
Eligibility for Admission After Passing Second Year Enginee ring as per
the Ordinance 0.6243
3 Passing Marks 40%
4 Ordinances /
Regulations ( if any) Ordinance 0.6243

5
No. of Years / Semesters
8 semesters

6
Level P.G. / U.G. / Diploma / Certificate
(Strike out which is not applicable)

7
Pattern Yearly / Semester
(Strike out which is not applicable )

8
Status New / Revised
(Strike out which is not applicable )
9 To be implemented from
Academic Year With effect from Academic Year: 2021 -2022


Dr. S. K. Ukarande Dr Anuradha Muzumdar
Associate Dean Dean
Faculty of Science and Technology Faculty of Science and Technology
University of Mumbai University of Mumbai
AC: 29/06/2021
Item No: 6.15
UNIVERSITY OF MUMBAI


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Preamble

To meet the challenge of ensuring excellence in engineering education, the issue of quality needs to
be addressed, debated and taken forward i n a systematic manner. Accreditation is the principal means
of quality assurance in higher education. The major emphasis of accreditation process is to measure
the outcomes of the program that is being accredited. In line with this Faculty of Science and
Technology (in particular Engineering) of University of Mumbai has taken a lead in incorporating
philosophy of outcome based education in the process of curriculum development.
Faculty resolved that course objectives and course outcomes are to be clearly de fined for each course,
so that all faculty members in affiliated institutes understand the depth and approach of course to be
taught, which will enhance learner’s learning process. Choice based Credit and grading system enables
a much -required shift in foc us from teacher -centric to learner -centric education since the workload
estimated is based on the investment of time in learning and not in teaching. It also focuses on
continuous evaluation which will enhance the quality of education. Credit assignment fo r courses is
based on 15 weeks teaching learning process, however content of courses is to be taught in 13 weeks
and remaining 2 weeks to be utilized for revision, guest lectures, coverage of content beyond syllabus
etc.
There was a concern that the earlier revised curriculum more focused on providing information and
knowledge across various domains of the said program, which led to heavily loading of students in
terms of direct contact hours. In this regard, faculty of sc ience and technology resolved that to
minimize the burden of contact hours, total credits of entire program will be of 170, wherein focus is
not only on providing knowledge but also on building skills, attitude and self learning. Therefore in
the present c urriculum skill based laboratories and mini projects are made mandatory across all
disciplines of engineering in second and third year of programs, which will definitely facilitate self
learning of students. The overall credits and approach of curriculum p roposed in the present revision
is in line with AICTE model curriculum.
The present curriculum will be implemented for Second Year of Engineering from the academic year
2021 -22. Subsequently this will be carried forward for Third Year and Final Year Engine ering in the
academic years 2022 -23, 2023 -24, respectively.




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

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ncorporation and Implementation of Online Contents from
NPTEL/ Swayam Platform



The curriculum revision is mainly focused on knowledge component, skill based activities and
project based activities. Self-learning opportunities are provided to learners. In the revision process
this time in par ticular Revised syllabus of ‘C’ scheme wherever possible additional resource links
of platforms such as NPTEL, Swayam are appropriately provided. In an earlier revision of
curriculum in the year 2012 and 2016 in Rev ised scheme ‘A' and ‘B' respectively, efforts were
made to use online contents more appropriately as additional learning materials to enhance
learning of students.
In the current revision based on the recommendation of AICTE model curriculum overall credit s
are reduced to 171, to provide opportunity of self-learning to learner. Learners are now getting
sufficient time for self-learning either through online courses or additional projects for enhancing
their knowledge and skill sets.
The Principals/ HoD’s / Faculties of all the institute are required to motivate and encourage learners
to use additional online resources available on platforms such as NPTEL/ Swayam. Learners can
be advised to take up online courses, on successful completion they are required to submit
certification for the same. This will definitely help learners to facilitate their enhanced learning
based on their interest.






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

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Preface by Board of Studies in
Computer Engineering
Dear Students and Teachers, we, the members of Board of Studies Computer
Engineering, are very happy to present Third Year Computer Engineering syllabus
effective from the Academic Year 2021 -22 (REV -2019’C’ Scheme). We are sure you
will find this syllabus interesting, challenging, fulfill certain needs and expectations.
Computer Engineering is one of the most sought -after cour ses amongst engineering
students. The syllabus needs revision in terms of preparing the student for the
professional scenario relevant and suitable to cater the needs of industry in present day
context. The syllabus focuses on providing a sound theoretical background as well as
good practical exposure to students in the relevant areas. It is intended to provide a
modern, industry -oriented education in Computer Engineering. It aims at producing
trained professionals who can successfully acquainted with the d emands of the industry
worldwide. They obtain skills and experience in up -to-date the knowledge to analysis,
design, implementation, validation, and documentation of computer software and
systems.
The revised syllabus is finalized through a brain storming session attended by Heads of
Departments or senior faculty from the Department of Computer Engineering of the
affiliated Institutes of the Mumbai University. The syllabus falls in line with the
objectives of affiliating University, AICTE, UGC, and various accreditation agencies by
keeping an eye on the technological developments, innovations, and industry
requirements.

The salient features of the revised syllabus are:
1. Reduction in credits to 170 is implemented to ensure that students have more
time for ext racurricular activities, innovations, and research.
2. The department Optional Courses will provide the relevant specialization
within the branch to a student.
3. Introduction of Skill Based Lab and Mini Project to showcase their talent by
doing innovative proje cts that strengthen their profile and increases the
chance of employability.
4. Students are encouraged to take up part of course through MOOCs platform
SWAYAM
We would like to place on record our gratefulness to the faculty, students, industry
experts and st akeholders for having helped us in the formulation of this syllabus.
Board of Studies in Computer Engineering
Prof. Sunil Bhirud : Chairman
Prof. Sunita Patil : Member
Prof. Leena Raga : Member
Prof. Subhash Shinde : Member
Prof. Meera Narvekar : Member
Prof. Suprtim Biswas : Member
Prof. Sudhir Sawarkar : Member
Prof. Dayanand Ingle : Member
Prof. Satish Ket : Member

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Program Structure for Third Year Computer Engineering
UNIVERSITY OF MUMBAI (With Effect from 2021 -2022)
Semester V
Course
Code Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract. Theory Pract . Total
CSC501 Theoretical Computer
Science 3 -- 3 -- 3
CSC5 02 Software Engineering 3 -- 3 3
CSC503 Computer Network 3 -- 3 -- 3
CSC504 Data Warehousing &
Mining 3 -- 3 -- 3
CSDLO501 x Department Level
Optional Course - 1 3 -- 3 -- 3
CSL5 01 Software Engineering
Lab -- 2 -- 1 1
CSL5 02 Computer Network Lab -- 2 -- 1 1
CSL5 03 Data Warehousing &
Mining Lab -- 2 -- 1 1
CSL504 Professional Comm . &
Ethics II -- 2*+2 -- 2 2
CSM501 Mini Project: 2 A -- 4$ -- 2 2
Total 15 14 15 07 22
Course
Code Course Name Examination Scheme
Theory Term
Work Pract
&oral Total
Internal
Assessment End
Sem
Exam Exam.
Duration
(in Hrs)
Test
1 Test
2 Avg
CSC501 Theoretical Computer
Science 20 20 20 80 3 25 -- 125
CSC5 02 Software Engineering 20 20 20 80 3 -- -- 100
CSC503 Computer Network 20 20 20 80 3 -- -- 100
CSC504 Data Warehousing &
Mining 20 20 20 80 3 -- -- 100
CSD LO501 x Department Level
Optional Course -1 20 20 20 80 3 -- -- 100
CSL5 01 Software Engineering Lab -- -- -- -- -- 25 25 50
CSL5 02 Computer Network Lab -- -- -- -- -- 25 25 50
CSL5 03 Data Warehousing &
Mining Lab -- -- -- -- -- 25 25 50
CSL504 Professional Comm. &
Ethics II -- -- -- -- -- 50 -- 50
CSM501 Mini Project : 2A -- -- -- -- -- 25 25 50
Total -- -- 100 400 -- 175 100 775
* Theory class to be conducted for full class and $ indicates workload of Learner (Not Faculty), students
can form groups with minimum 2(Two) and not more than 4(Four). Faculty Load: 1hour per week per
four groups.

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Program Structure for Third Year Computer Engineering
UNIVERSITY OF MUMBAI (With Effect from 2021 -2022 )
Semester VI
Course
Code Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract.
Tut. Theory Pract . Total
CSC601 System Programming &
Compiler Construction 3 -- 3 -- 3
CSC6 02 Cryptography & System
Security 3 -- 3 3
CSC603 Mobile Computing 3 -- 3 -- 3
CSC604 Artificial Intelligence 3 -- 3 -- 3
CSDL O601x Department Level Optional
Course -2 3 -- 3 -- 3
CSL6 01 System Programming &
Compiler Construction Lab -- 2 -- 1 1
CSL6 02 Cryptography & System
Security Lab -- 2 -- 1 1
CSL6 03 Mobile Computing Lab -- 2 -- 1 1
CSL604 Artificial Intelligence Lab -- 2 -- 1 1
CSL605 Skill base Lab Course:
Cloud Computing -- 4 -- 2 2
CSM601 Mini Project Lab: 2B -- 4$ -- 2 2
Total 15 16 15 08 23
Course
Code Course Name Examination Scheme
Theory Term
Work Pract.
&oral Total
Internal Assessment End
Sem
Exa
m Exam.
Duration
(in Hrs)
Test
1 Test
2 Avg
CSC601 System Programming &
Compiler Construction 20 20 20 80 3 -- -- 100
CSC6 02 Cryptography & System
Security 20 20 20 80 3 -- -- 100
CSC603 Mobile Computing 20 20 20 80 3 -- -- 100
CSC604 Artificial Intelligence 20 20 20 80 3 -- -- 100
CSDLO 601x Department Level Optional
Course -2 20 20 20 80 3 -- -- 100
CSL6 01 System Programming &
Compiler Construction Lab -- -- -- -- -- 25 25 50
CSL6 02 Cryptography & System
Security Lab -- -- -- -- -- 25 -- 25
CSL6 03 Mobile Computing Lab -- -- -- -- -- 25 - 25
CSL604 Artificial Intelligence Lab 25 25 50
CSL605 Skill base Lab Course:
Cloud Computing -- -- -- -- -- 50 25 75
CSM601 Mini Project :2B -- -- -- -- -- 25 25 50
Total -- -- 100 400 -- 175 100 775

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Program Structure for Computer Engineering
UNIVERSITY OF MUMBAI (With Effect from 2021 -2022)
Department Optional Courses
Department Level
Optional Courses Semester Code & Course

Department Level
Optional Course -1
V CSDLO5011: Probabilistic Graphical
Models
CSDLO5012: Internet Programming
CSDLO5013: Advance Data base
Management System

Department Level
Optional Course -2
VI CSDLO6011: Internet of Things
CSDLO6012: Digital Signal & Image
Processing
CSDLO6013: Quantitative Analysis













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Course Code Course Name Credits
CSC501 Theoretical Computer Science 3

Prerequisite: Discrete Structures
Course Objectives:
1. Acquire conceptual understanding of fundamentals of grammars and languages.
2. Build concepts of theoretical design of deterministic and non -deterministic finite
automata and push down automata.
3. Develop understanding of different types of Turing machines and applications.
4. Understand the concept of Undecidability.
Course Outcomes: At the end of the course, the students will be able to
1. Understand concepts of Theoretical Computer Science, difference and equivalence
of DFA and NFA , languages described by finite automata and regular expressions.
2. Design Context free grammer, pushdown automata to recognize the language.
3. Develop an understanding of computation through Turing Machine.
4. Acquire fundamental understanding of decidability and undecidability.

Module
No. Unit
No. Topics Theory
Hrs.
1.0 Basic Concepts and Finite Automata 09
1.1 Importance of TCS, Alphabets, Strings, Languages, Closure
properties, Finite Automata (FA) and Finite State machine
(FSM).
1.2 Deterministic Finite Automata (DFA) and Nondeterministic
Finite Automata (NFA): Definitions, transition diagrams and
Language recognizers, Equivalence between NFA with and
without ε - transitions, NFA to DFA Conversion, Minimization
of DFA, FSM with output: Moore and Mealy machines,
Applications and limitations of FA.
2.0 Regular Expressions and Languages 07
2.1 Regular Expression (RE),Equivalence of RE and FA, Arden‘s
Theorem, RE Applications
2.2 Regular Language (RL), Closure properties of RLs, Decision
properties of RLs, Pumping lemma for RLs.
3.0 Grammars 08
3.1 Grammars and Chomsky hierarchy
3.2 Regular Grammar (RG), Equivalence of Left and Right
linear grammar, Equivalence of RG and FA.

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3.3 Context Free Grammars (CFG)
Definition, Sentential forms, Leftmost and Rightmost
derivations, Parse tree, Ambiguity, Simplification and
Applications, Normal Forms: Chomsky Normal Forms
(CNF) and Greibach Normal Forms (GNF), C ontext Free
language ( CFL) - Pumping lemma, Closure properties.
4.0 Pushdown Automata(PDA) 04
4.1 Definition, Language of PDA,PDA as generator, decider and
acceptor of CFG, Deterministic PDA , Non -Deterministic
PDA, Application of PDA.
5.0 Turing Machine (TM) 09
5.1 Definition, Design of TM as generator, decider and acceptor,
Variants of TM: Multitrack, Multitape, Universal TM,
Applications, Power and Limitations of TMs.
6.0 Undecidability 02
6.1 Decidability and Undecidability , Recursive and Recursively
Enumerable Languages, Halting Problem, Rice‘s Theorem,
Post Correspondence Problem.
Total 39

Text Books:
1. John E. Hopcroft, Rajeev Motwani, Jeffery D. Ullman, “Introduction to Automata
Theory, Languages and Computation” , 3rd Edition, Pearson Education, 2008.
2. Michael Sipser, “Theory of Computation” , 3rd Edition, Cengage learning. 2013.
3. Vivek Kulkarni, “Theory of Computation”, Illustrated Edition, Oxford University
Press, (12 April 2013) India.
Reference Books:
1. J. C. Martin, “Introduction to Languages and the Theory of Computation ”, 4th Edition,
Tata McGraw Hill Publication, 2013.
2. Kavi Mahesh, “Theory of Computation: A Problem Solving Approach” , Kindle
Edition, Wiley -India, 2011.

Assessment:
Internal Assessment:
1. Assessment consists of two class tests of 20 marks each.
2. The first class test is to be conducted when approx. 40% syllabus is completed and
second class test when additional 40% syllabus is completed.
3. Duration of each test shall be one hour.
Term work:
1. Term Work should consist of at least 06 assignments (at least one assignment on
each module).

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2. Assignment (best 5 assignments) 20 marks
Attendance 5 marks
3. It is recommended to use JFLAP software (www.jflap.org) for better teaching and
learning processes.

Useful Links:
1. www.jflap.org
2. https://nptel.ac.in/courses/106/104/106104028/
3. https://nptel.ac.in/courses/106/104/106104148/

















End Semester Theory Examination :
1. Question paper will comprise of 6 questions, each carrying 20 marks.
2. The students need to solve total 4 questions.
3. Question No.1 will be compulsory and based on entire syllabus.
4. Remaining questions (Q.2 to Q.6) will cover all the modules of syllabus.

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Course Code: Course Title Credit
CSC502 Software Engineering 3

Prerequisite: Object Oriented Programming with Java , Python Programming
Course Objectives:
1 To provide the knowledge of software engineering discipline.
2 To apply analysis, design and testing principles to software project development.
3 To demonstrate and evaluate real world software projects.
Course Outcomes : On successful completion of course, learners will be able to:
1 Identify requirements & assess the process models.
2 Plan, schedule and track the progress of the projects.
3 Design the software projects.
4 Do testing of software project .
5 Identify risks, manage the change to assure quality in software projects.


Module Content Hrs
1 Introduction To Software Engineering and Process Models 7
1.1 Software Engineering -process framework, the Capability Maturity Model
(CMM), Advanced Trends in Software Engineering
1.2 Prescriptive Process Models: The Waterfall, Incremental
Process Models, Evolutionary Process Models: RAD & Spiral
1.3 Agile process model: Extreme Programming (XP), Scrum, Kanban
2 Software Requirements Analysis and Modeling 4
2.1 Requirement Engineering, Requirement Modeling, Data flow diagram,
Scenario based model
2.2 Software Requirement Specification document format(IEEE)
3 Software Estimation Metrics 7
3.1 Software Metrics, Software Project Estimation (LOC, FP, COCOMO II )
3.2 Project Scheduling & Tracking
4 Software Design 7
4.1 Design Principles & Concepts
4.2 Effective Modular Design, Cohesion and Coupling, Architectural design
5 Software Testing 7
5.1 Unit testing, Integration testing, Validation testing, System testing
5.2 Testing Techniques, white -box testing: Basis path, Control structure testing
black -box testing : Graph based, Equivalence, Boundary Value
5.3 Types of Software Maintenance, Re-Engineering, Reverse Engineering
6 Software Configuration Management, Quality Assurance and
Maintenance 7
6.1 Risk Analysis & Management : Risk Mitigation, Monitoring and
Management Plan (RMMM).
6.2 Quality Concepts and Software Quality assurance Metrics, Formal Technical
Reviews, Software Reliability
6.3 The Software Configuration Management (SCM) ,Version Control and
Change Control
39

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Textbooks:
1 Roger Pressman , “Software Engineering: A Practitioner‘s Approach” , 9th edition ,
McGraw -Hill Publications , 2019
2 Ian Sommerville , “Software Engineering” , 9th edition, Pearson Education, 2011
3 Ali Behfrooz and Fredeick J. Hudson , "Software Engineering Fundamentals" , Oxford
University Press, 1997
4 Grady Booch, James Rambaugh, Ivar Jacobson , “The unified modeling language user
guide” , 2nd edition , Pearson Education, 2005
References:
1 Pankaj Jalote , "An integrated approach to Software Engineering" , 3rd edition, Springer,
2005
2 Rajib Mall , "Fundamentals of Software Engineering" , 5th edition, Prentice Hall India, 2014
3 Jibitesh Mishra and Ashok Mohanty , “Software Engineering” , Pearson , 2011
4 Ugrasen Suman , “Software Engineering – Concepts and Practices” , Cengage Learning,
2013
5 Waman S Jawadekar, “Software Engineering principles and practice” , McGraw Hill
Education , 2004


Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first-class test is to be conducted when
approx. 40% syllabus is completed and the second -class test when an additional 40% syllabus is
completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise a total of six questions.
2 All question carries equal marks
3 Only Four questions need to be solved.
4 In question paper weightage of each module will be proportional to number of respective
lecture hours as mentioned in the syllabus.

Useful Links
1 https://nptel.ac.in/courses/106/105/106105182/
2 https://onlinecourses.nptel.ac.in/noc19_cs69/preview
3 https:/ /www .mooc -list.com/course/software -engineering -introduction -edx














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Course Code: Course Title Credit
CSC503 Computer Network 3

Prerequisite: None
Course Objectives:
1 To introduce concepts and fundamentals of data communication and computer networks.
2 To explore the inter -working of various layers of OSI.
3 To explore the issues and challenges of protocols design while delving into TCP/IP protocol
suite.
4 To assess the strengths and weaknesses of various routing algorithms.
5 To understand various transport layer and application layer protocols.
Course Outcomes: On successful completion of course, learner will be able to
1 Demonstrate the concepts of data communication at physical layer and compare ISO - OSI
model with TCP/IP model.
2 Explore different design issues at data link layer.
3 Design the network using IP addressing and sub netting / supernetting schemes .
4 Analyze transport layer protocols and congestion control algorithms.
5 Explore protocols at application layer

Module Content Hrs
1 Introduction to Networking 4
1.1 Introduction to computer network, network application, network
software and hardware components (Interconnection networking devices),
Network topology, protocol hierarchies, design issues for the layers,
connection oriented and connectionless se rvices
1.2 Reference models: Layer details of OSI, TCP/IP models. Communication
between layers.
2 Physical Layer 3
2.1 Introduction to Communication Electromagnetic Spectrum
2.2 Guided Transmission Media: Twisted pair, Coaxial, Fiber optics.
3 Data Link Layer 8
3.1 DLL Design Issues (Services, Framing, Error Control, Flow Control),
Error Detection and Correction(Hamming Code, CRC, Checksum) ,
Elementary Data Link protocols , Stop and Wait, Sliding Window(Go
Back N, Selective Repeat)

3.2 Medium Access Control sublayer
Channel Allocation problem, Multiple access Protocol( Aloha, Carrier
Sense Multiple Access (CSMA/CD)
4 Network layer 12
4.1 Network Layer design issues, Communication Primitives: Unicast,
Multicast, Broadcast. IPv4 Addressing (classfull and classless),
Subnetting, Supernetting design problems ,IPv4 Protocol, Network
Address Translation (NAT), IPv6

4.2 Routing algorithms : Shortest Path (Dijkastra‘s), Link state routing,
Distance Vector Routing
4.3 Protocols - ARP,RARP, ICMP, IGMP

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4.4 Congestion control algorithms: Open loop congestion control, Closed
loop congestion control, QoS parameters, Token & Leaky bucket algorithms
5 Transport Layer 6
5.1 The Transport Service : Transport service primitives, Berkeley Sockets,
Connection management (Handshake), UDP, TCP, TCP state transition,
TCP timers
5.2 TCP Flow control (sliding Window), TCP Congestion Control: Slow Start
6 Application Layer 6
6.1 DNS: Name Space, Resource Record and Types of Name Server. HTTP,
SMTP, Telnet, FTP, DHCP

Textbooks:
1 A.S. Tanenbaum, Computer Networks ,4th edition Pearson Education
2 B.A. Forouzan, Data Communications and Networking , 5th edition, TMH
3 James F. Kurose, Keith W. Ross, Computer Networking, A Top-Down Approach
Featuring the Internet ,6th edition, Addison Wesley
References:
1 S.Keshav, An Engineering Approach To Computer Networking , Pearson
2 Natalia Olifer & Victor Olifer, Computer Networks: Principles, Technologies &
Protocols for Network Design , Wiley India, 2011.
3 Larry L.Peterson, Bruce S.Davie, Computer Networks: A Systems Approach , Second
Edition , The Morgan Kaufmann Series in Networking

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first class test is to be conducted
when approx. 40% syllabus is completed and second class test when additional 40% syllabus is
completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
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 module 3)
4 Only Four question need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.

Useful Links
1 https://www.netacad.com/courses/networking/networking -essentials
2 https://www.coursera.org/learn /computer -networking
3 https://nptel.ac.in/courses/106/105/106105081
4 https://www.edx.org/course/introduction -to-networking




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Course Code: Course Title Credit
CSC504 Data Warehousing and Mining 3

Prerequisite: Data base Concepts
Course Objectives:
1. To identify the significance of Data Warehousing and Mining.
2. To analyze data, choose relevant models and algorithms for respective applications.
3. To study web data mining.
4. To develop research interest towards advances in data mining.
Course Outcomes: At the end of the course, the student will be able to
1. Understand data warehouse fundamentals and design data warehouse with dimensional
modelling and apply OLAP operations.
2. Understand data mining principles and perform Data preprocessing and Visualization.
3. Identify appropriate data mining algorithms to solve real world problems.
4. Compare and evaluate different data mining techniques like classification, prediction, clustering
and association rule mining
5. Describe complex information and social networks with respect to web mining.

Module Content Hrs
1 Data Warehousing Fundamentals 8
Introduction to Data Warehouse, Data warehouse architecture, Data warehouse
versus Data Marts, E -R Modeling versus Dimensional Modeling, Information
Package Diagram, Data Warehouse Schemas; Star Schema, Snowflake Schema,
Factless Fact Table, Fact Constel lation Schema. Update to the dimension tables.
Major steps in ETL process, OLTP versus OLAP, OLAP operations: Slice, Dice,
Rollup, Drilldown and Pivot.
2 Introduction to Data Mining, Data Exploration and Data Pre-processing 8
Data Mining Task Primitives, Architecture, KDD process, Issues in Data Mining,
Applications of Data Mining, Data Exploration: Types of Attributes, Statistical
Description of Data, Data Visualization , Data Preprocessing: Descriptive data
summarization, Clea ning, Integration & transformation, Data reduction, Data
Discretization and Concept hierarchy generation .
3 Classification 6
Basic Concepts, Decision Tree Induction, Naïve Bayesian Classification,
Accuracy and Error measures, Evaluating the Accuracy of a Classifier: Holdout
& Random Subsampling, Cross Validation, Bootstrap .
4 Clustering 6
Types of data in Cluster analysis , Partitioning Methods ( k-Means, k-Medoids),
Hierarchical Methods (Agglomerative, Divisive) .
5 Mining frequent patterns and associations 6
Market Basket Analysis, Frequent Item sets, Closed Item sets, and Association
Rule , Frequent Pattern Mining , Apriori Algorithm, Association Rule Generation,
Improving the Efficiency of Apriori, Mining Frequent Itemsets without candidate
generation, Introduction to Mining Multilevel Association Rules and Mining
Multidimensional Association Rules.

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6 Web Mining 5
Introduction , Web Content Mining: Crawlers, Harvest System, Virtual Web View,
Personalization, Web Structur e Mining: Page Rank , Clever, Web Usage Mining .

Textbooks :
1 Paulraj Ponniah, “ Data Warehou sing: Funda mentals for IT Professionals”, Wiley India.
2 Han, Kamber, “Data Mining Concepts and Techniques” , Morgan Kaufmann 2nd edition .
3 M.H. Dunham, “Data Mining Introductory and Advanced Topics” , Pearson Education.
References:
1 Reema Theraja, “Data warehou sing”, Oxford University Press 2009 .
2 Pang -Ning Tan, Michael Steinbach and Vipin Kum ar, “Introduction to Data Mining” ,
Pearson Publisher 2nd edition .
3 Ian H. Witten , Eibe Frank and Mark A. Hall, “Data Mining” , Morgan Kaufmann 3rd edition .

Assessment:
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first -class test is to be conducted when
approx. 40% syllabus is completed and second -class test when additional 40% syllabus is
completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
3 Questions will be mixed in nature (for example , If Q.2 part (a) from module 3 then part (b)
can be from any module other than module 3)
4 Only Four question s need to be solved.
5 In question paper weightage of each module will be proportional to the number of respective
lecture hours as mention ed in the syllabus.
Useful Links
1 https://onlinecourses.nptel.ac.in/noc20_cs12/preview
2 https://www.coursera.org/specializations/data -mining









Page 20

Course Code: Course Title Credit
CSD LO501 1 Probabilistic Graphical Models 3

Prerequisite: Engineering Mathematics, Discrete Structure
Course Objectives:
1 To give comprehensive introduction of probabilistic graphical models
2 To make inferences, learning, actions and decisions while applying these models
3 To introduce real -world trade -offs when using probabilistic graphical models in practice
4 To develop the knowledge and skills necessary to apply these models to solve real world
problems.
Course Outcomes: At the end of the course, the student will be able to
1 Understand basic concepts of probabilistic graphical modelling .
2 Model and extract inference from various graphical models like Bayesian Networks, Markov
Models
3 Perform learning and take actions and decisions using probabilistic graphical models
4 Represent real world problems using graphical models; design inference algorithms; and learn
the structure of the graphical model from data.
5 Design real life applica tions using probabilistic graphical models.

Module Content Hrs
1. Introduction to Probabilistic Graphical Modeling 5
1.1 Introduction to Probability Theory:
Probability Theory, Basic Concepts in Probability, Random
Variables and Joint Distribution, Independence and Conditional
Independence, Continuous Spaces, Expectation and Variances
1.2 Introduction to Graphs: Nodes and Edges, Subgraphs, Paths and
Trails, Cycles and Loops
1.3 Introduction to Probabilistic Graph Models: Bayesian Network,
Markov Model, Hidden Markov Model
1.4 Applications of PGM
2. Bayesian Network Model and Inference 10
2.1 Directed Graph Model: Bayesian Network -Exploiting Independence
Properties, Naive Bayes Model, Bayesian Network Model,
Reasoning Patterns, Basic Independencies in Bayesian Networks,
Bayesian Network Semantics, Grap hs and Distributions. Modelling :
Picking variables, Picking Structure, Picking Probabilities , D-
separation
2.2 Local Probabilistic Models: Tabular CPDs, Deterministic CPDs,
Context Specific CPDs, Generalized Linear Models.

Page 21

2.3 Exact inference variable elimination: Analysis of Complexity,
Variable Elimination, Conditioning, Inference with Structured CPDs.
3. Markov Network Model and Inference 8
3.1 Undirected Graph Model : Markov Model -Markov Network,
Parameterization of Markov Network, Gibb's distribution, Reduced
Markov Network, Markov Network Independencies, From
Distributions to Graphs, Fine Grained Parameterization, Over
Parameterization
3.2 Exact inference variable elimination: Graph Theoretic Analysis for
Variable Elimination, Conditioning
4. Hidden Markov Model and Inference 6
4.1 Template Based Graph Model : HMM - Temporal Models, Template
Variables and Template Factors, Directed Probabilistic Models,
Undirected Representation, Structural Uncertainty.
5. Learning and Taking Actions and Decisions 6
5.1 Learning Graphical Models: Goals of Learning, Density Estimation,
Specific Prediction Tasks, Knowledge Discovery. Learning as
Optimization: Empirical Risk, over fitting, Generalization,
Evaluating Generalization Performance, Selecting a Learning
Procedure, Goodness of fit, Learning Tasks. Parameter Estimation:
Maximum Likelihood Estimation, MLE for Bayesian Networks
5.2 Causality: Conditioning and Intervention, Correlation and Causation,
Causal Models, Structural Causal Identifiability, Mechanisms and
Response Variables, Learning Causal Models. Utilities and
Decisions: Maximizing Expected Utility, Utility Curves, Utility
Elicitation. Structured Decision Problems: Decision Tree
6. Applications 4
6.1 Application of Bayesian Networks: Classification, Forecasting,
Decision Making
6.2 Application of Markov Models: Cost Effectiveness Analysis,
Relational Markov Model and its Applications, Application in
Portfolio Optimization
6.3 Application of HMM: Speech Recognition, Part of Speech Tagging,
Bioinformatics.

Textbooks:
1. Daphne Koller and Nir Friedman , "Probabilistic Graphical Models: Principles
and Techniques” , Cambridge, MA: The MIT Press, 2009 (ISBN 978 -0-262-0139 -
2).
2. David Barber, "Bayesian Reasoning and Machine Learning" , Cambridg e
University Press, 1st edition, 2011.
References:

Page 22

1. Finn Jensen and Thomas Nielsen , "Bayesian Networks and Decision Graphs
(Information Science and Statistics ) ", 2nd Edition, Springer, 2007.
2. Kevin P. Murphy, "Machine Learning: A Probabilistic Perspective" , MIT Press,
2012.
3. Martin Wainwright and Michael Jordan, M., "Graphical Models, Exponential
Families, and Variational Inference ", 2008.

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first class test is to be m
onducted when approx. 40% syllabus is completed and second class test when additional
40% syllabus is completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1. Question paper will comprise of total six questions.
2. All question carries equal marks
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 module 3)
4. Only Four question need to be solved.
5. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
Useful Links
1. https://www.coursera.org/specializations/probabilistic -graphical -models
2. https://www.mooc -list.com/tags/probabilistic -graphical -models
3. https://scholarship.claremont.edu/cgi/viewcontent.cgi?referer=https://www.google.c
om/&httpsredir=1&article=2690 &context=cmc_theses
4. https://www.upgrad.com/blog/bayesian -networks/
5. https://www.utas.edu.au/__data/assets/pdf_file/0009/588474/TR_14_BNs_a_resour
ce_guide.pdf
6. https://math.libretexts.org/Bookshelves/Applied_Mathematics/Book%3A_Applied_
Finite_Mathematics_(Sekhon_and_Bloom)/10%3A_Markov_Chains/10.02%3A_A
pplications_of_Mar kov_Chains/10.2.01%3A_Applications_of_Markov_Chains_(E
xercises)
7. https://link.springer.com/chapter/10.1007/978 -3-319-43742 -2_24
8. https://homes.cs.washington.edu/~pedrod/papers/kdd02a.pdf
9. https://core.ac.uk/download/pdf/191938826.pdf
10. https://cs.brown.edu/research/pubs/theses/ugrad/2005/dbooksta.pdf

Page 23

11. https://web.ece.ucsb.edu/Faculty/Rabiner/ece259/Reprints/tutorial%20on%20hmm
%20and%20applications.pdf
12. https://mi.eng.cam.ac.uk/~mjfg/mjfg_NOW.pdf
13. http://bioinfo.au.tsinghua.edu.cn/member/jgu/pgm/materials/Chapter3 -
LocalProbabilisticModels.pdf

Suggested List of Experiments:
Sr. No Experiment
1. Experiment on Probability Theory
2. Experiment on Graph Theory
3. Experiment on Bayesian Network Modelling
4. Experiment on Markov Chain Modeling
5. Experiment on HMM
6. Experiment on Maximum Likelihood Estimation
7. Decision Making using Decision Trees
8. Learning with Optimization
** Suggestion: Laboratory work based on above syllabus can be incorporated along with
mini project in CSM501: Mini -Project.

















Page 24

Course Code: Course Title Credit
CSD LO501 2 Internet Programming 3

Prerequisite: Data Structures , Programming Languages - JAVA, Python
Course Objectives:
1 To get familiar with the basics of Internet Programming.
2 To acquire knowledge and skills for creation of web site considering both client and server -
side programming
3 To gain ability to develop responsive web applications and explore different web extensions
and web services standards
4 To learn characteristics of RIA and React J s
Course Outcomes:
1 Implement interactive web page(s) using HTML and CSS.
2 Design a responsive web site using JavaScript and demonstrate database connectivity using
JDBC
3 Demonstrate Rich Internet Application using Ajax and d emonstrate and differentiate various
Web Extensions
4 Demonstrate web application using Reactive Js

Module Content Hrs
1 Introduction to Web Technology 10
1.1 Web Essentials : Clients, Servers and Communication, The Internet,
Basic Internet protocols, World wide web, HTTP Request Message,
HTTP Response Message, Web Clients, Web Servers
HTML5 – fundamental syntax and semantics, Tables, Lists, Image ,
HTML5 control elements, Semantic elements, Drag and Drop, Audio –
Video controls
CSS3 – Inline, embedded and external style sheets – Rule cascading,
Inheritance, Backgrounds, Border Images, Colors, Shadows, Text ,
Transformations, Transitions, Animation, Basics of Bootstrap.
2 Front End Development 7
2.1 Java Script: An introduction to JavaScript –JavaScri pt DOM Model -
Date and Objects -Regular Expressions - Exception Handling -
Validation -Built -in objects -Event Handling, DHTML with JavaScript -
JSON introduction – Syntax – Function Files – Http Request –SQL.
3. Back End Development 7
3.1 Servlets : Java Servlet Architecture, Servlet Life Cycle, Form GET and
POST actions, Session Handling, Understanding Cookies, Installing
and Configuring Apache Tomcat Web Server,
Database Connectivity : JDBC perspectives, JDBC program example
JSP: Understanding Java Server Pages, JSP Standard Tag Library
(JSTL), Creating HTML forms by embedding JSP code.
4 Rich Internet Application (RIA) 4
4.1 Characteristics of RIA,
Introduction to AJAX : AJAX design basics, AJAX vs Traditional
Approach, Rich User Interface using Ajax, jQuery framework with
AJAX.
5 Web Extension: PHP and XML 6
5.1 XML –DTD (Document Type Definition), XML Schema, Document
Object Model, Presenting XML, Using XML Parsers: DOM and SAX,
XSL -eXtensible Stylesheet Language

Page 25

5.2 Introduction to PHP - Data types, control structures, built in functions ,
building web applications using PHP - tracking users, PHP and
MySQLdatabase connectivity with example.
6 React js 5
6.1 Introduction, React features, App “Hello World” Application,
Introduction to JSX, Simple Application using JSX.
39

Textbooks:
1 Ralph Moseley, M.T. Savliya, “Developing Web Applications”, Willy India, Second
Edition, ISBN: 978 -81-265-3867 -6
2 “Web Technology Black B ook”, Dremtech Press, First Edi tion, 978 -7722 -997
3 Robin Nixon, "Learning PHP, MySQL, JavaScript, CSS & HTML5" Third Edition,
O'REILLY , 2014 .
(http://www.ebooksbucket.com/uploads/itprogramming/javascr ipt/Learning_PHP_MySQ
L_Javascri pt_CSS_HTML5__Robin_Nixon_3e.pdf)
4 Dana Moore, Raymond Budd, Edward Benson, Professional Rich Internet Applications:
AJAX and Beyond Wiley publications. https://ebooks -it.org/0470082801 -ebook.htm
5. Alex Banks and Eve Porcello, Learning React Functional Web Development with React
and Redux,OREILLY, First Edition
References:
1 Harvey & Paul Deitel& Associates, H arvey Deitel and Abbey Deitel, Internet and World
Wide Web - How To Program , Fifth Edition, Pearson Education, 2011.
2 Achyut S Godbole and Atul Kahate, ―Web Technologies , Second Edition, Tata McGraw
Hill, 2012.
3 Thomas A Powell, Fritz Schneider, ―Jav aScript: The Complete Reference , Third Edition,
Tata McGraw Hill, 2013
4 David Flanagan, ―JavaScript: The Definitive Guide, Sixth Edition , O'Reilly Media, 2011
5 Steven Holzner ―The Complete Reference - PHP, Tata McGraw Hill, 2008
6 Mike Mcgrath―PHP & MySQL in easy Steps , Tata McGraw Hill, 2012.

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The firstclass test is to be conducted
when approx. 40% syllabus is completed and the secondclass test when an additional 40%
syllabus is completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise a total of six questions.
2 All question carries equal marks
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 module 3)
4 Only Four questions need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mentioned in the syllabus.

Useful Links
1 https://books.goalkicker.com/ReactJSBook/
2 https://www.guru99.com/reactjs -tutorial.html
3 www.nptelvideos.in
4 www.w3schools.com
5 https://spoken -tutorial.org/
6 www.coursera.org
The following list can be used as a guideline for mini project:

Page 26

1 Create Simple web page using HTML5
2 Design and Implement web page using CSS3 and HTML5
3 Form Design an d Client -Side Validation using: a. Javascript and HTML5 , b. Javascript
and Jquery
4 Develop interactive web pages using HTML 5 with JDBC database connectivity
5 Develop simple web page using PHP
6 Develop interactive web pages using PHP with database connectivity MYSQL
7 Develop XML web page using DTD, XSL
8 Implement a web page using Ajax and PHP
9 Case study based on Reactive js
10 Installation of the React DOM library.
* Suggestion: Laboratory work based on above syllabus can be incorporate d as mini
project in CSM501: Mini -Project.

Page 27

Course Code: Course Title Credit
CSD LO501 3 Advance Database Management System 3

Prerequisite: Database Management System
Course Objectives:
1 To provide insights into distributed database designing
2 To specify the various approaches used for using XML and JSON technologies.
3 To apply the concepts behind the various types of NoSQL databases and utilize it for Mongodb
4 To learn about the trends in advance databases
Course Outcomes: After the successful completion of this course learner will be able to:
1 Design distributed database using the various techniques for query processing
2 Measure query cost and perform distributed transaction management
3 Organize the data using XML and JSON database for better interoperability
4 Compare different types of NoSQL databases
5 Formulate NoSQL queries using Mongodb
6 Describe various trends in advance databases through temporal, graph based and spatial
based databases

Module Content Hrs
1 Distributed Databases 3
1.1 Introduction, Distributed DBMS Architecture, Data Fragmentation,
Replication and Allocation Techniques for Distributed Database Design.

2 Distributed Database Handling 8
2.1 Distributed Transaction Management – Definition, properties, types,
architecture
Distributed Query Processing - Characterization of Query Processors,
Layers/ phases of query processing.
2.2 Distributed Concurrency Control - Taxonomy, Locking based, Basic TO
algorithm,
Recovery in Distributed Databases: Failures in distributed database, 2PC
and 3PC protocol.

3 Data interoperability – XML and JSON 6
3.1 XML Databases: Document Type Definition, XML Schema, Querying and
Transformation: XPath and XQuery.
3.2 Basic JSON syntax, (Java Script Object Notation),JSON data types,
Stringifying and parsing the JSON for sending & receiving, JSON Object
retrieval using key -value pair and JQuery, XML Vs JSON

4 NoSQL Distribution Model 10
4.1 NoSQL database concepts: NoSQL data modeling, Benefits of NoSQL,
comparison between SQL and NoSQL database system.
4.2 Replication and sharding, Distribution Models Consistency in distributed
data, CAP theorem, Notion of ACID Vs BASE, handling Transactions,
consistency and eventual consistency
4.3 Types of NoSQL databases: Key -value data store, Document database and
Column Family Data store, Comparison of NoSQL databases w.r.t CAP
theorem and ACID properties.

5 NoSQL using MongoDB 6

Page 28

5.1 NoSQL using MongoDB: Introduction to MongoDB Shell, Running the
MongoDB shell, MongoDB client, Basic operations with MongoDB shell,
Basic Data Types, Arrays, Embedded Documents
5.2 Querying MongoDB using find( ) functions, advanced queries using logical
operators and sorting, simple aggregate functions, saving and updating
document.
MongoDB Distributed environment: Concepts of replication and horizonal
scaling through sharding in MongoDB

6 Trends in advance databases 6
6.1 Temporal database: Concepts, time representation, time dimension,
incorporating time in relational databases.
6.2 Graph Database: Introduction, Features, Transactions, consistency,
Availability, Querying, Case Study Neo4J
6.3 Spatial database: Introduction, data types, models, operators and queries
39

Textbooks:
1 Korth, Siberchatz,Sudarshan, “Database System Concepts”, 6thEdition, McGraw Hill
2 Elmasri and Navathe, “Fundamentals of Database Systems”, 5thEdition, Pearson Education
3 Ozsu, M. Tamer, Valduriez, Patrick, “Principles of distributed database systems”,3rd Edition,
Pearson Education, Inc.
4 PramodSadalge, M artin Fowler, NoSQL Distilled: A Brief Guide to the Emerging World of
Polyglot Persistence , Addison Wesely/ P earson
5 Jeff Friesen , Java XML and JSON,Second Edition, 2019, après Inc.
References:
1 Peter Rob and Carlos Coronel,Database Systems Design , Implementation and Management ,
Thomson Learning, 5thEdition.
2 Dr. P.S. Deshpande, SQL and PL/SQL for Oracle 10g, Black Book, Dreamtech Press.
3 Adam Fowler, NoSQL for dummies, John Wiley & Sons, Inc.
4 Shashank Tiwari, Professional NOSQL, John Willy & Sons. Inc
5 Raghu Ramkrishnan and Johannes Gehrke, Database Management Systems, TMH
6 MongoDB Manual : https://docs.mongodb.com/manual

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first -class test is to be conducted
when approx. 40% syllabus is completed and second class test when additional 40% syllabus is
completed. Duration of each test shall be on e hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
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 module 3)
4 Only Four question need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.
NOTE: Suggested that in Mini Projects (CSM501) can be include d NoSQL databases for
implementation as a backend.


Page 29

Useful Links
1 https://cassandra.apache.org
2 https://www.mongodb.com
3 https://riak.com
4 https://neo4j.com
5 https://martinfowler.com/articles/nosql -intro -original.pdf

Page 30

Lab Code Lab Name Credit
CSL501 Software Engineering Lab 1

Prerequisite: Object Oriented Programming with Java , Python Programming
Lab Objectives:
1 To solve real life problems by applying software engineering principles
2 To impart state-of-the-art knowledge on Software Engineering
Lab Outcomes: On successful completion of laboratory experiments , learners will be able to :
1 Identify requirements and apply software process model to selected case study.
2 Develop architectural models for the selected case study.
3 Use computer -aided software engineering (CASE) tools.

Suggested List of Experiments - Assign the case study/project as detail statement of problem
to a group of two/three students . Laboratory work will be based on course syllabus with
minimum 10 experiments. Open source computer -aided software engineering (CASE) tools can
be used for performing the experiment.
Sr. No. Title of Experiment
1 Application of at least two traditional process models.
2 Application of the Agile process models.
3 Preparation of software requirement specification (SRS) document in IEEE format.
4 Structured data flow analysis.
5 Use of metrics to estimate the cost.
6 Scheduling & tracking of the project.
7 Write test cases for black box testing .
8 Write test cases for white box testing .
9 Preparation of Risk Mitigation, Monitoring and Management Plan (RMMM).
10 Version controlling of the project .


Term Work:
1 Term work should consist of 10 experiments.
2 Journal must include at least 2 assignments on content of theory and practical of “Software
Engineering”
3 The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minim um passing marks in term work.
4 Total 25 Marks (Experiments: 15 -marks, Attendance Theory & Practical: 05 -marks,
Assignments: 05 -marks)
Oral & Practical exam
Based on the entire syllabus of CSC502 and CSL501 syllabus


Page 31

Lab Code Lab Name Credit
CSL502 Computer Network Lab 1

Prerequisite: None
Lab Objectives:
1 To practically explore OSI layers and understand the usage of simulation tools.
2 To analyze, specify and design the topological and routing strategies for an IP based
networking infrastructure.
3 To identify the various issues of a packet transfer from source to destination, and how they
are resolved by the various existing protocols
Lab Outcomes: On successful completion of lab, learner will be able to
1 Design and setup networking environment in Linux.
2 Use Network tools and simulators such as NS2, Wireshark etc. to explore networking
algorithms and protocols.
3 Implement programs using core programming APIs for understanding networking concepts.

Suggested List of Ex periments
Sr. No. Title of Experiment
1. Study of RJ45 and CAT6 Cabling and connection using crimping tool.
2. Use basic networking commands in Linux (ping, tracert, nslookup, netstat, ARP,
RARP, ip, ifconfig, dig, route )
3. Build a simple network topology and configure it for static routing protocol using
packet tracer. Setup a network and configure IP addressing, subnetting, masking.
4. Perform network discovery using discovery tools (eg. Nmap, mrtg)
5. Use Wire shark to u nderstand the operation of TCP/IP layers:
● Ethernet Layer: Frame header, Frame size etc.
● Data Link Layer: MAC address, ARP (IP and MAC address binding)
● Network Layer: IP Packet (header, fragmentation), ICMP (Query and Echo)
● Transport Layer: TCP Ports, TCP h andshake segments etc.
● Application Layer: DHCP, FTP, HTTP header formats
6. Use simulator (Eg. NS2) to understand functioning of ALOHA, CSMA/CD.
7. Study and Installation of Network Simulator (NS3)
8. a. Set up multiple IP addresses on a single LAN.
b. Using nestat and route commands of Linux, do the following:
● View current routing table
● Add and delete routes
● Change default gateway
c. Perform packet filtering by enabling IP forwarding using IPtables in Linux.
9 Design VPN and Configure RIP/OSPF using Packet tracer.
10. Socket programming using TCP or UDP
11. Perform File Transfer and Access using FTP
12. Perform Remote login using Telnet server

Term Work:
1 Term work should consist of 10 experiments.
2 Journal must include at least 2 assignments on content of theory and practical of “Computer
Network”
3 The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
4 Total 25 Marks (Experiments: 15 -marks, Attendance Theory& Practical: 05 -marks,

Page 32

Assignments: 05 -marks)
Oral & Practical exam
Based on the entire syllabus of CSC503: Computer Network

Useful Links
1 https://www.netacad.com/courses/packet -tracer/introduction -packet -tracer
2 https://w ww.coursera.org/projects/data -forwarding -computer -networks
3 https://www.edx.org/course/ilabx -the-internet -masterclass


Page 33

Lab Code Lab Name Credit
CSL503 Data Warehousing and Mining Lab 1

Prerequisite: Data base Concepts
Lab Objectives:
1. Learn how to build a data warehouse and query it.
2. Learn about the data sets and data preprocessing.
3. Demonstrate the working of algorithms for data mining tasks such Classification ,
clustering , Association rule mining & Web mining
4. Apply the data mining techniques with varied input values for different parameters.
5. Explore open source software (like WEKA) to perform d ata mining tasks.
Lab Outcomes: At the end of the course, the student will be able to
1. Design data warehouse and perform various OLAP operations.
2. Implement data mining algorithms like classification.
3. Implement clustering algorithms on a given set of data sample.
4. Implement Association rule mining & web mining algorithm.

Suggested List of Experiments
Sr.
No. Title of Experiment
1 One case study on building Data warehouse/Data Mart
 Write Detailed Problem statement and design dimensional modelling (creation of star
and snowflake schema)
2 Implementation of all dimension table and fact table based on experiment 1 case study
3 Implementation of OLAP operations: Slice, Dice, Rollup, Drilldown and Pivot based on
experiment 1 case study
4 Implementation of Bayesian algorithm
5 Implementation of Data Discretization (any one) & Visualization (any one)
6 Perform data Pre -processing task and demonstrate Classification, Clustering, Association
algorithm on data sets using data mining tool (WEKA /R too l)
7 Implementation of Clustering algorithm (K -means/ K-medoids )
8 Implementation of any one Hierarchical Clustering method
9 Implementation of Association Rule Mining algorithm (Apriori)
10 Implementation of Page rank/HITS algorithm

Term Work:
1 Term work should consist of 10 experiments.
2 Journal must include at least 1 assignment on content of theory and practical of “ Data
Warehousing and Mining”
3 The final certification and acceptance of term work ensures that satisfactory performance
of laboratory work and minimum passing marks in term work.
4 Total 25 Marks (Experiments: 15 -marks, Attendance (Theory & Practical ): 05-marks,
Assignments: 05 -marks)
Oral & Practical exam
Based on the entire syllabus of CSC 504 : Data Warehousing and Mining

Page 34

Course Code Course Name Credit
CSL504 Professional Communication & Ethics II 02

Course Rationale: This curriculum is designed to build up a professional and ethical approach,
effective oral and written communication with enhanced soft skills. Through practical sessions, it
augments student's int eractive competence and confidence to respond appropriately and creatively to
the implied challenges of the global Industrial and Corporate requirements. It further inculcates the
social responsibility of engineers as technical citizens.
Course Objectives
1 To discern and develop an effective style of writing important technical/business documents.
2 To investigate possible resources and plan a successful job campaign.
3 To understand the dynamics of professional communication in the form of group discussions,
meetings, etc. required for career enhancement.
4 To develop creative and impactful presentation skills.
5 To analyze personal traits, interests, values, aptitudes and skills.
6 To understand the importance of integrity and develop a personal code of ethics.
Course Outcomes : At the end of the course, the student will be able to
1 Plan and prepare effective business/ technical documents which will in turn provide solid
foundation for their future managerial roles.
2 Strategize their personal and professional skills to build a professional image and meet
the demands of the industry.
3 Emerge successful in group discussions , meetings and result -oriented agreeable solutions in
group communication situations.
4 Deliver persuasive and professional presentations .
5 Develop creative thinking and interpersonal skills required for effective professional
communication.
6 Apply codes of ethical conduct , personal integrity and norms of organizational behaviour.

Module Contents Hours
1 ADVANCED TECHNICAL WRITING : PROJECT/PROBLEM
BASED LEARNING (PBL) 06
Purpose and Classification of Reports :
Classification on the basis of: Subject Matter (Technology, Accounting,
Finance, Marketing, etc.) , Time Interval (Periodic, One -time, Special) ,
Function (Informational, Analytical, etc.) , Physical Factors (Memorandum,
Letter, Short & Long)
Parts of a Long Formal Report : Prefatory Parts (Front Matter) , Report
Proper (Main Body) , Appended Parts (Back Matter)
Language and Style of Reports : Tense, Person & Voice of Reports ,
Numbering Style of Chapters, Sections, Figures, Tables and Equations ,
Referencing Styles in APA & MLA Format , Proofreading through Plagiarism
Checkers
Definition, Purpose & Types of Proposals : Solicited (in conformance with
RFP) & Unsolicited Proposals , Types (Short and Long proposals)
Parts of a Proposal : Elements , Scope and Limitations , Conclusion
Technical Paper Writing : Parts of a Technical Paper (Abstract, Introduction,
Research Methods, Findings and Analysis, Discussion, Limitations, Future
Scope and References) , Language and Formatting , Referencing in IEEE
Format

Page 35

2 EMPLOYMENT SKILLS 06
Cover Letter & Resume : Parts and Content of a Cover Letter , Difference
between Bio -data, Resume & CV , Essential Parts of a Resume , Types of
Resume (Chronological, Functional & Combination)
Statement of Purpose : Importance of SOP , Tips for Writing an Effective SOP
Verbal Aptitude Test : Mod elled on CAT, GRE, GMAT exams
Group Discussions : Purpose of a GD , Parameters of Evaluating a GD ,
Types of GDs (Normal, Case -based & Role Plays) , GD Etiquettes
Personal Interviews : Planning and Preparation , Types of Questions ,
Types of Interviews (Structured, Stress, Behavioural, Problem Solving &
Case -based) , Modes of Interviews: Face -to-face (One -to one and Panel)
Telephonic, Virtual
3 BUSINESS MEETINGS 02
Conducting Business Meetings : Types of Meetings , Roles and
Responsibilities of Chairperson, Secretary and Members , Meeting
Etiquette
Documentation : Notice , Agenda , Minutes
4 TECHNICAL/ BUSINESS PRESENTATIONS 02
Effective Presentation Stra tegies : Defining Purpose , Analyzing
Audience, Location and Event , Gathering, Selecting &Arranging
Material , structuring a Presentation , Making Effective Slides , Types of
Presentations Aids , Closing a Presentation , Platform skills
Group Presentations : Sharing Responsibility in a Team , Building the
contents and visuals together , Transition Phases
5 INTERPERSONAL SKILLS 08
Interpersonal Skills : Emotional Intelligence , Leadership & Motivation ,
Conflict Management & Negotiation , Time Management , Assertiveness ,
Decision Making
Start -up Skills : Financial Literacy , Risk Assessment , Data Analysis
(e.g. Consumer Behaviour, Market Trends, etc.)
6 CORPORATE ETHICS 02
Intellectual Property Rights : Copyrights , Trademarks , Patents ,
Industrial Designs , Geographical Indications , Integrated Circuits , Trade
Secrets (Undisclosed Information)
Case Studies : Cases related to Business/ Corporate Ethics


List of assignments : (In the form of Short Notes, Questionnaire/ MCQ Test, Role Play,
Case Study, Quiz, etc.)
Sr.
No. Title of Experiment
1 Cover Letter and Resume
2 Short Proposal
3 Meeting Documentation
4 Writing a Technical Paper/ Analyzing a Published Technical Paper
5 Writing a SOP
6 IPR
7 Interpersonal Skills
Note:
1 The Main Body of the project /book report should contain minimum 25 pages (excluding Front
and Back matter).

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2 The group size for the final report presentation should not be less than 5 students or exceed 7
students.
3 There will be an end –semester presentation based on the book report.
Assessment :
Term Work :
1 Term work shall consist of minimum 8 experiments.
2 The distribution of marks for term work shall be as follows:
Assignment : 10 Marks
Attendance : 5 Marks
Presentation slides : 5 Marks
Book Report (hard copy) : 5 Marks
3 The final certification and acceptance of term work ensures the satisfactory performance of
laboratory work and minimum passing in the term work.
Internal oral : Oral Examination will be based on a GD & the Project/Book Report presentation.
Group Discussion : 10 marks
Project Presentation : 10 Marks
Group Dynamics : 5 Marks
Books Recommended: Textbooks and Reference books
1 Arms, V. M. (2005). Humanities for the engineering curriculum: With selected
chapters from Olsen/Huckin: Technical writing and professional communication,
second edition . Boston, MA: McGraw -Hill.
2 Bovée, C. L., &Thill, J. V. (2021). Business communication today . Upper Saddle
River, NJ: Pearson.
3 Butterfield, J. (2017). Verbal communication: Soft skills for a digital workplace .
Boston, MA: Cengage Learning.
4 Masters, L. A., Wallace, H. R., & Harwood, L. (2011). Personal development for life
and work . Mason: South -Western Cengage Learning.
5 Robbins, S. P., Judge, T. A., & Campbell, T. T. (2017). Organizational behaviour .
Harlow, England: Pearson.
6 Meenakshi Raman, Sangeeta Sharma (2004) Technical Communication, Principles and
Practice. Oxford University Press
7 Archana Ram (2018) Place Men tor, Tests of Aptitude for Placement Readiness.
Oxford University Press
8 Sanjay Kumar &PushpLata (2018). Communication Skills a workbook, New Delhi:
Oxford University Press.






Page 37

Course C ode Course Name Credits
CSM501 Mini Project 2A 02

Objectives
1 To understand and identify the problem
2 To apply basic engineering fundamentals and attempt to find solutions to the problems.
3 Identify, analyze, formulate and handle programming projects with a comprehensive and
systematic approach
4 To develop communication skills and improve teamwork amongst group members and
inculcate the process of self -learning and research.
Outcome: Learner will be able to…
1 Identify societal/research/innovation/entrepreneurship problems through appropriate
literature surveys
2 Identify Methodology for solving above problem and apply engineering knowledge and
skills to solve it
3 Validate, Verify the results using test cases/benchmark data/theoretical/
inferences/experiments/simulations
4 Analyze and evaluate the impact of solution/product/research/innovation
/entrepreneurship towards societal/environmental/sustainable development
5 Use standard norms of engineering practices and project management principles during
project work
6 Communicate through technical report writing and oral presentation.
● The work may result in research/white paper/ article/blog writing and publication
● The work may result in business plan for entrepreneurship product created
● The work may result in patent f iling.
7 Gain technical competency towards participation in Competitions, Hackathons, etc.
8 Demonstrate capabilities of self -learning, leading to lifelong learning.
9 Develop interpersonal skills to work as a member of a group or as leader
Guidelines for Mini Project
1 Mini project may be carried out in one or more form of following:
Product preparations, prototype development model, fabrication of set -ups, laboratory
experiment development, process modification/development, simulation, software
development, integration of software (frontend -backend) and hardware, statistical data
analysis, creating awareness in society/environment etc.
2 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.
3 Students should do survey and identify needs, which shall be converted into problem
statement for mini project in consultati on with faculty supervisor or
head of department/internal committee of faculties.
4 Students shall submit an implementation plan in the form of Gantt/PERT/CPM ch art,
which will cover weekly activity of mini projects.
5 A logbook may be prepared by each group, wherein the group can record weekly work
progress, guide/supervisor can verify and record notes/comments.
6 Faculty supervisors may give inputs to students during mini project activity; however,
focus shall be on self -learning.
7 Students under the guidance of faculty supervisor shall convert the best solution into a
working model using various components of their domain areas and demonstrate.
8 The solution to be validated with proper justification and report to be compiled in
standard format of University of Mumbai. Software requirement specification (SRS)
documents, research papers, competition certificates may be submitted as part of

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annexure to the report.
9 With the focus on self -learning, innovation, addressing societal/research/innovation
problems and entrepreneurship quality development within the students through the Mini
Projects, it is preferable that a single project of appropriate le vel and quality be carried
out in two semesters by all the groups of the students. i.e. Mini Project 2 in semesters V
and VI.
10 However, based on the individual students or group capability, with the mentor’s
recommendations, if the proposed Mini Project adhering to the qualitative aspects
mentioned above, gets completed in odd semester, then that group can be allowed to work
on the extension of the Mini Project with suitable improvements/modifications or a
completely new project idea in even semes ter. This policy can be adopted on a case by
case basis.

Term Work
The review/ progress monitoring committee shall be constituted by the heads of departments of
each institute. The progress of the mini project to be evaluated on a continuous basis, based on
the SRS document submitted. 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 questi ons.
Distribution of Term work marks for both semesters shall be as below: Marks 25
1 Marks awarded by guide/supervisor based on logbook 10
2 Marks awarded by review committee 10
3 Quality of Project report 05
Review / progress monitoring committee may consider following points for assessment
based on either one year or half year project as mentioned in general guidelines
One-year project:
1 In one-year project (sem V and VI) , first semester the entire theoretical solution shall be
made ready, including components/system selection and cost analysis. Two reviews will
be conducted based on a presentation given by a student group.
First shall be for finalization of problem
Second sh all be on finalization of proposed solution of problem.
2 In the second semester expected work shall be procurement of component’s/systems,
building of working prototype, testing and validation of results based on work completed
in an earlier semester.
First review is based on readiness of building working prototype to be conducted.
Second review shall be based on poster presentation cum demonstration of working
model in the last month of the said semester.
Half -year project:
1 In this case in one semester students’ group shall complete project in all aspects including,
Identification of need/problem
Proposed final solution
Procurement of components/systems
Building prototype and testing
2 Two reviews will be conducted for continuous assessment,
First shall be for finalization of problem and proposed solution
Second shall be for implementation and testing of solution.

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Mini Project shall be assessed based on following points
1 Clarity of problem and quality of literature Survey for problem identification
2 Requirement Gathering via SRS/ Feasibility Study
3 Completeness of methodology implemented
4 Design, Analysis and Further Plan
5 Novelty, Originality or Innovativeness of project
6 Societal / Research impact
7 Effective use of skill set : Standard engineering practices and Project management
standard
8 Contribution of an individual’s as member or leader
9 Clarity in written and oral communication
10 Verification and validation of the solution/ Test Cases
11 Full functioning of working model as per stated requirements
12 Technical writing /competition/hackathon outcome being met

In one year project (sem V and VI), first semester evaluation may be based on first 10 criteria and
remaining may be used for second semester evaluation of performance of students in mini
projects.
In case of half year projects (completing in V sem) all criteria in generic may b e considered for
evaluation of performance of students in mini projects.

Guidelines for Assessment of Mini Project Practical/Oral Examination:
1 Report should be prepared as per the guidelines issued by the University of Mumbai.
2 Mini Project shall be assessed through a presentation and demonstration of working model
by the student project group to a panel of Internal and External Examiners preferably from
industry or research organizations having experience of more than five years approved by
the he ad of Institution.
3 Students shall be motivated to publish a paper/participate in competition based on the work
in Conferences/students competitions.

Page 40


Course Code: Course Title Credit
CSC601 System Programming and Compiler Construction 3

Prerequisite: Theoretical computer science, Operating system. Computer Organization and
Architecture .
Course Objectives:
1 To understand the role and function ality of various system programs over application
programs.
2 To understand basic concepts, st ructure and design of assemblers, macro processors, linkers
and loaders.
3 To understand the basic principles of compiler design, its various constituent parts,
algorithms and data structures required to be used in the compiler.
4 To understand the need to follow the syntax in writing an application program and to learn
how the analysis phase of compiler is designed to understand the programmer ‘s
requirements without ambiguity
5 To synthesize the analysis phase outcomes to produce the object code that i s efficient in
terms of space and execution time
Course Outcomes: On successful completion of course, learner will be able to
1 Identify the relevance of different system programs.
2 Explain various data structures used for assembler and microprocessor design .
3 Distinguish between different loaders and linkers and their contribution in developing
efficient user applications.
4 Understand fundamentals of compiler design and identify the relationships among different
phases of the compiler.

Module Content Hrs
1 Introduction to System Software 2
1.1 Concept of System Software, Goals of system software, system program
and system programming, Introduction to various system programs such
as Assembler, Macro processor, Loader, Linker, Compiler, Interpreter,
Device Drivers, Operating system, Editors, Debuggers.
2 Assemblers 7
2.1 Elements of Assembly Language programming, Assembly scheme, pass
structure of assembler, Assembler Design: Two pass assembler Design
and single pas s Assembler Design for X86 processor, data structures used.
3 Macros and Macro Processor 6
3.1 Introduction, Macro definition and call, Features of Macro facility:
Simple, parameterized, conditional and nested. Design of Two pass macro
processor, data structures used.
4 Loaders and Linkers 6
4.1 Introduction, functions of loaders, Relocation and Linking concept,
Different loading schemes: Relocating loader, Direct Linking Loader,
Dynamic linking and loading.
5 Compilers: Analysis Phase 10
5.1 Introduction to compilers, Phases of compilers:
Lexical Analysis - Role of Finite State Automata in Lexical Analysis,
Design of Lexical analyzer, data structures used.

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Syntax Analysis - Role of Context Free Grammar in Syntax analysis,
Types of Parsers: Top down parser - LL(1), Bottom up parser - SR Parser,
Operator precedence parser, SLR.
Semantic Analysis , Syntax directed definitions.
6 Compilers: Synthesis phase 8
6.1 Intermediate Code Generation : Types of Intermediate codes: Syntax
tree, Postfix notation, three address codes: Triples and Quadruples,
indirect triple . Code Optimization : Need and sources of optimization,
Code optimization techniques: Machine Dependent and Machine
Independent. Code Generation: Issues in the design of code generator,
code generation algorithm. Basic block and flow graph.

Textbooks:
1 D. M Dhamdhere: Systems programming and Operating Systems, Tata McGraw Hill ,
Revised Second Edition
2 A. V. Aho, R. Shethi, Monica Lam, J.D. Ulman: Compilers Principles, Techniques and
Tools , Pearson Education, Second Edition.
3 J. J. Donovan: Systems Programming Tata McGraw Hill, Edition 1991
References:
1 John R. Levine, Tony Mason & Doug Brown, Lex & YACC , O ‘Reilly publication, second
Edition
2 D, M .Dhamdhere , Compiler construction 2e, Macmillan publication, second edition .
3 Kenneth C. Louden , Compiler construction: principles and practices , Cengage Learning
4 Leland L. Beck, System software: An introduction to system programming , Pearson
publication, Third Edition
Useful Links for E -resources:
1 http://www.nptelvideos.in/2012/11/compiler -design.html
2 https://www.coursera.org/lecture/nand2tetris2/unit -4-1-syntax -analysis -5pC2Z

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first -class test is to be conducted
when approx. 40% syllabus is completed and the second -class test when an additional 40%
syllabus is completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise a total of six questions.
2 All question carries equal marks
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 module 3)
4 Only Four questions need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mentioned in the syllabus.



Page 42

Course Code: Course Title Credit
CSC602 Cryptography & System Security 3

Prerequisite: Computer Networks
Course Objectives:
1 To introduce classical encryption techniques and concepts of modular arithmetic and
number theory.
2 To explore the working principles and utilities of various cryptographic algorithms
including secret key cryptography, hashes and message digests, and public key algorithms
3 To explore the design issues and working principles of various authentication protocols, PKI
standards and various secure communication standards including Kerberos, IPsec, a nd
SSL/TLS.
4 To develop the ability to use existing cryptographic utilities to build programs for secure
communication
Course Outcomes:
1 Understand system security goals and concepts, classical encryption techniques and acquire
fundamental knowledge on the concepts of modular arithmetic and number theory
2 Understand, compare and apply different encryption and decryption techniques to solve
problems related to confidentiality and authentication
3 Apply different message digest and digital signature algorithms to verify integrity and
achieve authentication and design secure applications
4 Understand network security basics, analyse different attacks on networks and evaluate the
performance of firewalls and security protocols like SSL, IPSec, and PGP
5 Analyse and apply system security concept to recognize malicious code

Module Content Hrs
1 Introduction - Number Theory and Basic Cryptography 8
1.1 Security Goals, Attacks, Services and Mechanisms, Techniques. Modular
Arithmetic: Euclidean Algorithm, Fermat‘s and Euler‘s theorem
1.2 Classical Encryption techniques, Symmetric cipher model, mono -
alphabetic and polyalphabetic substitution techniques: Vigenere cipher,
playfair cipher, Hill cipher, transposition techniques: keyed and keyless
transposition ciphers
2 Symmetric and Asymmetric key Cryptography and key Management 11
2.1 Block cipher principles, block cipher modes of operation, DES,
Double DES, Triple DES, Advanced Encryption Standard (AES), Stream
Ciphers: RC4 algorithm.
2.2 Public key cryptography: Principles of public key cryptosystems - The
RSA Cryptosystem, The knapsack cryptosystem
2.3 Symmetric Key Distribution: KDC, Needham -schroeder protocol.
Kerberos: Kerberos Authentication protocol, Symmetric key agreement:
Diffie Hellman, Public key Distribution: Digital Certificate: X.509, PKI
3 Cryptographic Hash Functions 3
3.1 Cryptographic hash functions, Properties of secure hash function, MD5,
SHA -1, MAC, HMAC, CMAC.
4 Authentication Protocols & Digital Signature Schemes 5
4.1 User Authentication, Entity Authentication: Password Base, Challenge
Response Based

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4.2 Digital Signature, Attacks on Digital Signature, Digital Signature Scheme:
RSA
5 Network Security and Applications 9
5.1 Network security basics: TCP/IP vulnerabilities (Layer wise), Network
Attacks: Packet Sniffing, ARP spoofing, port scanning, IP spoofing
5.2 Denial of Service: DOS attacks, ICMP flood, SYN flood, UDP flood,
Distributed Denial of Service
5.3 Internet Security Protocols: PGP, SSL, IPSEC. Network security: IDS,
Firewalls
6 System Security 3
6.1 Buffer Overflow, malicious Programs: Worms and Viruses, SQL injection

Textbooks :
1 William Stallings, “Cryptography and Network Security, Principles and Practice” , 6th
Edition, Pearson Education, March 2013
2 Behrouz A. Ferouzan, “Cryptography & Network Security” , Tata Mc Graw Hill
3 Behrouz A. Forouzan & Debdeep Mukhopadhyay , “Cryptography and Network
Security” 3rd Edition, McGraw Hill

Referecebooks :
1 Bruce Schneier, “Applied Cryptography, Protocols Algorithms and Source Code in C ”,
Second Edition, Wiley .
2 Atul Kahate , “Cryptography and Network Security ”, Tata McGraw -Hill Education, 2003 .
3 Eric Cole , “Network Security Bible ”, Second Edition, Wiley , 2011.

Assessment :
Internal Assessment :
Assessment consists of two class tests of 20 marks each. The first class test is to be conducted
when approx. 40% syllabus is completed and second class test when additional 40% syllabus is
completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
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 module 3)
4 Only Four question need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.

Useful Links
1 https://github.com/cmin764/cmiN/blob/master/FII/L3/SI/book/W.Stallings%20 -
%20Cryptography%20and%20Network%20Se curity%206th%20ed.pdf
2 https://docs.google.com/file/d/0B5F6yMKYDUbrYXE4X1ZCUHpLNnc/view



Page 44


Course Code: Course Title Credit
CSC603 Mobile Computing 3

Prerequisite: Computer Networks
Course Objectives:
1 To introduce the basic concepts and principles in mobile computing. This includes major
techniques involved, and networks & systems issues for the design and implementation of
mobile computing systems and applications.
2 To explore both theoretical and practical issues of mobile computing.
3 To provide an opportunity for students to understand the key components and technologies
involved and to gain hands -on experiences in building mobile applications.
Course Outcomes: On successful completion of course, learner will be able to
1 To identify basic concepts and principles in computing, cellular architecture.
2 To describe the components and functioning of mobile networking.
3 To classify variety of security techniques in mobile network.
4 To apply the concepts of WLAN for loca l as well as remote applications.
5 To describe Long Term Evolution (LTE) architecture and its interfaces.

Module Content Hrs
1 Introduction to Mobile Computing 4
1.1 Introduction to Mobile Computing, Telecommunication Generations,
Cellular systems,
1.2 Electromagnetic Spectrum, Antenna, Signal Propagation, Signal
Characteristics, Multiplexing, Spread Spectrum: DSSS & FHSS, Co-
channel interference
2 GSM Mobile services 8
2.1 GSM Mobile services, System Architecture, Radio interface, Protocols,
Localization and Calling, Handover, security (A3, A5 & A8)
2.2 GPRS system and protocol architecture
2.3 UTRAN, UMTS core network; Improvements on Core Network,
3 Mobile Networking 8
3.1 Medium Access Protocol, Internet Protocol and Transport layer
3.2 Mobile IP: IP Packet Delivery, Agent Advertisement and Discovery,
Registration, Tunneling and Encapsulation, Reverse Tunneling.
3.3 Mobile TCP : Traditional TCP, Classical TCP Improvements like Indirect
TCP, Snooping TCP & Mobile TCP, Fast Retransmit/ Fast Recovery,
Transmission/Timeout Freezing, Selective Retransmission
4 Wireless Local Area Networks 6
4.1 Wireless Local Area Networks: Introduction, Infrastructure and ad -hoc
network
4.2 IEEE 802.11: System architecture , Protocol architecture , Physical layer,
Medium access control layer, MAC management, 802.11a, 802.11b
standard
4.3 Wi-Fi security : WEP ,WPA, Wireless LAN Threats , Securing Wireless
Networks

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4.4 Bluetooth: Introduction, User Scenario, Architecture, protocol stack
5 Mobility Management 6
5.1 Mobility Management : Introduction, IP Mobility, Optimization, IPv6
5.2 Macro Mobility : MIPv6, FMIPv6
5.3 Micro Mobility: CellularIP, HAWAII, HMIPv6
6 Long -Term Evolution (LTE) of 3GPP 7
6.1 Long -Term Evolution (LTE) of 3GPP : LTE System Overview,
Evolution from UMTS to LTE
6.2 LTE/SAE Requirements, SAE Architecture
6.3 EPS: Evolved Packet System, E -UTRAN, Voice over LTE (VoLTE),
Introduction to LTE -Advanced
6.4 Self Organizing Network (SON -LTE), SON for Heterogeneous Networks
(HetNet), Comparison between Different Generations (2G, 3G, 4G and 5G),
Introduction to 5G

Textbooks:
1 Jochen Schilller, “ Mobile Communication ”, Addision wisely, Pearson Education
2 William Stallings “ Wireless Communications & Networks ”, Second Edition, Pearson
Education
3 Christopher Cox, “ An Introduction to LTE: LTE, LTE -Advanced, SAE and 4G
Mobile Communications ”, Wiley publications
4 Raj Kamal, “Mobile Computing” , 2/e, Oxford University Press -New
References:
1 Seppo Hamalainen, Henning Sanneck , Cinzia Sartori, “LTE Self -Organizing
Networks (SON): Network Management Automation for Operational Efficiency”,
Wiley publications
2 Ashutosh Dutta, Henning Schulzrinne “Mobility Protocols and Handover
Optimization: Design, Evaluation and Application”, IEEE Press, Wiley Publication
3 Michael Gregg, “Build your own security lab”, Wiley India edition
4 Dipankar Raychaudhuri, Mario Gerla, “Emerging Wireless Technologies and the
Future Mobile Internet”, Cambridge
5 Andreas F. Molisch, “Wireless Communications”, Second Edition, Wiley Publication

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first class test is to be conducted
when approx. 40% syllabus is completed and second class test when additional 40% syllabus is
completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
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 module 3)
4 Only Four question need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.

Page 46

Useful Links
1 https://www.coursera.org/learn/smart -device -mobile -emerging -technologies
2 https://nptel.ac.in/courses/106/106/106106167/

















































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Course Code: Course Title Credit
CSC604 Artificial Intelligence 3

Prerequisite: Discrete Mathematics, Data Structures
Course Objectives:
1 To conceptualize the basic ideas and techniques underlying the design of intelligent
systems.
2 To make students understand and Explore the mechanism of mind that enables intelligent
thought and action.
3 To make students understand advanced representation formalism and search techniques.
4 To make students understand how to deal with uncertain and incomplete information.
Course Outcomes: At the end of the course, the students will be able to
1 Ability to develop a basic understanding of AI building blocks presented in intelligent
agents.
2 Ability to choose an appropriate problem solving method and knowledge representation
technique.
3 Ability to analyze the strength and weaknesses of AI approaches to knowledge – intensive
problem solving.
4 Ability to design models for reasoning with uncertainty as well as the use of unreliable
information.
5 Ability to design and develop AI applications in real world scenarios.

Module Content Hrs
1 Introduction to Artificial Intelligence 4
1.1 Introduction, History of Artificial Intelligence, Intelligent Systems:
Categorization of Intelligent System, Components of AI Program,
Foundations of AI, Sub -areas of AI, Applications of AI, Current trends
in AI.
2 Intelligent Agents 4
2.1 Agents and Environments, The concept of rationality, The nature of
environment, The structure of Agents, Types of Agents, Learning
Agent.
2.2 Solving problem by Searching: Problem Solving Agent, Formulating
Problems, Example Problems.
3 Problem solving 10
3.1 Uninformed Search Methods: Breadth First Search (BFS), Depth First
Search (DFS), Depth Limited Search, Depth First Iterative Deepening
(DFID), Informed Search Methods: Greedy best first Search, A*
Search, Memory bounded heuristic Search.
3.2 Local Search Algorithms and Optimization Problems: Hill climbing
search Simulated annealing, Genetic algorithms.
3.3 Adversarial Search: Game Playing, Min -Max Search, Alpha Beta
Pruning
4 Knowledge and Reasoning 12
4.1 Knowledge based Agents, Brief Overview of propositional logic, First
Order Logic: Syntax and Semantic, Inference in FOL, Forward
chaining, backward Chaining.
4.2 Knowledge Engineering in First -Order Logic, Unification, Resolution

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4.3 Uncertain Knowledge and Reasoning: Uncertainty, Representing
knowledge in an uncertain domain, The semantics of belief network,
Simple Inference in belief network
5 Planning and Learning 5
5.1 The planning problem, Planning with state space search, Partial order
planning, Hierarchical planning, Conditional Planning.

5.2 Learning: Forms of Learning, Theory of Learning, PAC learning.
Introduction to statistical learning (Introduction only )
Introduction to reinforcement learning: Learning from Rewards,
Passive Reinforcement Learning, Active reinforcement Learning
6 AI Applications 4
A. Introduction to NLP - Language models, Grammars, Parsing
B. Robotics - Robots, Robot hardware, Problems Robotics can
solve
C. AI applications in Healthcare, Retail, Banking

Textbooks:
1 Stuart J. Russell and Peter Norvig, " Artificial Intelligence: A Modern Approach ”, Fourth
Edition" Pearson Education, 2020.
2 Saroj Kaushik, “ Artificial Intelligence ”, Cengage Learning, First edition, 2011
3 George F Luger, “ Artificial Intelligence ” Low Price Edition, Fourth edition, Pearson
Education.,2005
References:
1 Nils J. Nilsson, Principles of Artificial Intelligence, Narosa Publication.
2 Deepak Khemani , A First Course in Artificial Intelligence, McGraw Hill Publication
3 Patrick H. Winston, Artificial Intelligence, 3rd edition, Pearson Education.
4 Elaine Rich and Kevin Knight, " Artificial Intelligence ”, Third Edition, McGraw Hill
Education,2017 .

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first class test is to be conducted
when approx. 40% syllabus is completed and the second class test when an additional 40%
syllabus is completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise a total of six questions.
2 All question carries equal marks
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 module 3)
4 Only Four questions need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mentioned in the syllabus.

Useful Links
1 https://nptel.ac.in/courses/106/105/106105078/
2 https://thestempedia.com/blog/simple -ai-and-machine -learning -projects -for-students -
and-beginners/
3 https://nptel.ac.in/courses/106/105/106105079/

Page 49


Course Code: Course Title Credit
CSD LO601 1 Internet of Things 3

Prerequisite: C Programming, Digital Logic and Computer Architecture, Microprocessor,
Computer Networks.
Course Objectives:
1 To equip students with the fundamental knowledge and basic technical competence in the
field of Internet of Things (IoT).
2 To emphasize on core IoT functional Stack to build assembly language programs. To learn
the Core IoT Functional Stack.
3 To understand the different common application protocols for IoT and apply IoT knowledge
to key industries that IoT is revol utionizing.
4 To examines various IoT hardware items and software platforms used in projects for each
platform that can be undertaken by a beginner, hobbyist, student, academician, or researcher
to develop useful projects or products.
Course Outcomes: On the completion of the course, learners will be able to:
1 Understand the concepts of IoT and the Things in IoT.
2 Emphasize core IoT functional Stack and understand application protocols for IoT.
3 Apply IoT knowledge to key industries that IoT is revolutionizing.
4 Examines various IoT hardware items and software platforms used in projects.

Module Content Hrs
1 Introduction to Internet of Things (IoT) 7
1.1 What is IoT? - IoT and Digitization
1.2 IoT Impact – Connected Roadways, Connected Factory, Smart Connected
Buildings, Smart Creatures
1.3 Convergence of IT and OT, IoT Challenges
1.4 The oneM2M IoT Standardized Architecture
1.5 The IoT World Forum (IoTWF) Standardized Architecture
1.6

IoT Data Management and Compute Stack – Design considerations and Data
related problems, Fog Computing, Edge Computing, The Hierarchy of Edge, Fog
and Cloud
2 Things in IoT 7
2.1 Sensors/Transducers – Definition, Principles, Classifications, Types,
Characteristics and Specifications
2.2 Actuators -– Definition, Principles, Classifications, Types, Characteristics and
Specifications
2.3 Smart Object – Definition, Characteristics and Trends
2.4 Sensor Networks – Architecture of Wireless Sensor Network, Network Topologies
2.5 Enabling IoT Technologies - Radio Frequency Identification Technology, Micro -
Electro -Mechanical Systems (MEMS), NFC (Near Field Communication),
Bluetooth Low Energy (BLE), LTE -A (LTE Advanced), IEEE 802.15.4 –
Standardization and Alliances, ZigBee.
3 The Core IoT Functional Stack 6
3.1 Layer 1 – Things: Sensors and Actuators Layer

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3.2 Layer 2 – Communications Network Layer, Access Network Sublayer, Gateways
and Backhaul Sublayer, Network Transport Sublayer, IoT Network Management
Sublayer
3.3 Layer 3 – Applications and Analytics Layer, Analytics Vs. Control Applications,
Data Vs. Network Analytics, Data Analytics Vs. Business Benefits, Smart Services
4 Application Protocols for IoT 7
4.1 The Transport Layer
4.2 IoT Application Transport Methods
4.3 Application Layer Protocol Not Present
4.4 SCADA - Background on SCADA, Adapting SCADA for IP, Tunneling Legacy
SCADA over IP Networks, SCADA Protocol Translation, SCADA Transport over
LLNs with MAP -T,
4.5 Generic Web -Based Protocols
4.6 IoT Application Layer Protocols – CoAP and MQTT
5 Domain Specific IoTs 6
5.1 Home Automation – Smart Lighting, Smart Appliances, Intrusion Detection,
Smoke/Gas Detectors
5.2 Cities – Smart Parking, Smart Lighting, Smart Roads, Structural Health
Monitoring, Surveillance
5.3 Environment – Weather Monitoring, Air Pollution Monitoring, Noise Pollution
Monitoring, Forest Fire Detection, River Floods Detection
5.4 Energy – Smart Grids, Renewable Energy Systems, Prognostics
5.5 Retail – Inventory Management, Smart Payments, Smart Vending Machines
5.6 Logistics – Route Generation & Scheduling, Fleet Tracking, Shipment Monitoring
5.7 Agriculture – Smart Irrigation, Green House Control
5.8 Industry – Machine Diagnostics & Prognosis, Indoor Air Quality Monitoring
5.9 Health & Lifestyle – Health & Fitness Monitoring, Wearable Electronics
6 Create your own IoT 6
6.1 IoT Hardware - Arduino, Raspberry Pi, ESP32, Cloudbit/Littlebits, Particle
Photon, Beaglebone Black.
6.2 IoT Software - languages for programming IoT hardware, for middleware
applications and API development, for making front ends, REST and JSON -LD
6.3 A comparison of IoT boards and platforms in terms of computing
6.4 A comparison of IoT boards and platforms in terms of development environments
and communication standards
6.5 A comparison of boards and platforms in terms of connectivity
6.6 A comparison of IoT software platforms

Textbooks:
1 David Hanes, Gonzalo Salgueiro , Patrick Grossetete, Rob Barton, Jerome Henry, “IoT
Fundamentals – Networking Technologies, Protocols, and Use Cases for the Internet
of Things”, 1st Edition, Published by Pearson Education, Inc, publishing as Cisco Press,
2017.

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2 Hakima Chaouchi, “The I nternet of Things - Connecting Objects to the Web”, 1st
Edition, Wiley, 2010.
3 Perry Lea, “Internet of things For Architects”, 1st Edition, Packt Publication, 2018
4 Arshdeep Bahga, Vijay Madisetti, “Internet of Things – Hands -On Approach”, 2nd
Edition , Universities Press, 2016.
References:
1 Adrian McEwen & Hakim Cassimally, “Designing the Internet of Things”, 1st Edition,
Wiley, 2014.
2 Donald Norris, “Raspberry Pi – Projects for the Evil Genius”, 2nd Edition, McGraw Hill,
2014.
3 Anand Tamboli , “Build Your Own IoT Platform”, 1st Edition, Apress, 2019.

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first -class test is to be conducted
when approx. 40% syllabus is completed and second -class test when additional 40% syllabus is
completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
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 module 3)
4 Only Four question need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.

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/special izations/IoT











Page 52

Course Code: Course Title Credit
CSD LO601 2 Digital Signal & Image Processing 3

Prerequisite: Applied Engineering Mathematics
Course Objectives:
1 To understand the fundamental concepts of digital signal processing and Image processing
2 To explore DFT for 1 -D and 2 -D signal and FFT for 1 -D signal
3 To apply processing techniques on 1 -D and Image signals
4 To apply digital image processing techniques for edge detection
Course Outcomes: On successful completion of course, learners will be able to:
1 Understand the concept of DT Signal and DT Systems
2 Classify and analyze discrete time signals and systems
3 Implement Digital Signal Transform techniques DFT and FFT
4 Use the enhancement techniques for digital Image Processing
5 Apply image segmentation techniques

Module
No. Unit
No. Topic details Hrs.
1.0 Discrete -Time Signal and Discrete -Time System 10
1.1 Introduction to Digital Signal Processing, Sampling and
Reconstruction, Standard DT Signals, Concept of Digital
Frequency, Representation of DT signal using Standard DT Signals,
Signal Manipulations (shifting, reversal, scaling, addition,
multiplication).
1.2 Classification of Discrete -Time Signals, Classification of Discrete -
Systems
1.3 Linear Convolut ion formulation for 1 -D signal (without
mathematical proof), Circular Convolution (without
mathematical proof), Linear convolution using Circular
Convolution. Auto and Cross Correlation formula evaluation,
Concept of LTI system, Output of DT system using Time Domain
Linear Convolution.
2.0 Discrete Fourier Transform 05
2.1 Introduction to DTFT, DFT, Relation between DFT and DTFT,
IDFT
2.2 Properties of DFT without mathematical proof (Scaling and
Linearity, Periodicity, Time Shift and Frequency Shift, Time
Reversal, Convolution Property and Parseval ’s Energy
Theorem). DFT computation using DFT properties.
2.3 Convolution of long sequences, Introduction to 2 -D DFT
3.0 Fast Fourier Transform 04
3.1 Need of FFT, Radix -2 DIT-FFT algorithm,
3.2 DIT-FFT Flow graph for N=4 and 8, Inverse FFT algorithm.
3.3 Spectral Analysis using FFT
4.0 Digital Image Fundamentals 05
4.1 Introduction to Digital Image, Digital Image Processing System,
Sampling and Quantization
4.2 Representation of Digital Image, Connectivity
4.3 Image File Formats: BMP, TIFF and JPEG.
5.0 Image Enhancement in Spatial domain 09
5.1 Gray Level Transformations, Zero Memory Point Operations,
5.2 Histogram Processing, Histogram equalization.

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5.3 Neighborhood processing, Image averaging, Image Subtraction,
Smoothing Filters - Low pass averaging, Sharpening Filters -High
Pass Filter , High Boost Filter, Median Filter for reduction of noise
6.0 Image Segmentation 06
6.1 Fundamentals, Segmentation based on Discontinuities
and Similarities
6.2 Point, line and Edge Detection, Image edge detection using Robert,
Prewitt and Sobel masks, Image edge Detection using Laplacian mask
6.3 Region based segmentation: Region Growing, Region Splitting
and Merging

Total 39

Textbooks :
1 John G. Proakis, Dimitris and G .Manolakis, “Digital Signal Processing: Principles,
Algorithms, and Applications” , 4th Edition , Pearson Education, 2007
2 A. Anand Kumar, “Digital Signal Processing” , 2nd Edition, PHI Learning Pvt. Ltd.
2014 .
3 Rafel C. Gonzalez and Richard E. Woods, “Digital Image Processing” , Pearson
Education Asia, 4th Edition, 2018.
4 S. Sridhar, “Digital Image Processing” , 2nd Edition, Oxford University Press, 2012.
References:
1 Sanjit Mitra, “Digital Signal Processing: A Computer Based Approach” , 4th Edition ,
Tata McGraw Hill, 2013
2 S. Salivahanan, A. Vallavaraj, and C. Gnanapriya, “Digital Signal Processing” , 2nd
Edition , Tata McGraw Hill Publication , 2011 .
3 S. Jayaraman, E. Esakkirajan and T. Veerku mar, “Digital Image Processing” , 3rd
Edition, Tata McGraw Hill Education Private Ltd, 2009.
4 Anil K. Ja in, “Fundamentals of Digital Image Processing” , 4th Edition , Prentice Hall
of India Private Ltd,. 1989
Assessment :
Internal Assessment :
Assessment consists of two class tests of 20 marks each. The first class test is to be conducted
when approx. 40% syllabus is completed and second class test when additional 50% syllabus
is completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
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 module 3)
4 Only Four question need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.

Useful Links
1 https://nptel.ac.in/courses/
2 https://swayam.gov.in



Page 54

Course Code: Course Title Credit
CSD LO601 3 Quantitative Analysis 3

Prerequisite: A pplied Mathematics
Course Objectives:
1 Introduction to the basic concepts in Statistics
2 Understand concept of data collection & sampling methods .
3 Introduction to Regression, Multiple Linear Regression
4 Draw interference using Statistical inference methods
5 Tests of hypotheses
Course Outcomes:
1 Recognize the need of Statistics and Quantitative Analysis
2 Apply the data collection and the sampling methods.
3 Analyze using concepts of Regression, Multiple Linear Regression
4 Formulate Statistical inference drawing methods.
5 Apply Testing of hypotheses

Module Content Hrs
1 Introduction to Statistics 6
Functions – Importance – Uses and Limitations of Statistics. Statistical data –
Classification, Tabulation, Diagrammatic & Graphic representation of data
2 Data Collection & Sampling Methods 6
Primary & Secondary data, Sources of data, Methods of collecting data.
Sampling – Census & Sample methods –Methods of sampling, Probability
Sampling and Non -Probability Sampling.
3 Introduction to Regression 8
Mathematical and Statistical Equation – Meaning of Intercept and Slope –
Error term – Measure for Model Fit –R2 – MAE – MAPE .
4 Introduction to Multiple Linear Regression 8
Multiple Linear Regression Model, Partial Regression Coefficients, Testing
Significance overall significance of Overall fit of the model, Testing for
Individual Regression Coefficients
5 Statistical inference 6
Random sample -Parametric point estimation unbiasedness and consistence
- method of moments and method of maximum likelihood.
6 Tests of hypotheses 5
Null and Alternative hypotheses. Types of errors. Neyman -Pearson lemma -
MP and UMP tests.

Textbooks:
1 Agarwal, B.L. (2006): -Basic Statistics. Wiley Eastern Ltd., New Delhi
2 Gupta, S. P. (2011): -Statistical Methods. Sultanchand&Sons, New Delhi
3 Sivathanupillai, M &Rajagopal, K. R. (1979): -Statistics for Economics Students.
4 Hogg ,R.V. and Craig, A.T.(2006), An introduction to mathematical statistics, Amerind
publications.
References:

Page 55

1 Arora, P.N., SumeetArora, S. Arora (2007): - Comprehensive Statistical Methods. Sultan
Chand, New Delhi
2 Montgomery,D.C. ,Peck E.A, & Vining G.G.(2003). Introduction to Linear Regression
Analysis. John Wiley and Sons,Inc.NY
3 Mood AM, Graybill FA, and Boes, D.C.(1985), Introduction to the theory of statistics,
McGrawhill Book Company, New Delhi.
4 Kapur, J.N. and Saxena,H .C.(1970), Mathematical statistics, Sultan Chand & company, New
Delhi..

Assessment :
Internal Assessment:
Assessment consists of two class tests of 20 marks each. The first class test is to be conducted
when approx. 40% syllabus is completed and second class test when additional 40% syllabus is
completed. Duration of each test shall be one hour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
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 module 3)
4 Only Four question need to be solved.
5 In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.




























Page 56


Lab Code Lab Name Credit
CSL601 System Programming and Compiler Construction Lab 1

Prerequisite: Theoretical computer science, Operating system. Computer Organization and
Architecture
Lab Outcomes: At the end of the course, the students will be able to
1 Generate machine code by implementing two pass assemblers.
2 Implement Two pass macro processor .
3 Parse the given input string by constructing Top down/Bottom -up parser .
4 Identify and Validate tokens for given high level language and Implement synthesis phase of
compiler.
5 Explore LEX & YACC tools.

Suggested List of Experiments
Sr. No. Title of Experiment
1 Implementations of two pass Assembler.
2 Implementation of Two pass Macro Processor.
3 Implementation of Lexical Analyzer.
4 Implementation of Parser (Any one).
5 Implementation of Intermediate code generation phase of compiler.
6 Implementation of code generation phase of compiler.
7 Study and implement experiments on LEX, YACC.

Reference Books:
1 Andrew W. Appel Princeton University. Jens Palsberg Modern Compiler.
Implementation in Java , Second Edition. Purdue University. CAMBRIDGE
University press @2002.
2 Charles N. Fischer, Richard J. LeBlanc Crafting a compiler with C , pearson
Education 2007

Term Work:
1 Term work should consist of experiments based on suggested experiment list.
2 Journal must include at least 2 assignments on content of theory and practical of “ System
Programming and Compiler Construction ”
3 The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
4 The distribution of marks for term work shall be as follows:
Laboratory work (experiments/case studies): ....................................(15) Marks.
Assignment: ...................................................................................... (05) Marks.
Attendance ..................... .................................................................... (05) Marks
TOTAL: .............................................................................................. (25) Marks.
Oral & Practical exam will be based on the above and CSC601 syllabus.




Page 57

Lab Code Lab Name Credit
CSL602 Cryptography & System Security Lab 1

Prerequisite: Computer Network
Lab Objectives:
1 To apply various encryption techniques
2 To study and implement various security mechanism
3 To explore the network security concept and tools
Lab Outcomes: At the end of the course, the students will be able to
1 apply the knowledge of symmetric and asymmetric cryptography to implement simple
ciphers.
2 explore the different network reconnaissance tools to gather information about networks.
3 explore and use tools like sniffers, port scanners and other related tools for analysing
packets in a Network.
4 set up firewalls and intrusion detection systems using open -source technologies and to
explore email security.
5 explore various attacks like buffer -overflow and web application attack.


Suggested List of Experiments
Sr. No Title of Experiment
1 Design and Implementation of a product cipher using Substitution and Transposition
ciphers.
2 Implementation and analysis of RSA crypto system.
3 Implementation of Diffie Hellman Key exchange algorithm
4 For varying message sizes, test integrity of message using MD -5, SHA -1, and
analyse the performance of the two protocols. Use crypt APIs.
5 Study the use of network reconnaissance tools like WHOIS, dig, traceroute, ns
lookup to gather information about networks and domain registrars.
6 Study of p acket sniffer tools: wireshark, :
1. Download and install wireshark and capture icmp, tcp, and http packets in
promiscuous mode.
2. Explore how the packets can be traced based on different filters.
7 Download and install nmap. Use it with different options to scan open ports, perform
OS fingerprinting, do a ping scan, tcp port scan, udp port scan , xmas scan etc.
8 Detect ARP spoofing using nmap and/or open -source tool ARPWATCH and
wireshark. Use arping tool to generate gratuitous arps and monitor using wireshark
9 Simulate DOS attack using Hping, hping3 and other tools
10 Simulate buffer overflow attack using Ollydbg, Splint, Cpp check etc
11 a. Set up IPSEC under LINUX.
b. Set up Snort and study the logs.
12 Setting up personal Firewall using iptables
13 Explore the GPG tool of linux to implement email security
14 SQL injection attack, Cross -Cite Scripting attack simulati on
15 Case Study /Seminar: Topic beyond syllabus related to topics covered.

Term Work:
1 Term work should consist of 10 experiments.
2 Journal must include at least 2 assignments on content of theory and practical of

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“Cryptography and System Security “
3 The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
4 The distribution of marks f or term work shall be as follows:
Lab Performance 15 Marks
Assignments 05 Marks
Attendance (Theory & practical) 05 Marks



Page 59

Lab Code Lab Name Credit
CSL603 Mobile Computing Lab 1

Prerequisite: Computer Networks
Lab Objectives:
1 To learn the mobile computing tools and software for implementation.
2 To understand the security algorithms in mobile networks
3 To learn security concepts
Lab Outcomes: At the end of the course, the students will be able to
1 develop and demonstrate mobile applications using various tools
2 articulate the knowledge of GSM, CDMA & Bluetooth technologies and demonstrate it.
3 Students will able to carry out simulation of frequency reuse, hidden/exposed terminal
problem
4 implement security algorithms for mobile communication network
5 demonstrate simulation and compare the performance of Wireless LAN

Suggested List of Experiments
The softwares like Android Studio, J2ME, NS2, NS3 and any other software which is suitable
are recommended for performing the practical.
Sr. No. Title of Experiment
1 Implementation a Bluetooth network with application as transfer of a file from one
device to another.
2 To implement a basic function of Code Division Multiple Access (CDMA).
3 Implementation of GSM security algorithms (A3/A5/A8)
4 Illustration of Hidden Terminal/Exposed terminal Problem. Consider two Wi -fi
base stations (STA) and an access point (AP) located along the x -axis. All the
nodes are fixed. The AP is situated at the middle of the two STA, the distance of
separation being 150 m. [variable]. Node #0 and node #1 are the hidden
terminals. Both are tra nsmitting some data to the AP (almost at same rate) at the
same time. The loss across the wireless link between each STA and the AP is
fixed at 50 dB irrespective of the distance of separation. To study how
RTS/CTS helps in wireless networks,
1. No RTS/CT S is being sent.
2. Nodes do exchange RTS/CTS packets.
Compare the no. of packet retransmissions required in both the cases (as
obtained in the output) and compare the results.

5 To setup & configuration of Wireless Access Point (AP). Analyze the Wi -Fi
communication range in the presence of the access point (AP) and the base
station (BS). Consider BS and AP are static. Find out the maximum distance to
which two way communications i s possible. Try multiple iterations by adjusting
its distance in the code and test it.

6 Study of security tools (like Kismet,Netstumbler)
7 Develop an application that uses GUI components.
8 Write an application that draws basic graphical primitives on the screen.
9 Develop an application that makes use of database.
10 Develop a native application that uses GPS location information.
11 Implement an application that creates an alert upon receiving a message.

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12 Implementation of income tax/loan EMI calculator and deploy the same on real
devices (Implementation of any real time application)

Term Work:
1 Term work should consist of 10 experiments.
2 Journal must include at least 2 assignments on content of theory and practical of “ Mobile
Computing”
3 The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
4 Total 25 Marks (Experiments: 15 -marks, Att endance Theory& Practical: 05 -marks,
Assignments: 05 -marks)

Useful Links
1 https://nptel.ac.in/courses/106/106/106106147/
2 https://www.coursera.org/learn/smart -device -mobile -emerging -technologies



Page 61

Lab Code Lab Name Credit
CSL604 Artificial Intelligence Lab 1

Prerequisite: Discrete Mathematics, Data Structure
Lab Objectives:
1 To realize the basic techniques to build intelligent systems
2 To apply appropriate search techniques used in problem solving
3 To create knowledge base for uncertain data
Lab Outcomes: At the end of the course, the students will be able to
1 Identify languages and technologies for Artificial Intelligence
2 Understand and implement uninformed and informed searching techniques for real world
problems.
3 Create a knowledge base using any AI language.
4 Design and implement expert systems for real world problems.

Suggested List of Experiments (programming in python)
Sr. No. Title of Experiment
1 One case study on AI applications published in IEEE/ACM/Springer or any prominent
journal.
2 Assignments on State space formulation and PEAS representation for various AI
applications
3 Program on uninformed search methods.
4 Program on informed search methods.
5 Program on Game playing algorithms.
6 Program for first order Logic
7 Planning Programming
8 Implementation for Bayes Belief Network
Note: Any other practical covering the syllabus topics and subtopics can be conducted.
The programming assignment for First order logics could be in the form of a mini project

Term Work:
1 Term work should consist of a minimum of 8 experiments.
2 Journal must include at least 2 assignments on content of theory and practical of “ Artificial
Intelligence ”
3 The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
4 Total 25 Marks (Experiments: 15 -marks, Attendance Theory & Practical: 05 -marks,
Assignments: 05 -marks)
Oral & Practical exam: Based on the entire syllabus of CSC604: Artificial Intelligence


Page 62

Lab Code Lab Name Credit
CSL605
Cloud Computing
2
Prerequisite: Computer Networks
Lab Objectives: The course has following objectives
1 To make students familiar with key concepts of virtualization.
2 To make students familiar with various deployment models of cloud such as private, public,
hybrid and community so that they star using and adopting appropriate type of cloud for their
application.
3 To make students familiar with various service models such as IaaS, SaaS, PaaS, Security as
a Service (SECaaS) and Database as a Service.
4 To make students familiar with security and privacy issues in cloud computing and how to
address them.
Lab Outcomes: At the end of the course, the students will be able to
1 Implement different types of virtualization techniques.
2 Analyze various cloud computing service models and implement them to solve the given
problems.
3 Design and develop real world web applications and deploy them on commercial cloud(s).
4 Explain major security issues in the cloud and mechanisms to address them.
5 Explore various commercially available cloud services and recommend the appropriate one for
the given application.
6 Implement the concept of containerization
Module Detailed Contents Hours LO
01 Title: Introduction and overview of cloud computing.
Objective: To understand the origin of cloud computing, cloud
cube model, NIST model, characteristics of cloud, different
deployment models, service models, advantages and
disadvantages. 2 2
02 Title: To study and implement Hosted Virtualization using
VirtualBox& KVM.
Objective: To know the concept of Virtualization along with
their types, structures and mechanisms. This experiment should
have demonstration of creating and running Virtual machines
inside hosted hypervisors like VirtualBox and KVM with their
comparison based on var ious virtualization parameters. 2 1

03 Title: To study andImplement Bare -metal Virtualization using
Xen, HyperV or VMware Esxi.
Objective: To understand the functionality of Bare -metal
hypervisors and their relevance in cloud computing platforms.
This experiment should have demonstration of install, configure
and manage Bare Metal hypervisor along with instructions to
create and run virtual machines inside it. It should also
emphasize on accessing VMs in different environments along
with additional serv ices provided by them like Load balancing,
Auto -Scaling, Security etc. 4 1

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04 Title: To study andImplement Infrastructure as a Service using
AWS/Microsoft Azure.
Objective: To demonstrate the steps to create and run virtual
machines inside Public cloud platform. This experiment should
emphasize on creating and running Linux/Windows Virtual
machine inside Amazon EC2 or Microsoft Azure Compute and
accessing them using RDP or V NC tools. 4 2
05 Title: To study andImplement Platform as a Service using
AWS Elastic Beanstalk/ Microsoft Azure App Service.
Objective: To demonstrate the steps to deploy Web applications
or Web services written in different languages on AWS Elastic
Beanstalk/ Microsoft Azure App Service. 4 2
06 Title: To study andImplementStorage as a Service using Own
Cloud/ AWS S3, Glaciers/ Azure Storage.
Objective: To understand the concept of Cloud storage and to
demonstrate the different types of storages like object storage,
block level storages etc. supported by Cloud Platforms like Own
Cloud/ AWS S3, Glaciers/ Azure Storage. 4 2
07 Title: To study andImplementDatabase as a Service on
SQL/NOSQL databases like AWS RDS, AZURE SQL/
MongoDB Lab/ Firebase.
Objective: To know the concept of Database as a Service
running on cloud and to demonstrate the CRUD operations on
different SQL and NOSQL databases running on cloud like
AWS RDS, AZURE SQL/ Mongo Lab/ Firebase. 2 2
08 Title: To study andImplementSecurity as a Service on
AWS/Azure
Objective: To understand the Security practices available in
public cloud platforms and to demonstrate various Threat
detection, Data protection and Infrastructure protection services
in AWS and Azure. 3 4
09 Title: To study and implement Identity and Access
Manage ment (IAM) practices on AWS/Azure cloud.
Objective: To understand the working of Identity and Access
Management IAM in cloud computing and to demonstrate the
case study based on Identity and Access Management (IAM) on
AWS/Azure cloud platform. 2 2
10 Title: To study and Implement Containerization using Docker
Objective: To know the basic differences between Virtual
machine and Container. It involves demonstration of creating,
finding, building, installing, and running Linux/Windows
application containe rs inside local machine or cloud platform. 4 6

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11 Title: To study and implement container orchestration using
Kubernetes
Objective: To understand the steps to deploy Kubernetes
Cluster on local systems, deploy applications on Kubernetes,
creating a Service in Kubernetes, develop Kubernetes
configuration files in YAML and creating a deployment in
Kubernetes using YAML, 4 6
12 Mini -project: Design a Web Application hosted on public
cloud platform
[It should cover the concept of IaaS, PaaS, DBaaS, Storage as a
Service, Security as a Service etc.] 4 3, 5

Sr. No. Suggested Assignment List (Any two) LO
1 Assignment based on selection of suitable cloud platform solution
based on requirement analysis considering given problem
statement 5
2 Assignment on recent trends in cloud computing and related
technologies 5
3 Assignment on comparative study of different computing
technologies [Parallel, Distributed, Cluster, Grid, Quantum) 5
4 Comparative study of different hosted and bare metal Hypervisors
with suitable parameters along with their use in public/private
cloud platform 1
5 Assignment on explore and compare the similar type of services
provided by AWS and Azure [Any ten services] 5

Digital Material:
Sr.
No. Topic Link
1 Introduction and overview of cloud
computing https://www.nist.gov/system/files/documents
/itl/cloud/NIST_SP -500-291_Version -
2_2013_June18_FINAL.pdf
2 Hosted Virtualization using KVM https://phoenixnap.com/kb/ubuntu -install -
kvm\
3 Baremetal Virtualization using Xen https://docs.citrix.com/en -us/xenserver/7 -
1/install.html
4 IaaS, PaaS, STaaS, DbaaS, IAM and
Security as a Service on AWS and
Azure 1) AWS
https://docs.aws.amazon.com/
2) MS Azure
https://docs.microsoft.com/en -us/azure
5 Docker https://docs.docker.com/get -started/

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6 Kubernetes https://kubernetes.io/docs/home/

Textbooks:
1 Bernard Golden, “Amazon Web Services for Dummies”, John Wiley & Sons, Inc.
2 Michael Collier, Robin Shahan, “Fundamentals of Azure, Microsoft Azure Essentials”,
Microsoft Press.
3 RajkumarBuyya, Christian Vecchiola, S ThamaraiSelvi, “Mastering Cloud Computing”,
Tata McGraw -Hill Education.
4 Barrie Sosinsky, “Cloud Computing Bible”, Wiley publishing.
5 John Paul Mueller, “AWS for Admins for Developers”, John Wiley & Sons, Inc.
6 Ken Cochrane, Jeeva S. Chelladhurai, NeependraKhare , “Docker Cookbook - Second
Edition”, Packt publication
7 Jonathan Baier, “Getting Started with Kubernetes -Second Edition”, Packt Publication.

Term Work:
1 Term work should consist of 10 experiments and a mini project.
2 Journal must include at least 2 assignments.
3 The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
4 Total 50 Marks (Experiments: 15 -marks, Mini project (Implementation) 15 marks,
Mini Project Presentation & Report [for deployment, utilization, monitoring and
billing] 10 Marks, Attendance 05 -marks, Assignments: 05 -marks)
Oral examination will be based on Laboratory work, mini project and above syllabus.

Page 66

Course code Course Name Credits
CSM601 Mini Project 2B 02

Objectives
1 To understand and identify the problem
2 To apply basic engineering fundamentals and attempt to find solutions to the problems.
3 Identify, analyze, formulate and handle programming projects with a comprehensive and
systematic approach
4 To develop communication skills and improve teamwork amongst group members and
inculcate the process of self -learning and research.
Outcome: Learner will be able to…
1 Identify societal/research/innovation/entrepreneurship problems through appropriate
literature surveys
2 Identify Methodology for solving above problem and apply engineering knowledge and
skills to solve it
3 Validate, Verify the results using test cases/benchmark data/theoretical/
inferences/experiments/simulations
4 Analyze and evaluate the impact of solution/product/research/innovation /entrepreneurship
towards societal/environmental/sustainable development
5 Use standard norms of engineering practices and project management principles during
project work
6 Communicate through technical report writing and oral presentation.
● The work may result in research/white paper/ article/blog writing and publication
● The work may result in business plan for entrepreneurship product created
● The work may result in patent f iling.
7 Gain technical competency towards participation in Competitions, Hackathons, etc.
8 Demonstrate capabilities of self -learning, leading to lifelong learning.
9 Develop interpersonal skills to work as a member of a group or as leader
Guidelines for Mini Project
1 Mini project may be carried out in one or more form of following:
Product preparations, prototype development model, fabrication of set -ups, laboratory
experiment development, process modification/development, simulation, software
development, integration of software (frontend -backend) and hardware, statistical data
analysis, creating awareness in society/environment etc.
2 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.
3 Students should do survey and identify needs, which shall be converted into problem
statement for mini project in consultation with faculty supervisor/head
of department/internal committee of faculties.
4 Students shall submit an implementation plan in the form of Gantt/PERT/CPM chart, which
will cover weekly activity of mini projects.
5 A logbook may be prepared by each group, wherein the group can record weekly work
progress, guide/supervisor can verify and record notes/comments.
6 Faculty supervisors may give inputs to students during mini project activity; however, focus
shall be on self -learning.
7 Students under the guidance of faculty supervisor shall convert the best solution into a
working model using various components of their domain areas and demonstrate.
8 The solution to be validated with proper justification and report to be compiled in standard
format of University of Mumbai. Software requirement specification (SRS) documents,
research papers, competition certificates may be submitted as part of annexure to the report.

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9 With the focus on self -learning, innovation, addressing societal/research/innovation
problems and entrepreneurship quality development within the students through the Mini
Projects, it is preferable that a single project of appropriate level and quality be carried out
in two semesters by all the groups of the students. i.e. Mini Project 2 in semesters V and
VI.
10 However, based on the individual students or group capability, with the mentor’s
recommendations, if the proposed Mini Project adhering to the qualitative aspects
mentioned above, gets completed in odd semester, then that group can be allowed to work
on the extension of the Mini Project with suitable improvements/modifications or a
completely new project idea in even seme ster. This policy can be adopted on a case by
case basis.
Term Work
The review/ progress monitoring committee shall be constituted by the heads of departments of
each institute. The progress of the mini project to be evaluated on a continuous basis, based on
the SRS document submitted. 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: Marks 25
1 Marks awarded by guide/supervisor based on logbook 10
2 Marks awarded by review committee 10
3 Quality of Project report 05
Review / progress monitoring committee may consider following points for assessment based
on either one year or half year project as mentioned in general guidelines
One-year project:
1 In the first semester the entire theoretical solution shall be made ready, including
components/system selection and cost analysis. Two reviews will be conducted based on
a presentation given by a student group.
First shall be for finalization of problem
Second shall be on finalization of proposed solution of problem.
2 In the second semester expected work shall be procurement of component’s/systems,
building of working prototype, testing and validation of results based on work completed
in an earlier semester.
First review is based on readiness of building working prototype to be co nducted.
Second review shall be based on poster presentation cum demonstration of working
model in the last month of the said semester.
Half -year project:
1 In this case in one semester students’ group shall complete project in all aspects including,
Identification of need/problem
Proposed final solution
Procurement of components/systems
Building prototype and testing
2 Two reviews will be conducted for continuous assessment,
First shall be for finalization of problem and proposed solution
Second shall be for implementation and testing of solution.
Mini Project shall be assessed based on following points
1 Clarity of problem and quality of literature Survey for problem identification
2 Requirement gathering via SRS/ Feasibility Study
3 Completeness of methodology implemented

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4 Design, Analysis and Further Plan
5 Novelty, Originality or Innovativeness of project
6 Societal / Research impact
7 Effective use of skill set : Standard engineering practices and Project management
standard
8 Contribution of an individual’s as member or leader
9 Clarity in written and oral communication
10 Verification and validation of the solution/ Test Cases
11 Full functioning of working model as per stated requirements
12 Technical writing /competition/hackathon outcome being met

In one year project (sem V and VI), first semester evaluation may be based on first 10 criteria
and remaining may be used for second semester evaluation of performance of students in mini
projects.
In case of half year projects (completing in VI sem) all criteria’s in generic may be considered
for evaluation of performance of students in mini projects.

Guidelines for Assessment of Mini Project Practical/Oral Examination:
1 Report should be prepared as per the guidelines issued by the University of Mumbai.
2 Mini Project shall be assessed through a presentation and demonstration of working model
by the student project group to a panel of Internal and External Examiners preferably from
industry or research organizations having experience of more than five years approved by
the head of Institution.
3 Students shall be motivated to publish a paper/participate in competition based on the
work in Conferences/students competitions.