N BE Computer Science Design Sem V VI _1 Syllabus Mumbai University

Page 1

Page 2

Copy for information and necessary action : -

1. The Deputy Registrar, College Affiliations & Development Department
(CAD),
2. College Teachers Approval Unit (CTA),
3. The Deputy Registrar, (Admissions, Enrolment, Eligibility and
Migration Department (AEM),
4. The Deputy Registrar, Academic Appointments & Quality Assurance
(AAQA)
5. The Deputy Registrar, Research Administration & Promotion Cell
(RAPC),
6. The Deputy Registrar, Executive Authorities Section (EA)
He is requested to treat this as action taken report on the concerned
resolution adopted by the Academic Council referred to the above
circular.

7. The Deputy Registrar, PRO, Fort, (Publication Section),
8. The Deputy Registrar, Special Cell,
9. The Deputy Registrar, Fort Administration Department
(FAD) Record Section,
10. The Deputy Registrar, Vidyanagari Administration Department
(VAD),


Copy for information : -


1. The Director, Dept. of Information and Communication Technology
(DICT), Vidyanagari,
He is requested to upload the Circular University Website
2. The Director of Department of Student Development (DSD) ,
3. The Director, Institute of Distance and Open Learning (IDOL Admin),
Vidyanagari,
4. All Deputy Registrar, Examination House,
5. The Deputy Registrars, Finance & Accounts Section,
6. The Assistant Registrar, Administrative sub -Campus Thane,
7. The Assistant Registrar, School of Engg. & Applied Sciences, Kalyan,
8. The Assistant Registrar, Ratnagiri sub -centre, Ratnagiri,
9. P.A to Hon’ble Vice -Chancellor,
10. P.A to Pro -Vice-Chancellor,
11. P.A to Registrar,
12. P.A to All Deans of all Faculties,
13. P.A to Finance & Account Officers, (F & A.O),
14. P.A to Director, Board of Examinations and Evaluation,
15. P.A to Director, Innovation, Incubation and Linkages,
16. P.A to Director, Department of Li felong Learning and Extension (D LLE),
17. The Receptionist,
18. The Telephone Operator,

Copy with compliments for information to : -

19. The Secretary, MUASA
20. The Secretary, BUCTU.

Page 3

AC – 01/11/2023
Item No. – 6.10(N)





University of Mumbai








Syllabus for
B.E. (Computer Science & Design )
Third Year with Effect from AY 2023 -24
Final Year with Effect from AY 2024 -25

Sem ester - V & VI

Choice Based Credit System

REV- 2019 ‘C’ Scheme

Page 4

University of Mumbai



Syllabus for Approval
Sr.
No.
Heading
Particulars
1 Title of Course
B.E. (Computer Science & Design)

2 Eligibility of Admission
After Passing Second Year
Engineering as per the Ordinance
0.6243
3 Passing Marks

40%
4 Ordinance / Regulations (if any)
Ordinance 0.6243
5 No. of years/Semesters: 4 years / 8 semesters

6 Level: Under Graduation

7 Pattern: Semester

8 Status: New
REV-2019 ‘C’ Scheme





9 To be implemented from Academic Year: With effect from Academic Year:
2023-2024





Dr. Deven Shah Dr. Shivram Garje
Offg . Associate Dean Offg. Dean
Faculty of Science and Technology Faculty of Science and Technology

Page 5

Preamble

To meet the challenge of ensuring excellence in engineering education, the issue of quality needs to
be addressed, debated and taken forward in a systematic manner. Accreditation is the principal
means of quality assuranc e in higher education. The major emphasis of accreditation process is to
measure the outcomes of the program that is being accredited. In line with this Faculty of Science
and Technology (in particular Engineering) of University of Mumbai has taken a lead in
incorporating philosophy of outcome based education in the process of curriculum development.
Faculty resolved that course objectives and course outcomes are to be clearly defined for each
course, so that all faculty members in affiliated institutes und erstand the depth and approach of
course to be taught, which will enhance learner‟s learning process. Choice based Credit and grading
system enables a much -required shift in focus from teacher -centric to learner -centric education since
the workload estimat ed is based on the investment of time in learning and not in teaching. It also
focuses on continuous evaluation which will enhance the quality of education. Credit assignment for
courses is based on 15 weeks teaching learning process, however content of co urses 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 science and technology resolved that to
minimize the burden of contact hours, total credits of entire program will be of 170, wherein focus is
not only on providing knowledge but also on building skills, attitude and self learning. Therefore in
the present curriculum skill based laboratories and mini projects are made mandatory across all
disciplines of engineering in se cond and third year of programs, which will definitely facilitate self
learning of students. The overall credits and approach of curriculum proposed in the present revision
is in line with AICTE model curriculum.
The present curriculum will be implemented for Second Year of Engineering from the academic year
2021 -22. Subsequently this will be carried forward for Third Year and Final Year Engineering in the
academic years 2022 -23, 2023 -24, respectively.




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

Page 6

Incorporation and Implementation of Online Contents from
NPTEL/ Swayam Platform



The curriculum revision is mainly focused on knowledge comp onent, 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 a s NPTEL, Swayam are appropriately provided. In an earlier
revision of curriculum in the year 2012 and 2016 in Revised scheme „A' and „B' respectively,
efforts were made to use online contents more appropriately as additional learning materials to
enhance l earning of students.
In the current revision based on the recommendation of AICTE model curriculum overall credits
are reduced to 171, to provide opportunity of self-learning to learner. Learners are now getting
sufficient time for self-learning either thr ough 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
Associate Dean
Faculty of Science and Technology
University of Mumbai

Page 7

Preface by Board of Studies in
Computer Engineering
Dear Students and Teachers, we, the member s 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 courses 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 indus try 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 a ims at producing
trained professionals who can successfully acquainted with the demands 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 fall s 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 extracurricular activities, innovations, and research.
2. The department Optional Courses will provide the relevant specialization
within the branch to a student.
3. Introduction of Ski ll Based Lab and Mini Project to showcase their talent by
doing innovative projects 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 pl ace on record our gratefulness to the faculty, students, industry
experts and stakeholders for having helped us in the formulation of this syllabus.

Page 8

Program Structure for Third Year
UNIVERSITY OF MUMBAI (With Effect from 2021 -2022)
Semester V
Course
Code Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract. Theory Pract. Tuto Total
CSC501 Theoretical Computer
Science 3 -- 3 -- 1 4
CSC5 02 Software Engineering 3 -- 3 -- -- 3
CSC503 Computer Network 3 -- 3 -- -- 3
CSC504 Data Ware housing &
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 Professi onal Comm. &
Ethics II -- 2*+2 -- 2 -- 2
CSM501 Mini Project: 2 A -- 4$ -- 2 -- 2
Total 15 14 15 07 01 23
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
CSDLO501x 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 C omm. &
Ethics II -- -- -- -- -- 25 25 50
CSM501 Mini Project : 2A -- -- -- -- -- 25 25 50
Total -- -- 100 400 -- 150 125 775
* Theory class to be conducted for full class and $ indicates workload of Learner (Not Faculty), students
can form groups with m inimum 2(Two) and not more than 4(Four). Faculty Load: 1hour per week per
four groups.

Page 9

Program Structure for Third Year
UNIVERSITY OF MUMBAI (With Effect from 2021 -2022 )
Semester VI
Course
Code Course Name Teaching Scheme
(Contact Hours) Credits Assigne d
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 Departme nt 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 Intelligenc e 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 Mobi le 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

Page 10

UNIVE RSITY 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

Page 11

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 co mputation 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,Eq uivalence of RG and FA.

Page 12

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 Fo rms (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, R ecursive 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 compl eted.
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).

Page 13

2. Assignment (best 5 assignments) 20 marks
Attendance 5 marks
3. It is recommended t o 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.

Page 14

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 Introduct ionToSoftwareEngineeringandProcessModels 7
1.1 SoftwareEngineering -processframework,theCapabilityMaturityModel(CMM),
AdvancedTrendsinSoftwareEngineering
1.2 PrescriptiveProcessModels: TheWaterfall,Incremental
ProcessModels, EvolutionaryProcessModels:RA D &Spiral
1.3 Agileprocessmodel: ExtremeProgramming (XP),Scrum, Kanban
2 SoftwareRequirementsAnalysisandModeling 4
2.1 Requirement
Engineering,RequirementModeling,Dataflowdiagram,Scenariobasedmodel
2.2 Software RequirementSpecificationdocument f ormat(IEEE)
3 SoftwareEstimationMetrics 7
3.1 SoftwareMetrics,SoftwareProjectEstimation(LOC,FP,COCOMOII)
3.2 Project Scheduling&Tracking
4 SoftwareDesign 7
4.1 DesignPrinciples & Concepts
4.2 EffectiveModularDesign,CohesionandCoupling, Arch itecturaldesign
5 SoftwareTesting 7
5.1 Unittesting,Integrationtesting,Validationtesting,Systemtesting
5.2 TestingTechniques, white -boxtesting:Basispath,Controlstructuretesting
black -box testing :Graphbased,Equivalence,BoundaryValue
5.3 TypesofSo ftwareMaintenance,Re -Engineering, ReverseEngineering
6 Software Configuration Management, Quality Assurance and
Maintenance 7
6.1 RiskAnalysis&Management : Risk Mitigation, Monitoring and Management
Plan (RMMM).
6.2 QualityConceptsandSoftwareQuality assurance
Metrics,FormalTechnicalReviews, SoftwareReliability
6.3 TheSoftware Configuration Management (SCM)
,VersionControlandChangeControl
39

Page 15

Textbooks:
1 Roger Pressman ,“Software Engineering: A Practitioner„s Approach” ,9thedition , McGraw -
Hill Publications , 2019
2 Ian Sommerville ,“Software Engineering” ,9thedition, PearsonEducation, 2011
3 Ali Behfrooz and Fredeick J. Hudson ,"Software Engineering Fundamentals" ,Oxford
UniversityPress, 1997
4 Grady Booch, James Rambaugh, Ivar Jacobson , “The unified modeling language user
guide” , 2nd edition , PearsonEducation, 2005
References:
1 Pankaj Jalote ,"An integrated approach to Software Engineering" ,3rd edition, Springer,
2005
2 Rajib Mall ,"Fundamentals of Software Engineering" , 5th edition, Prentic eHallIndia, 2014
3 Jibitesh Mishra and Ashok Mohanty ,“Software Engineering” ,Pearson , 2011
4 UgrasenSuman ,“Software Engineering – Concepts and Practices” ,CengageLearning, 2013
5 WamanSJawadekar, “Software Engineering principles and practice” , McGraw Hil l
Education ,2004


Assessment :
InternalAssessment:
Assessmentconsistsoftwoclasstestsof20markseach.Thefirst -classtest
istobeconductedwhenapprox.40%syllabusiscompletedandthesecond -
classtestwhenanadditional40%syllabusis completed.Durationofeachtestshallbeo nehour.
EndSemesterTheoryExamination:
1 Questionpaperwillcompriseatotalofsix questions.
2 Allquestioncarriesequalmarks
3 OnlyFourquestions needtobesolved.
4 Inquestionpaperweightageofeachmodulewillbeproportionaltonumberofrespective
lecturehoursasmenti onedinthesyllabus.

UsefulLinks
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

Page 16

Course Code: Course Title Credit
CSC5 03 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 proto cols 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, le arner 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 / supe rnetting schemes .
4 Analyze transport layer protocols and congestion control algorithms.
5 Explore protocols at application layer

Module Content Hr
s
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 services
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: Twistedpair,Coaxial,Fiberoptics.
3 DataLink Layer 8
3.1 DLLDesignIssues(Services, Framing, Error Control,FlowControl),ErrorDet
ection andCorrection(HammingCode,CRC,Checksum) ,
Elementary DataLinkprotocols ,StopandWait,SlidingWindow(GoBackN,S
electiveRepeat)

3.2 Medium Access Control sublayer
ChannelAllocation problem, MultipleaccessProtocol(Aloha,Carrier SenseM
ultiple Access(CSMA/CD)
4 Network layer 12
4.1 NetworkLayer design issues,CommunicationPrimitives:Unicast,Multicast,
Broadcast. IPv4Addressing(classfull andclassless), Subnetting, Supernetting
design problems ,IPv4Protocol, Network AddressTranslation(NAT), IP v6

4.2 Routingalgorithms :Shortest Path(Dijkastra„s),Link staterouting,Distance
VectorRouting
4.3 Protocols -ARP,RARP,ICMP, IGMP

Page 17

4.4 Congestioncontrolalgorithms: Openloopcongestioncontrol,Closedloopco
ngestioncontrol,QoSparameters,Token & Leaky bucket algorithms
5 TransportLayer 6
5.1 TheTransportService :Transportserviceprimitives,BerkeleySockets,Conn
ection management (Handshake), UDP, TCP,TCPstatetransition, TCPtimers
5.2 TCP Flow control(slidingWindow), TCP CongestionControl:Slow Start
6 ApplicationLa yer 6
6.1 DNS:Name Space,ResourceRecordandTypes 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. Ku rose, 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: Principl es, 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 consi sts 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 Examinati on:
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 Fou r 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





Course Code: Course Title Credit

Page 18

CSC504 Data Warehousing a nd 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: Atthe 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 d ata 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 ass ociation 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 Constellation 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, Cleaning, 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 analysi s, 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 ,Aprior i 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.
6 Web Mining 5
Introduction , Web Content Mining: Crawlers, Harvest System, Virtual Web

Page 19

View, Personalization, Web Structure Mining: Page Rank , Clever, Web Usage
Mining .

Textbooks :
1 PaulrajPonniah, “DataWarehou sing:Funda mentalsfor ITProfessionals”,Wiley India.
2 Han, Ka mber, “Data Mining Concepts and Techniques” , MorganKaufmann 2nd edition .
3 M.H. Dunham, “Data Mining Introductory and Advanced Topics” ,Pearson Education.
References:
1 ReemaTheraja, “Datawarehou sing”,Oxford UniversityPress 2009 .
2 Pang -Ning Tan, Michae l 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” , MorganKaufmann3rdedition .

Assessment:
Internal Assessment:
Assessment consists of two class tests o f 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 wi ll 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/noc 20_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: Atthe 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 prob lems using graphical models; design inference algorithms; and learn
the structure of the graphical model from data.
5 Design real life applications using probabilistic graphical models.

Module Content Hrs
1. Introduction to Probabilistic Graphical Mo deling 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 Gr aphs: 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 Direc ted 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 variabl es, 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 Networ k 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 Model s: 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, Learnin g 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, Learnin g 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 Makin g
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.

Page 22

References:
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 carri es 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 wi ll 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_Math ematics_(Sekhon_and_Bloom)/10%3A_Markov_Chains/10.02%3A_A
pplications_of_Markov_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

Page 23

10. https://cs.brown.edu/research/pubs/theses/ugrad/2005/dbooksta.pdf
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

Prerequisit e: 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 ga in ability to develop responsive web applications and explore different web extensions
and web services standards
4 To learn characteristics of RIA and React Js
Course Outcomes:
1 Implement interactive web page(s) using HTML and CSS.
2 Design a respons ive web site using JavaScript andd emonstrate 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 ,
Transfor mations, 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, DH TML 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,
Installin g 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 (RI A) 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 MySQLdata base 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/i tprogramming/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, Inter net 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 , Thir d
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 Hil l, 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. Dura tion 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.w3s chools.com
5 https://spoken -tutorial.org/
6 www.coursera.org

Page 26

The following list can be used as a guideline for mini project:
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 Objecti ves:
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 a bout 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 t ransaction management
3 Organize the data using XMLand JSON database for better interoperability
4 Compare different types of NoSQL databases
5 Formulate NoSQL queries using Mongodb
6 Describe various trends in advance databasesthrough temporal, grap h 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 Datab ase 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 Tra nsformation: 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 Distributi on 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, Comparisonof NoSQL databases w.r.t
CAP theorem and ACID properties.

5 NoSQL using Mo ngoDB 6
5.1 NoSQL using MongoDB: Introduction to MongoDB Shell, Running the

Page 28

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 Tempo ral 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: Introductio n, 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. T amer, Valduriez, Patrick, “Principles of distributed database systems”,3rd
Edition, Pearson Education, Inc.
4 PramodSadalge, Martin Fowler, NoSQL Distilled: A Brief Guide to the Emerging World
of Polyglot Persistence , Addison Wesely/ P earson
5 Jeff Frie sen , 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, D reamtech 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 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 (fo r 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 a s 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/n osql-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 principle s
2 To impart state-of-the-art knowledge on Software Engineering
Lab Outcomes: Onsuccessfulcompletionoflaboratory experiments ,learnerswillbeableto :
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 toa groupoftwo/three students . Laboratory work will be based on cour se 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 Writetestcasesforblackboxtes ting.
8 Writetestcasesforwhiteboxtesting .
9 Preparation of Risk Mitigation, Monitoring and Management Plan (RMMM).
10 Versioncontrolling of the project .


Term Work:
1 Term work should consist of 10 experiments.
2 Journal must include at least 2 assi gnments 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 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 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 fro m 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 NS 2, Wireshark etc. to explore networking
algorithms and protocols.
3 Implement programs using core programming APIs for understanding networking concepts.

Suggested List of Experiments
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. Se tup a network and configure IP addressing, subnetting, masking.
4. Perform network discovery using discovery tools (eg. Nmap, mrtg)
5. Use Wire shark to understand the operation of TCP/IP layers:
● Ethernet Layer: Frame header, Frame sizeetc.
● Data Link Lay er: MAC address, ARP (IP and MAC addressbinding)
● Network Layer: IP Packet (header, fragmentation), ICMP (Query andEcho)
● Transport Layer: TCP Ports, TCP handshake segmentsetc.
● Application Layer: DHCP, FTP, HTTP headerformats
6. Use simulator (Eg. NS2) to u nderstand functioning of ALOHA, CSMA/CD.
7. Study and Installation of Network Simulator (NS3)
8. a. Set up multiple IP addresses on a singleLAN.
b. Using nestat and route commands of Linux, do thefollowing:
● View current routingtable
● Add and deleterout es
● Change default gateway
c. Perform packet filtering by enabling IP forwarding using IPtables inLinux.
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 entir e syllabus of CSC503: Computer Network

Useful Links
1 https://www.netacad.com/courses/packet -tracer/introduction -packet -tracer
2 https://www.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 algorith ms for data mining tasks suchClassification , 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. Imple ment 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 Bayesianal gorithm
5 Implementation of Data Discretization (any one) & Visualization (any one)
6 Perform data Pre -processing task and demonstrateClassification,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 pas sing 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 Cred it
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
augment s student's interactive 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 develo p 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 communic ation 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 organi zational 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 Proposal s: 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 : Modelled 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 , Agend a, 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
Prese ntations 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 , Leadersh ip & 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 Pr operty 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 Sh ort 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).

Page 36

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). Huma nities 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 R iver,
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 Cen gage 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 Ra m (2018) Place Mentor, 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 appr oach
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 appr opriate
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 th rough 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 filing.
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 Proje ct
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, inte gration 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 fou r 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 Stude nts 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 r ecord 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

Page 38

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 Proj ects, 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, w ith 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 semester. 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 g roup 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 Pro ject report 05
Review / progress monitoring committee may consider following points for assessment
based on either one year or half year project asmentioned in general guidelines
One-year project:
1 In one-year project (sem V and VI) , first semester th e 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 fi nalization 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 stude nts‟ 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.

Page 39

Mini Project shall be assessed based on following points
1 Clarity of problem and quality of literature Survey for problem identific ation
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 wo rking 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 be considered for
evaluation of performance of students in mini projects.

Guidelines for Assessment of Mini Project Practical/O ral 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 Ex ternal 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 Conference s/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 underst and the role and function ality of various system programs over application
programs.
2 To understand basic concepts, structure and design of assemblers, macro processors, linkers
and loaders.
3 To understand the basic principles of compiler design, its v arious 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 pro grammer „s
requirements without ambiguity
5 To synthesize the analysis phase outcomes to produce the object code that is efficient in
terms of space and execution time
Course Outcomes: On successful completion of course, learner will be able to
1 Identif y 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 Under stand 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, Assembl y scheme, pass
structure of assembler, Assembler Design: Two pass assembler Design
and single pass 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 lo ader, 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,

Page 41

Design of Lexical analyzer, data structur es used.
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 pha se 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 Dep endent 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 Edi tion
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 Brow n, 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 s oftware: 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 compr ise 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
Cour se 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 messa ge 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, and
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 conce pt 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 Asymm etric 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 publi c 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 Ce rtificate: 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 Aut hentication: Password Base, Challenge
Response Based

Page 43

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. Fer ouzan, “Cryptography & Network Security” , Tata Mc Graw Hill
3 Behrouz A. Forouzan&DebdeepMukhopadhyay ,“Cryptography and Network Security”
3rd Edition, McGraw Hill

Referecebooks :
1 Bruce Schneier, “Applied Cryptography, Protocols Algorithms and Source Cod e in C ”,
Second Edition, Wiley .
2 AtulKahate , “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 t ests 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 pa per 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%20Security%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 issu es 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 compone nts and functioning of mobile networking.
3 To classify variety of security techniques in mobile network.
4 To apply the concepts of WLAN for local 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, Spr ead 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 architect ure
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, Tunne ling 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 L ocal 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 standar d
4.3 Wi-Fi security : WEP ,WPA, Wireless LAN Threats , Securing Wireless
Networks

Page 45

4.4 Bluetooth: Introduction, User Scenario, Architecture, protocol stack
5 Mobility Management 6
5.1 Mobility Management : Introduction, IP Mobility, Optimizati on, 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 Requiremen ts, 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 a nd 5G),
Introduction to 5G

Textbooks:
1 JochenSchilller, “ Mobile Communication ”, Addision wisely, Pearson Education
2 William Stallings “ Wireless Communications & Networks ”, Second Edition, Pearson
Education
3 Christopher Cox, “ An Int roduction 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 , CinziaSartori, “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 DipankarRaychaudhuri, Mario Gerla, “Emerging Wireless Technologies and the
Future Mobile Internet”, Cambridge
5 Andreas F. Molisch, “Wireless Communications”, Second Edition, Wiley Publication

Asses sment :
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 sha ll 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 fr om 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/

Page 47

Course C ode: 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 under stand 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 informatio n.
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 represe ntation
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 desig n 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 Iterativ e 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 Se arch: 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
4.3 Uncertain Knowledge and Reasoning: Uncertainty, Representing

Page 48

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, “ Artificia l 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
Educa tion,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 Thing s (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 rev olutionizing.
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 re volutionizing.
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, Connecte d 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 Sta ck – 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
3.2 Layer 2 – Communications Network Layer, Access Network Sublayer, Gateways
and Backhaul Sublayer, Network Transport Sublayer, IoT Network Management

Page 50

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 Meth ods
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 – Inven tory 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, Indo or 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 Softw are - 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.
2 HakimaChaouchi, “The Internet of Things - Connecting Ob jects to the Web”, 1st
Edition, Wiley, 2010.
3 Perry Lea, “Internet of things For Architects”, 1st Edition, Packt Publication, 2018

Page 51

4 ArshdeepBahga, Vijay Madisetti, “Internet of Things – Hands -On Approach”, 2nd
Edition, Universities Press, 2016.
Refer ences:
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 AnandTamboli , “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
complet ed. 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 modu le 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/specializations/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 Imageprocessing
2 To explore DFT for 1 -D and 2 -D signal and FFT for 1 -Dsignal
3 To apply p rocessing techniques on 1 -D and Imagesignals
4 To apply digital image processing techniques for edgedetection
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 andsystems
3 Implement Digital Signal Transform techniques DFT andFFT
4 Use the enhancement techniques for digital ImageProcessing
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(shift ing, 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
mathemati cal 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
EnergyTheorem). DFT computation using DFT prope rties.
2.3 Convolution of longsequences, 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 Spat ial domain 09
5.1 Gray Level Transformations, Zero Memory Point Operations,
5.2 Histogram Processing, Histogram equalization.

Page 53

5.3 Neighborhood processing, Image averaging, Image Subtraction,
Smoothing Filters - Low pass averaging, Sharpening F ilters -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
Educatio n Asia, 4th Edition, 2018.
4 S. Sridhar, “Digital Image Processing” , 2nd Edition, Oxford University Press, 2012.
References:
1 Sanjit Mitra, “DigitalSignalProcessing:AComputerBasedApproach” ,4thEdition ,
TataMcGrawHill, 2013
2 S.Salivahanan,A.Vallavaraj,an dC.Gnanapriya, “DigitalSignalProcessing” , 2nd
Edition ,TataMcGraw Hill Publication ,2011 .
3 S. Jayaraman, E. Esakkirajan and T. Veerku mar, “Digital Image Processing” , 3rd
Edition, TataMcGraw 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 onehour.
End Semester Theory Examination:
1 Question paper will comprise of total six questions.
2 All question carries equal marks
3 Questions will be mixed i n 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 d rawing 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 likel ihood.
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 Met hods. 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.

Page 55

References:
1 Arora, P.N., Sumeet Arora, 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), Int roduction 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 co mprise 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

Prer equisite: 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 Un iversity. 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 a t 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 wor k.
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 & Practica l 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 vario us 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 dif ferent 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 -sourc e 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 cryptosystem.
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 protoco ls. 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 cap ture 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, Cppchecketc
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 the ory and practical of

Page 58

“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 for term work shal l 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 to ols 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 variou s 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 netw ork
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 be ing 150 m. [variable]. Node #0 and node #1 are the hidden
terminals. Both are transmitting 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 dista nce of separation. To study how RTS/CTS
helps in wireless networks,
1. No RTS/CTS 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 resul ts.

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 commun ications is 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.

Page 60

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 “ M obile
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, Attendance 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 Ar tificial 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 Ex periments (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
application s
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 assig nments 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: 1 5-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 a nd 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 privac y 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 so lve 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 rec ommend 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 a long 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 various 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 i nstall,
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 services provided by them
like Load balancing , Auto -Scaling, Security etc. 4 1

Page 63

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 VNC tools. 4 2
05 Title: To study andImplement Platform as a Service using
AWS Elastic Beanstalk/ Microsoft Azure App Serv ice.
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, Glac iers/ 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 v arious Threat
detection, Data protection and Infrastructure protection
services in AWS and Azure. 3 4
09 Title: To study and implement Identity and Access
Management (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 differen ces between Virtual
machine and Container. It involves demonstration of creating,
finding, building, installing, and running Linux/Windows
application containers inside local machine or cloud platform. 4 6

Page 64

11 Title: To study and implement container orche stration 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 diff erent 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.co m/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/

Page 65

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 publis hing.
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 engi neering 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/whit e paper/ article/blog writing and publication
● The work may result in business plan for entrepreneurship product created
● The work may result in patent filing.
7 Gain technical competency towards participation in Competitions, Hackathons, etc.
8 Demonstrat e 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 preparatio ns, 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 a wareness 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, whi ch 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 a ctivity; 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 wit h 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.

Page 67

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 qualitati ve 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 semester. This policy can be adopted o n 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. m inimum 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 assess ment
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/syst ems,
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.
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

Page 68

4 Design, Analysis a nd 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.