Technology Syllabus Sem VIII Mumbai University PDF

AC:
Item No. :
UNIVERSITY OF MUMBAI
Bachelor of Engineering
in
Information Technology
Final Year with Effect from AY 2022-23
(REV- 2019 ‘C’ Scheme) from Academic Year 2019 – 20

Under
FACULTY OF SCIENCE & TECHNOLOGY

(As per AICTE guidelines with effect from the academic year
2019–2020)
AC:
Item No.
UNIVERSITY OF MUMBAI
Syllabus for Approval
Sr. No.
Heading Particulars
1 Title of the Course Final Year Bachelor of Information Technology
After Passing Third Year Engineering as per the

2 Eligibility for Admission Ordinance 0.6243
3 Passing Marks 40%
Ordinances /
4 Ordinance 0.6243
Regulations ( if any)
5 No. of Years / Semesters 8 semesters
Under Graduation
6 Level
Semester
7 Pattern
Revised
8 Status
To be implemented from
9 With effect from Academic Year: 2022-2023
Academic Year
Date :
Dr. S. K. Ukarande Dr Anuradha Muzumdar

Associate Dean Dean
Faculty of Science and Technology Faculty of Science and Technology
University of Mumbai University of Mumbai
Preamble
To meet the challenge of ensuring excellence in engineering education, the issue of quality needs to be addressed, debated
and taken forward in a systematic manner. Accreditation is the principal means of quality assurance in higher education.
The major emphasis of accreditation process is to measure the outcomes of the program that is being accredited. In line
with this Faculty of Science and Technology (in particular Engineering)of University of Mumbai has taken a lead in
incorporating philosophy of outcome based education in the process of curriculum development.
Faculty resolved that course objectives and course outcomes are to be clearly defined for each course, so that all faculty
members in affiliated institutes understand the depth and approach of course to be taught, which will enhance learner’s
learning process. Choice based Credit and grading system enables a much-required shift in focus from teacher-centric to
learner-centric education since the workload estimated is based on the investment of time in learning and not in teaching.
It also focuses on continuous evaluation which will enhance the quality of education. Credit assignment for courses is
based on 15 weeks teaching learning process, however content of courses is to be taught in 13 weeks and remaining 2
weeks to be utilized for revision, guest lectures, coverage of content beyond syllabus etc.
There was a concern that the earlier revised curriculum more focused on 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 second and third year of programs, which will definitely facilitate self learning of students.
The overall credits and approach of curriculum proposed in the present revision is in line with AICTE model curriculum.
The present curriculum will be implemented for Second Year of Engineering from the academic year 2020-21.
Subsequently this will be carried forward for Third Year and Final Year Engineering in the academic years 2021-22,
2022-23, respectively.
Dr. S. K. Ukarande Dr. Anuradha Muzumdar

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

Associate Dean Dean
Preface By Board of Studies Team
It is our honor and a privilege to present the Rev-2019 ‘C’ scheme syllabus of Bachelor of Engineering
in Information Technology (effective from year 2019-20) with inclusion of cutting edge technology.
Information Technology is comparatively a young branch among other engineering disciplines in the
University of Mumbai. It is evident from the placement statistics of various colleges affiliated to the
University of Mumbai that IT branch has taken the lead in the placement.
The branch also provides multi-faceted scope like better placement and promotion of entrepreneurship
culture among students, and increased Industry Institute Interactions. Industries views are considered
as stakeholders will design of the syllabus of Information Technology. As per Industries views only
16 % graduates are directly employable. One of the reasons is a syllabus which is not in line with the
latest technologies. Our team of faculties has tried to include all the latest technologies in the syllabus.
Also first time we are giving skill-based labs and Mini-project to students from third semester onwards
which will help students to work on latest IT technologies. Also the first time we are giving the choice
of elective from fifth semester such that students will be master in one of the IT domain. The syllabus
is peer reviewed by experts from reputed industries and as per their suggestions it covers future trends
in IT technology and research opportunities available due to these trends.
We would like to thank senior faculties of IT department of all colleges affiliated to University of
Mumbai for significant contribution in framing the syllabus. Also on behalf of all faculties we thank
all the industry experts for their valuable feedback and suggestions. We sincerely hope that the revised
syllabus will help all graduate engineers to face the future challenges in the field of information and
technology
Program Specific Outcome for graduate Program in Information Technology
1. Apply Core Information Technology knowledge to develop stable and secure IT system.
2. Design, IT infrastructures for an enterprise using concepts of best practices in information
Technology and security domain.
3. Ability to work in multidisciplinary projects and make it IT enabled.
4. Ability to adapt latest trends and technologies like Analytics, Blockchain, Cloud, Data science.
Board of Studies in Information Technology - Team

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

University of Mumbai
Program Structure for Fourth Year Information Technology Semester
VII & VIII
UNIVERSITY OFMUMBAI
(With Effect from2022-2023)
Semester VIII
Teaching Scheme
Credits Assigned
Course (Contact Hours)
Course Name
Code Pract.
Theory Theory Pract. Total
Tut.
ITC801 Blockchain and DLT 3 -- 3 -- 3
ITDO801 Department Optional Course – 5 3 -- 3 -- 3
X
ITDO802 Department Optional Course – 6 3 -- 3 -- 3
X
ITIO801X Institute Optional Course – 2 3 -- 3 -- 3
ITL801 Blockchain Lab -- 2 -- 1 1

ITL802 Cloud computing -- 2 -- 1 1
ITP801 Major Project II -- 12# -- 6 6
Total 12 16 12 8 20
Examination Scheme
Term Prac
Theory Total
Work /oral
Course End Exam.
Course Name Duratio
Code Internal Assessment Sem
n
Exam (in Hrs)
Test1 Test2 Avg
ITC801 Blockchain and DLT 20 20 20 80 3 -- -- 100

ITDO801 Department Optional Course – 5 20 20 20 80 3 -- -- 100
X
ITDO802 Department Optional Course – 6 20 20 20 80 3 -- -- 100
X
ILO801X Institute Optional Course – 2 20 20 20 80 3 -- -- 100
ITL801 Blockchain Lab -- -- -- -- -- 25 25 50

ITL802 Cloud computing -- -- -- -- -- 25 25 50
ITP801 Major Project II -- -- -- -- -- 100 50 150
Total -- -- 80 320 -- 150 100 650
# indicates work load of Learner (Not Faculty), for Major Project
Students group and load of faculty per week.

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

Students can form groups with minimum 2 (Two) and not more than 4 (Four)
Faculty Load : In Semester VII – ½ hour per week per project group
In Semester VIII – 1 hour per week per project group
ITDO801X Department Optional Course – 5
ITDO8011 Big Data Analytics
ITDO8012 Reinforcement learning
ITDO8013 Simulation and Modeling
ITDO8014 Knowledge management
ITDO802X Department Optional Course –6

ITDO8021 User Interface Design
ITDO8022 Robotics
ITDO8023 ERP
ITDO8024 Cloud computing and Services
# Institute Level Optional Course (ILO)
Every student is required to take one Institute Elective Course for Semester VIII, which is
not closely allied to their disciplines. Different sets of courses will run in the both the
semesters.
ILO801X Institute Optional Course – 2 ( Common for all branches will be notified )
ILO8011 Project Management
ILO8012 Finance Management
ILO8013 Entrepreneurship Development
and Management
ILO8014 Human Resource Management

ILO8015 Professional Ethics and CSR
ILO8016 Research Methodology
ILO8017 IPR and Patenting
ILO8018 Digital Business Management
ILO8019 Environmental Management
Course Code Course Theory Practical Tutorial Theory Practical/ Tutorial Total
Name Oral
ITC801 Blockchain 03 -- -- 03 -- -- 03
and DLT
Examination Scheme
Theory Marks
Course
Course Code Internal assessment
Name End Term
Practical Oral Total
Avg. Sem. Work
Test1 Test 2 of 2 Exam
Tests
ITC801 Blockchain
20 20 20 80 -- -- -- 100
and DLT
Course Objectives:
Sr.No Course Objectives

1 To get acquainted with the concept of Distributed ledger system and Blockchain.
2 To learn the concepts of consensus and mining in Blockchain through the Bitcoin network.
3 To understand Ethereum and develop-deploy smart contracts using different tools and frameworks.
4 To understand permissioned Blockchain and explore Hyperledger Fabric.
5 To understand different types of crypto assets.
6 To apply Blockchain for different domains IOT, AI and Cyber Security.
Course Outcomes:
Sr. Course Outcomes Cognitive levels of
No attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Describe the basic concept of Blockchain and Distributed Ledger Technology. L1,L2
2 Interpret the knowledge of the Bitcoin network, nodes, keys, wallets and transactions L1,L2,L3
3 Implement smart contracts in Ethereum using different development frameworks. L1,L2,L3
4 Develop applications in permissioned Hyperledger Fabric network. L1,L2,L3
5 Interpret different Crypto assets and Crypto currencies L1,L2,L3
6 Analyze the use of Blockchain with AI, IoT and Cyber Security using case studies. L1,L2,L3,L4
Prerequisite: Cryptography and Distributed Systems.
DETAILED SYLLABUS:
Sr. Module Detailed Content Hours CO

No. Mapping
0 Cryptography and Hash functions, Public – Private keys, SHA, ECC, Digital 02 —-
Distributed Systems signatures, Fundamental concepts of Distributed systems
(prerequisite)
University of Mumbai, B. E. (Information Technology), Rev 2016 273

I Introduction to DLT Introduction to Blockchain: Technical definition of 04 CO1
and Blockchain Blockchain. Elements of a blockchain Features of
Blockchain Type of Blockchain, What is DLT . DLT V/S
Blockchain CAP theorem Byzantine Generals Problem
Consensus Mechanism and its Type Cryptographic
primitives and data structure used in blockchain
Block in a Blockchain: Structure of a Block, Block

Header Hash and Block Height, The Genesis Block,
Linking Blocks in the Blockchain, Merkle Tree.
Self-learning Topics: Blockchain Demo
II Bitcoin What is Bitcoin and the history of Bitcoin, Bitcoin 08 CO2

Transactions, Bitcoin Concepts: keys, addresses and
wallets, Bitcoin Transactions, UTXO. validation of
transactions, Bitcoin Keys , Addresses, ECC , Base58 ,
BIP-38 , Pay-to Script and Multisig Addresses, Vanity
Addresses , Concept of Wallet, Wallet Technologies in
Bitcoin HD wallet from Seed. Transaction Scripts and
Scripts address, Bitcoin Mining and Difficulty levels
Structure of Blocks and Blockheader and Genesis Block ,
linking of Block.
Bitcoin Network: Bitcoin Core node and API, Peer-to-

Peer Network Architecture, Node Types and Roles,
Incentive based Engineering, The Extended Bitcoin
Network, Bitcoin Relay Networks, Network Discovery,
Full Nodes, Exchanging “Inventory”, Simplified Payment
Verification (SPV) Nodes, SPV Nodes and Privacy,
Transaction Pools, Blockchain Forks Bitcoin Testnet
Basics of Bitcoin Forensics: Analysis of Address and
Wallet , Clustering of Addresses following Money
Self-learning Topics: Study and compare different

consensus algorithms like PoA, PoS, pBFT
III Permissionless Introduction to Ethereum, Ethereum 1.0 and 2.0 , Turing 10 CO3
Blockchain: completeness EVM and compare with bitcoin Basics of
Ethereum Ether Units, Ethereum Wallets Working with Metamask
EOA and Contracts Transaction:: Structure of Transaction,
Transaction Nonce, Transaction GAS, Recipient, Values
and Data, Transmitting Values to EOA and Contracts
Smart Contracts and Solidity
Development environment and client , Basic of Solidity

and Web 3 Life cycle of Smart contract, Smart Contract
programming using solidity, Metamask (Ethereum

Wallet), Setting up development environment, Use cases of
Smart Contract, Smart Contracts: Opportunities and Risk.
Smart Contract Deployment: Introduction to Truffle,

Use of Remix and test networks for deployment
Self-learning Topics: Smart contract development using

Java or Python
IV Permissioned Introduction to Framework, Tools and Architecture of 07 CO4

Blockchain: Hyperledger Fabric Blockchain.
Hyperledger Fabric
Components: Certificate Authority, Nodes, Chain codes,
Channels, Consensus: Solo, Kafka, RAFT Designing
Hyperledger Blockchain Other Challenges :
Interoperability and Scalability of blockchain
Self-learning Topics: Fundamentals of Hyperledger

Composer
V Crypto assets and ERC20 and ERC721 Tokens, comparison between 04 CO5
Cryptocurrencies ERC20 & ERC721, NFT, ICO, STO, Different Crypto
currencies
Self-learning Topics: Defi, Metaverse, Types of

cryptocurrencies
VI Blockchain Blockchain in IoT, AI, Cyber Security 04 CO6

Applications & case
studies Self-learning Topics: Applications of Blockchain in
various domains Education, Energy, Healthcare, real-
estate, logistics, supply chain
Text Books:
1. “Mastering Bitcoin, PROGRAMMING THE OPEN BLOCKCHAIN”, 2nd Edition by Andreas M. Antonopoulos, June
2017, Publisher(s): O'Reilly Media, Inc. ISBN: 9781491954386.
2. Mastering Ethereum, Building Smart Contract and Dapps, Andreas M. Antonopoulos Dr. Gavin Wood, O'reilly.
3. Blockchain Technology, Chandramouli Subramanian, Asha A George, Abhillash K. A and Meena Karthikeyen,
Universities press.
4. Hyperledger Fabric In-Depth: Learn, Build and Deploy Blockchain Applications Using Hyperledger Fabric, Ashwani
Kumar, BPB publications
5. Solidity Programming Essentials: A beginner's Guide to Build Smart Contracts for Ethereum and Blockchain, Ritesh Modi,
Packt publication
6. Cryptoassets: The Innovative Investor’s Guide to Bitcoin and Beyond, Chris Burniske & Jack Tatar.
Reference Books:
1. Mastering Blockchain, Imran Bashir, Packt Publishing 2. Mastering Bitcoin Unlocking Digital Cryptocurrencies, Andreas
M. Antonopoulos, O'Reilly Media
2. Blockchain Technology: Concepts and Applications, Kumar Saurabh and Ashutosh Saxena, Wiley.
3. The Basics of Bitcoins and Blockchains: An Introduction to Cryptocurrencies and the Technology that Powers Them,
Antony Lewis. for Ethereum and Blockchain, Ritesh Modi, Packt publication.
4. Mastering Bitcoin Unlocking Digital Cryptocurrencies, Andreas M. Antonopoulos, O'Reilly Media
Online References:
1. NPTEL courses:
a. Blockchain and its Applications,
b. Blockchain Architecture Design and Use Cases
2. www.swayam.gov.in/
3. www.coursera.org
4. https://ethereum.org/en/
5. https://www.trufflesuite.com/tutorials
6. https://hyperledger-fabric.readthedocs.io/en/release-2.2/whatis.h
7. Blockchain demo: https://andersbrownworth.com/blockchain/
8. Blockchain Demo: Public / Private Keys & Signing: https://andersbrownworth.com/blockchain/public-private-keys/
Assessment:
Internal Assessment (IA) for 20 marks:
 IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
 Question paper format
 Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus
 Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
A total of four questions need to be answered.

Teaching Scheme (Contact
Hours) Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical Tutorial Total
& Oral
ITL801 Blockchain Lab -- 2 -- -- 1 -- 01
Examination Scheme
Theory Marks
Course Code Course Name
Internal assessment End Term Practical/
Total
Avg. of Sem. Work Oral
Test1 Test 2
2 Tests Exam
ITL801 Blockchain Lab
-- -- -- -- 25 25 50
Lab Objectives:
Sr.No Lab Objectives

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

attainment as per
Bloom’s Taxonomy
1 Develop and test smart contract on local Blockchain. L3,L4
2 Develop and test smart contract on Ethereum test networks. L3,L4
3 Write and deploy smart contract using Remix IDE and Metamask. L4
4 Design and develop Cryptocurrency. L4
5 Write and deploy chain code in Hyperledger Fabric. L4
6 Develop and test a Full-fledged DApp using Ethereum/Hyperledger. L5
Prerequisite: Programming Langauges.
DETAILED SYLLABUS:
Sr. Module Detailed Content Hours LO

No. Mapping
0 Prerequisite Java, Python, JavaScript 02 —
I Local Blockchain Introduction to Truffle, establishing local Blockchain 02 LO1

using Truffle
Mini Project: Allocation of the groups
II Smart contracts and Solidity programming language, chain code 04 LO2
(Java/JavaScript/Go), deployment on Truffle local
Chain code Blockchain
Mini Project: Topic selection
III Deployment and Ethereum Test networks 04 LO3
publishing smart (Ropsten/Gorelli/Rinkeby), deployment on test
contracts on networks, Web3.js/Web3.py for interaction with
Ethereum smart contract
Ethereum test
Mini Project: Topic validation and finalizing software
network requirements
IV Remix IDE and Smart contract development and deployment using 04 LO4
Metamask Metamask and Remix
Design and develop Crypto currency
Mini Project: Study the required programming
language for smart contract
V Chain code Chain code deployment in Hyperledger fabric 04 LO5
deployment in Mini project: Study required front end tools
Hyperledger Fabric
VI Mini-project on Implementation of Mini Project 06 LO6
Design and 1. Design, configure and testing of mini project
Development of a 2. Report submission as per guidelines
DApps using
Ethereum/Hyperledg
er Fabric
Mini project:
1. Students should carry out mini-project in a group of three/four students with a subject In-charge
2. The group should meet with the concerned faculty during laboratory hours and the progress of work discussed must be
documented.
3. Each group should perform a detailed literature survey and formulate a problem statement.
4. Each group will identify the hardware and software requirement for their defined mini project problem statement.
5. Design, develop and test their smart contract/chain code.
6. Each group may present their work in various project competitions and paper presentations
Documentation of the Mini Project
The Mini Project Report can be made on following lines:

1. Abstract
2. Contents
3. List of figures and tables
4. Chapter-1 (Introduction, Literature survey, Problem definition, Objectives, Proposed Solution, Technology/platform used)
5. Chapter-2 (System design/Block diagram, Flow chart, Software requirements, cost estimation)
6. Chapter-3 (Implementation snapshots/figures with explanation, code, future directions)
7. Chapter-4 (Conclusion)
8. References
Text Books:
1. Ethereum Smart Contract Development, Mayukh Mukhopadhyay, Packt publication.

2. Solidity Programming Essentials: A Beginner's Guide to Build Smart Contracts for Ethereum and Blockchain, Ritesh Modi,
Packt publication.
3. Hands-on Smart Contract Development with Hyperledger Fabric V2, Matt Zand, Xun Wu and Mark Anthony Morris,
O’Reilly.
References Books:
1. Mastering Blockchain, Imran Bashir, Packt Publishing

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

Teaching Scheme (Contact
Hours) Credits Assigned
Course Code Course Name Theory Practical Tutorial Theory Practical Tutorial Total
& Oral
ITL802 Cloud Computing -- 2 -- -- 1 -- 01
Examination Scheme
Theory Marks
Course Code Course Name
Internal assessment End Term Practical/
Total
Avg. of Sem. Work Oral
Test1 Test 2
2 Tests Exam
ITL802 Cloud
Computing -- -- -- -- 25 25 50
Lab Objectives:
Sr.No Lab 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.
3 To understand the using and adopting appropriate type of cloud for their application.
4 To make students familiar with various service models such as IaaS, SaaS, PaaS, Security as
a Service (SECaaS) and Database as a Service.
5 Apply the different service models for the application.
6 To make students familiar with security and privacy issues in cloud computing and how to
address them.
Lab Outcomes:
Sr.No Lab Outcomes Cognitive levels of

attainment as per
Bloom’s Taxonomy
1 Implement different types of virtualization techniques. L1,LL3,L4
2 Analyze various cloud computing service models and implement them to solve L1,L2,L3,L4
the given problems.
3 Design and develop real world web applications and deploy them on commercial L6
cloud(s).
4 Explain major security issues in the cloud and mechanisms to address them. L1,L2,L3
5 Explore various commercially available cloud services and recommend the appropriate L1,L2,L3
one for the given application.
6 Implement the concept of containerization. L1,L2,L3
Prerequisite: Programming Langauges, DBMS.
DETAILED SYLLABUS:
Sr. Module Detailed Content Hours LO

No. Mapping

0 Prerequisite DBMS, Programming Language. 02 —
I Overview & Introduction and overview of cloudcomputing. 04 LO1

Virtualization. Hosted Virtualization using KVM.
Lab1: To study and implement Hosted Virtualization

usingVirtual Box & KVM.
Lab2: To study and Implement Bare-metal

Virtualization using Xen, HyperV or VMware Esxi.
II Infrastructure To study the infrastructure services using different 04 LO2
Services. cloud platform
Lab3: To study and Implement Infrastructure as a

Service usingAWS/Microsoft Azure/Google cloud
platform
III Platform Services To study the different platform services. 03 LO3
Lab4: To study and Implement Platform as a Service

using AWS Elastic Beanstalk/ Microsoft Azure App
Service.
IV Cloud Services IaaS, PaaS, STaaS, DbaaS, IAM andSecurity as a 04 LO4
Service on AWS and Azure.
Lab5: To study and Implement Security as a

Service onAWS/Azure.
Lab6: To study and implement Identity and Access

Management (IAM) practices on AWS/Azure
cloud.
V Storage Services To study the storage services using Docker. 04 LO5
Lab7: To study and Implement Storage as a

Service using Own Cloud/ AWS S3, Glaciers/
Azure Storage.
Lab8: To study and Implement Database as a
Service on SQL/NOSQL databases like AWS
RDS, AZURE SQL/MongoDB Lab/ Firebase.
Lab9: To study and Implement Containerization
using Docker on AWS/Azure/Google cloud
platform.
VI Kubermetes Introduction and overview of Kubernetes. 05 LO6
Lab10: To study and implement container

orchestration using Kubernetes on
AWS/Azure/Google cloud platform
Textbooks:
1 Bernard Golden, “Amazon Web Services for Dummies”, John Wiley & Sons, Inc.

2 Michael Collier, Robin Shahan, “Fundamentals of Azure, Microsoft Azure Essentials”,
Microsoft Press.
3 RajkumarBuyya, Christian Vecchiola, S ThamaraiSelvi, “Mastering Cloud Computing”,
Tata McGraw-Hill Education.
4 Barrie Sosinsky, “Cloud Computing Bible”, Wiley publishing.
5 John Paul Mueller, “AWS for Admins for Developers”, John Wiley & Sons, Inc.
6 Ken Cochrane, Jeeva S. Chelladhurai, NeependraKhare , “Docker Cookbook - Second
Edition”, Packt publication
7 Jonathan Baier, “Getting Started with Kubernetes-Second Edition”, Packt Publication.
Online References:
1. https://phoenixnap.com/kb/ubuntu-install- kvm\
2. NIST Cloud Computing Security Reference Architecture
3. https://docs.citrix.com/en-us/xenserver/7- 1/install.html
4. https://docs.aws.amazon.com
5. https://docs.microsoft.com/en-us/azure
6. https://docs.docker.com/get-started/
7. https://kubernetes.io/docs/home/
Term-Work: Term-Work shall consist of 10 experiments on above guidelines/syllabus. Also, Term-work must include at least 2
assignments.
Term Work Marks: 25 Marks (Total marks) =15 Marks (Experiments) + 5 Marks (Assignments) + 5 Marks (Attendance)
Oral Exam: An Oral exam will be held based on the syllabus.

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

– II
Examination Scheme
Course Course Name
Code Theory Marks
Internal assessment End
Term Work Pract. /Oral Total
Sem.
Test1 Test 2 Avg.
Exam
ITM7 Major Project
01 – II -- -- -- -- 100 50 150
Course Objectives
1. To acquaint with the process of identifying the needs and converting it into the problem.
2. To familiarize the process of solving the problem in a group.
3. To acquaint with the process of applying basic engineering fundamentals to attempt solutions to the problems.
4. To inculcate the process of self-learning and research.
Course Outcome: Learner will be able to…
1. Identify problems based on societal /research needs.
2. Apply Knowledge and skill to solve societal problems in a group.
3. Develop interpersonal skills to work as member of a group or leader.
4. Draw the proper inferences from available results through theoretical/ experimental/simulations.
5. Analyse the impact of solutions in societal and environmental context for sustainable development.
6. Use standard norms of engineering practices
7. Excel in written and oral communication.
8. Demonstrate capabilities of self-learning in a group, which leads to life long learning.
9. Demonstrate project management principles during project work.
Guidelines for Major Project

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

 Students shall convert the best solution into working model using various components of their domain areas and
demonstrate.
 The solution to be validated with proper justification and report to be compiled in standard format of University
of Mumbai.
 With the focus on the self-learning, innovation, addressing societal problems and entrepreneurship quality
development within the students through the Major Project, it is preferable that a single project of appropriate
level and quality to be carried out in two semesters by all the groups of the students. i.e. Major Project-I in
semester VII and Major Project-II in semesters VIII.
 However, based on the individual students or group capability, with the mentor’s recommendations, if the
proposed Major Project adhering to the qualitative aspects mentioned above gets completed in odd semester,
then that group can be allowed to Scopus paper publications in Journal/Conference or Copyright or Patent as an
extension of the Major Project-1 with suitable improvements/modifications after testing and analysis in even
semester. This policy can be adopted on case by case basis.
Guidelines for Assessment of Major Project:
Term Work
1. The review/ progress monitoring committee shall be constituted by head of departments of each institute.
The progress of major project to be evaluated on continuous basis, minimum two reviews in each
semester VII and VIII.
2. In continuous assessment focus shall also be on each individual student, assessment based on individual’s
contribution in group activity, their understanding and response to questions.
3. Distribution of Term work marks for both semesters shall be as below;
a. Marks awarded by guide/supervisor based on log book : 10
b. Marks awarded by review committee : 10
c. Quality of Project report : 05
Review/progress monitoring committee may consider following points for assessment based on either one year
major project as mentioned in general guidelines.
One-year project:
 In semester VII entire theoretical solution shall be ready, including components/system selection and cost
analysis, building of working prototype. Two reviews will be conducted based on presentation given by
students group.
 First shall be for finalization of problem and proposed solution of the problem
 Second shall be on readiness of working and testing of prototype to be conducted.
 In semester VIII expected work shall be procurement of testing and validation of results based on work
completed in an odd semester.
 First review is based on improvements in testing and validation results cum demonstration for
publication to be conducted.
 Second review shall be based on paper presentation in conference/journal or motivate for
copyright or Indian patent in last month of the said semester.
Assessment criteria of Major Project.
Major Project shall be assessed based on following criteria;

14. Quality of survey/ need identification
15. Clarity of Problem definition based on need.
16. Innovativeness in solutions
17. Feasibility of proposed problem solutions and selection of best solution
18. Cost effectiveness
19. Societal impact
20. Innovativeness
21. Cost effectiveness and Societal impact
22. Full functioning of working model as per stated requirements
23. Effective use of skill sets
24. Effective use of standard engineering norms
25. Contribution of an individual’s as member or leader
26. Clarity in written and oral communication
 In one year, project, first semester evaluation may be based on first six criteria’s and remaining may be
used for second semester evaluation of performance of students in mini project.
Guidelines for Assessment of Major Project Practical/Oral Examination:
 Report should be prepared as per the guidelines issued by the University of Mumbai.
 Major Project shall be assessed through a presentation and demonstration of working model by the student project
group to a panel of Internal and External Examiners preferably from industry or research organizations having
experience of more than five years approved by head of Institution.
 Students shall be motivated to publish a paper based on the work in Scopus Conferences/Journals or copy right
or Indian Patent.
Major Project shall be assessed based on following points;

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

Name Oral
ITDO8011 Big Data 03 -- -- 03 -- -- 03
Analytics
Examination Scheme
Theory Marks
Course
Course Code Internal assessment End Term
Name Practical Oral Total
Avg. of 2 Sem. Work
Test1 Test 2
Tests Exam
ITDO8011 Big Data
20 20 20 80 -- -- -- 100
Analytics
Course Objectives:

1 To provide an overview of an exciting growing field of Big Data analytics.
2 To discuss the challenges traditional data mining algorithms face when analyzing Big Data.
3 To introduce the tools required to manage and analyze big data like Hadoop, NoSql MapReduce.
4 To teach the fundamental techniques and principles in achieving big data analytics with scalability and
streaming capability.
5 To introduce to the students several types of big data like social media, web graphs and data streams.
6 To enable students to have skills that will help them to solve complex real-world problems in decision support.
Course Outcomes:
Bloom’s Taxonomy
1 Explain the motivation for big data systems and identify the main sources of Big Data L1,L2,L3
in the real world.
2 Demonstrate an ability to use frameworks like Hadoop, NOSQL to efficiently store, L1,L2,L3
retrieve and process Big Data for Analytics.
3 Implement several Data Intensive tasks using the Map Reduce Paradigm. L1,L2,L3
4 Apply several newer algorithms for Clustering Classifying and finding associations in L1,L2,L3
Big Data.
5 Design algorithms to analyze Big data like streams, Web Graphs and Social Media data. L6
6 Design and implement successful Recommendation engines for enterprises. L6
Prerequisite: AI and DS
DETAILED SYLLABUS:
Sr. Module Detailed Content Hours CO Mapping

No.
0 Prerequisite Data Mining, Data Science 02
I Introduction to Introduction to Big Data, Big Data characteristics, types of 03 CO1

Big Data Big Data, Traditional vs. Big Data business approach, Big
Data Challenges, Examples of Big Data in Real Life, Big
Data Applications
Self-learning Topics: Identification of Big Data applications
and its solutions
II Introduction to What is Hadoop? Core Hadoop Components; Hadoop 06 CO2

Big Data Ecosystem; Working with Apache Spark
Frameworks What is NoSQL? NoSQL data architecture patterns: Key-
value stores, Graph stores, Column family (Bigtable) stores,
Document stores, MongoDB
Self-learning Topics: HDFS vs GFS, MongoDB vs other
NoSQL system, Implementation of Apache Spark
III MapReduce MapReduce: The Map Tasks, Grouping by Key, The Reduce 07 CO3
Paradigm Tasks, Combiners, Details of MapReduce Execution, Coping
With Node Failures. Algorithms Using MapReduce: Matrix-
Vector Multiplication by MapReduce , Relational-Algebra
Operations, Computing Selections by MapReduce,
Computing Projections by MapReduce, Union, Intersection,
and Difference by MapReduce, Computing Natural Join by
MapReduce, Grouping and Aggregation by MapReduce,
Matrix Multiplication, Matrix Multiplication with One
MapReduce Step . Illustrating use of MapReduce with use of
real life databases and applications.
Self-learning Topics: Implementation of MapReduce
algorithms like Word count, Matrix-Vector and Matrix-
Matrix algorithm
IV Mining Big Data The Stream Data Model: A DataStream-Management System, 07 CO4
Streams Examples of Stream Sources, Stream Queries, Issues in
Stream Processing. Sampling Data in a Stream : Sampling
Techniques. Filtering Streams: The Bloom Filter Counting
Distinct Elements in a Stream : The Count-Distinct Problem,
The Flajolet-Martin Algorithm, Combining Estimates, Space
Requirements . Counting Ones in a Window: The Cost of
Exact Counts, The Datar-Gionis-Indyk, Motwani Algorithm,
Query Answering in the DGIM Algorithm.
Self-learning Topics: Streaming services like Apache
Kafka/Amazon Kinesis/Google Cloud DataFlow.
Standard spark streaming library.
Integration with IOT devices to capture real time stream data.
V Big Data Mining Frequent Pattern Mining : Handling Larger Datasets in Main 07 CO5
Algorithms Memory Basic Algorithm of Park, Chen, and Yu. The SON
Algorithm and MapReduce. Clustering Algorithms: CURE
Algorithm. Canopy Clustering, Clustering with MapReduce
Classification Algorithms: Overview SVM classifiers,
Parallel SVM, KNearest Neighbor classifications for Big
Data, One Nearest Neighbour.
Self-learning Topics: Standard libraries included with spark
like graphX, MLlib
VI Big Data Link Analysis : PageRank Definition, Structure of the web, 07 CO6
Analytics dead ends, Using Page rank in a search engine, Efficient
Applications computation of Page Rank: PageRank Iteration Using
MapReduce, Topic sensitive Page Rank, link Spam, Hubs and
Authorities, HITS Algorithm.
Mining Social- Network Graphs : Social Networks as
Graphs, Types , Clustering of Social Network Graphs, Direct
Discovery of Communities, Counting triangles using Map-
Reduce.
Recommendation Engines: A Model for Recommendation
Systems, Content-Based Recommendations, Collaborative
Filtering
Self-learning Topics: Sample applications like social media
feeds, multiplayer game interactions, retail industry, financial
data analysis. Use case like location data, real-time stock
trades, log monitoring etc
Text Books:
1. Anand Rajaraman and Jeff Ullman “Mining of Massive Datasets”, Cambridge University Press.
2. Alex Holmes “Hadoop in Practice”, Manning Press, Dreamtech Press.
3. Professional NoSQL Paperback, by Shashank Tiwari, Dreamtech Press
4. Rajkumar Buyya, ,Rodrigo N. Calheiros and Amir Vahid Dastjerdi, “Big Data Principles and Paradigms”, Morgan Kaufmann
References Books:
1. Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, Bart Baesens , WILEY Big Data
Series.
2. Big Data Analytics with R and Hadoop by Vignesh Prajapati Paperback, Packt Publishing Limited
3. Hadoop: The Definitive Guide by Tom White, O'Reilly Publications
Online References:
1. https://nptel.ac.in/courses/106/104/106104189/
2. https://nptel.ac.in/courses/106106142/
3. https://nptel.ac.in/courses/106105186/
Assessment:

Test

Course Code Course Name Theory Practical Tutorial Theory Practical/Oral Tutorial Total
ITDO8012 Reinforcement 03 -- -- 03 -- -- 03
Learning
Examination Scheme
Course Theory Marks
Course Name
Code Internal assessment End Term
Avg. of 2 Sem. Work
Test1 Test 2
Tests Exam
ITDO8012 Reinforcement
Learning 20 20 20 80 -- -- -- 100
Course Objectives:

1 Define the key features of reinforcement learning that distinguishes it from AI and non-interactive machine
learning.
2 Introduce to statistical learning techniques where an agent explicitly takes actions and interacts with the world.
3 Implement in code common RL algorithms.
4 Describe multiple criteria for analyzing RL algorithms & evaluate algorithms on these metrics: e.g. regret,
sample complexity, computational complexity, empirical performance, convergence, etc.
5 Know how to implement dynamic programming as an efficient solution approach to an industrial control
problem.
6 Explore solutions to the Exploration-Exploitation Dilemma.
Course Outcomes:
Bloom’s Taxonomy
1 Learn how to define RL tasks and the core principles behind the RL, including policies, L1,L2
value functions, deriving Bellman equations.
2 Evaluate work with tabular methods to solve classical control problems. L1,L2,L3
3 Apply Markov Decision Processes to solve real-world problems. L1,L2,L3
4 Understand the dynamic programming for policy Evaluation. L1,L2
5 Implement reinforcement learning problems based on averaging sample returns using L1,L2,L3
Monte Carlo method.
6 Recognize current advanced techniques and applications in RL. L1,L2,L3
DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours CO

Mapping
0 Prerequisite Probability distributions and expected values, and basic linear 02

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

2. Alessandro Palmas, Dr. Alexandra Galina Petre, Emanuele Ghelfi, The Reinforcement Learning Workshop: Learn how to
Apply Cutting-edge Reinforcement Learning Algorithms to a Wide Range of Control Problems, 2020 Packt publishing.
3. Phil Winder, Reinforcement Learning Industrial Applications with Intelligent Agents, O’Reilly
4. Dr Engr S M Farrukh Akhtar, Practical Reinforcement Learning, Packt Publishing, 2017.
References Books:
1. Maxim Lapan, Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value
iteration, policy gradients, TRPO, AlphaGo Zero.
2. Csaba Szepesv´ari, Algorithms for Reinforcement Learning, Morgan & Claypool Publishers
3. Alberto Leon-Garcia, Probability, Statistics and Random Processes for Electrical Engineering, Third Edition, Pearson
Education, Inc.
Assessment:
Test


Name Oral
ITDO8013 Theory 03 -- -- 03 -- -- 03
Course
Examination Scheme
Course Theory Marks
Course Name
Test Avg. of 2 Sem. Work
Test 2
1 Tests Exam
ITDO8013 Simulation
and Modeling 20 20 20 80 -- -- -- 100
Course Objectives:

1 To introduce the discrete event simulation systems.
2 To discuss the modeling techniques of entities, queues, resources and entity transfers in the discrete event
environment.
3 To formulate and apply the statistical models in simulation and queuing theory.
4 To gain knowledge of random numbers, random variates and various statistical tests on random numbers.
5 To formulate and build valid models and perform simulation analysis of the system and analyze results
properly.
6 To familiarize with various applications of Simulation.
Course Outcomes:
Sr. Course Outcomes Cognitive levels
No of attainment as
per Bloom’s
Taxonomy
1 Understand the meaning of simulation and Identify the common applications of L1,L2
discrete-event system simulation.
2 Practice formulation and modeling skills. L1,L2,L3
3 Analyze events and inter-arrival time, arrival process, queuing strategies, resources and L1,L2,L3,L4
disposal of entities using statistical models.
4 Understand pseudo-random numbers and perform statistical tests to measure the quality L1,L2
of pseudo-random numbers.
5 Apply different distributions to fit the collected data and describe the process of L1,L2,L3
verification and validation of simulation models.
6 Describe various applications of simulation. L1,L2
Prerequisite: Probability and Statistics
DETAILED SYLLABUS:

No. Mapping

0 Prerequisite Concepts of Probability: Probability mass 02 -
function, Probability density function, Mean,
Variance, Median, Mode
I Introduction to Simulation Definition, When Simulation is an 04 CO1
Simulation appropriate tool and when it is not, Advantages
and disadvantages of simulation, Areas of
application of simulation, System and its types,
Models and its types, Steps in simulation study
Self-learning Topics: Monte Carlo simulation
II Simulation Simulation Process, Simulation of Single-server 08 CO2
Examples and and multi-server queueing systems, Simulation of
General Principles (M, N) Inventory and Newspaper Seller Problem,
Simulation of Lead-time Demand
Concepts in Discrete Event Simulation, Event
Scheduling Algorithm, Manual Simulation of
Single Server and Dump Truck Problem using
Event Scheduling Algorithm
Self-learning Topics: Simulation of Reliability
Problem, Process Interaction Approach in
Simulation.
III Mathematical Statistical Models: Terminology and concepts, 08 CO3
,Statistical and Useful statistical models, Discrete Distributions
Queueing Models in (Bernoulli’s trial, Binomial and Negative
Simulation Binomial, Poisson Distributions), Continuous
Distributions (Exponential, Uniform, Erlang,
Triangular and Normal Distributions), Poisson
Process,
Queueing Models: Queuing Notations, Long Run
Performance Measures, M/M/1 and M/G/1
Queueing Systems
IV Random Numbers Random Number Generation: Why are random 08 CO4
and Variates numbers required in simulation? Properties of
random numbers, Linear Congruential Method to
generate Random Numbers, Test for Uniformity:
Kolmogorov-Smirnov, Chi-Square, Test for
Independence: Runs up and runs down, Runs
above and below mean, Poker test), Random
Variate Generation: Inverse Transform
Technique, Direct Transformation for Normal
and Lognormal distribution, Acceptance
Rejection Technique
Self-learning Topics: Tests for Autocorrelation
V Analysis of Steps in Input Modeling, Goodness-of-fit tests, 06 CO5
Simulation Data Selecting Input Model without data, Multivariate
and Time Series Models,Model Building
verification and validation,Verification of
simulation models, Naylor and Finger Approach
for calibration and Validation of simulation
models
Self-learning Topics: Input-Output Validation:
Using Historical Input Data
VI Applications of High-Level Computer-System Simulation and 03 CO6
Simulation Memory Simulation, Simulation of
Manufacturing and Material Handling Systems
Self-learning Topics: Simulation of Computer
Networks
Text Books:
1. J. Banks, J. S. Carson, B. L. Nelson and D. M. Nicol (2001), Discrete Event System Simulation, 3 rd Ed., Prentice-Hall.
2. J. Banks, J. S. Carson, B. L. Nelson and D. M. Nicol (2001), Discrete Event System Simulation, 4th Ed., Prentice-Hall.
References Books:
1. A. M. Law and W. D. Kelton (2000), Simulation Modeling and Analysis, 4 th Ed., McGraw Hill.
2. K. S. Trivedi (2001), Probability and Statistics with Reliability, Queuing and Computer Science Applications, Eastern
Economy Edition, Prentice-Hall (India).
3. Banks C M, Sokolowski J A, Principles of Modeling and Simulation, Wiley
4. Geoffrey Gordon, System Simulation, EEE
5. Narsing Deo, System Simulation with Digital Computer; PHI
Online References:
1. https://www.udemy.com/course/discrete-event-system-simulation/
2. https://www.tutorialspoint.com/modelling_and_simulation/index.htm
Assessment:
Test

Course Code Course Theory Practical Tutorial Theory Practical Tutorial Total
Name /Oral
ITDO8014 Knowledge 03 -- -- 03 -- -- 03
Management
Examination Scheme
Subject Theory Marks
Subject Name
Avg. of 2 Sem. Work
Test1 Test 2
Tests Exam
ITDO8014 Knowledge
Management 20 20 20 80 -- -- -- 100
Course Objectives:

1 Establish a foundation of key terms and concepts, historical events and contributions, organizational benefits,
and guiding principles on which to build greater understanding of knowledge management.
2 Appreciate the role and use of knowledge for individuals, as well as organizations and institutions.
3 Increase information and understanding about knowledge transfer using low- and high technology strategies.
4 Explore the future of knowledge management and its influence on our jobs, communities, and society.
5 Explore different tools for knowledge codification and knowledge transfer.
6 Discuss impact of knowledge management on product, people and organization, etc. with qualitative and
quantitative measures.
Course Outcomes:
Bloom’s Taxonomy
1 Discuss KM, learning organizations, intellectual capital and related terminologies in L1,L2,L3
clear terms and understand the role of knowledge management in organizations.
2 Demonstrate an understanding of the history, concepts, and the antecedents of L1,L2,L3
management of knowledge and describe several successful knowledge management
systems.
3 Evaluate the impact of technology including telecommunications, networks, and L4,L5
Internet/intranet role in managing knowledge.
4 Discuss new jobs, roles and responsibilities resulting from the New or Knowledge L1,L2,L3
Economy Ponder KM’s current and future impact on individuals, organizations and
society at large.
5 Apply different tools for knowledge transfer and Business Intelligence in knowledge L1,L2,L3
sharing.
6 Analyze different modes of knowledge conversion and testing tools for knowledge L1,L2,L3,L4
codification.
Prerequisite: An introductory course in IT/ IS
DETAILED SYLLABUS:

No. Mapping
0 Prerequisite Meaning of data, information, knowledge and 02

expertise Meaning of epistemology, Types of
Knowledge -Subjective & Objective views of
knowledge, procedural Vs. declarative, tacit Vs.
explicit, general Vs. specific.
I Introduction to What is Knowledge? Data, information and 07 CO1
Knowledge knowledge, Knowledge management process, Types of
Management expertise – associational, motor skill, theoretical
Characteristics of knowledge – explicitness,
codifiability, teachability, specificity, Reservoirs of
knowledge, Meaning of Knowledge Management,
Forces Driving Organizational issues in KM, KM
Systems & their role, Relevance of KM in today’s
dynamic & complex environment, Future of
Knowledge Management
Self-Learning Topics: Study the various KM process.
II Knowledge Challenges in Building KM Systems – Conventional 06 CO2
management versus KM System Life Cycle (KMSLS) – Knowledge
system life Creation and Knowledge Architecture – Nonaka’s
cycle Model of Knowledge Creation and Transformation,
Knowledge Architecture.
Self-Learning Topics: Case study for KMSLS.
III KM Solutions KM Processes, KM Systems, Mechanisms & 06 CO5
for capture, Technologies, Knowledge Capturing Techniques:
sharing & Brain Storming – Protocol Analysis – Consensus
applications Decision Making – Repertory Grid- Concept Mapping
–Blackboarding, Nominal Group Technique, Delphi
method.
Self-Learning Topics: Study various technologies
used in KM in industry.
IV Knowledge Modes of Knowledge Conversion – Codification Tools 06 CO6
codification and Procedures – Knowledge Developer’s Skill Sets –
System Testing and Deployment – Knowledge Testing
–Approaches to Logical Testing, User Acceptance
Testing – KM System Deployment Issues – User
Training – Post implementation.
Self-Learning Topics: Study different tools for testing
for KM.
V Knowledge Transfer Methods – Role of the Internet – Knowledge 06 CO3
transfer and Transfer in e-world – KM System Tools – Neural
sharing Network – Association Rules – Classification Trees –
Data Mining and Business Intelligence – Decision
Making Architecture – Data Management –
Knowledge Management Protocols – Managing
Knowledge Workers.
Self-Learning Topics: Case study for transfer
methods in KM.
VI KM Impact Dimensions of KM Impact – People, Processes, 06 CO4
Products & Organizational Performance Factors
influencing impact – universalistic & contingency
views Assessment of KM Impact – Qualitative &
quantitative measures, Identification of appropriate
KM solutions, Competing with Business Analytics,
Caveats for managing Knowledge and Business
Intelligence, Corporate social Responsibility, Ethical
Legal and Managerial Issues: PAPA, Security and
controls.
Self-Learning Topics: Case study on KM impact.
Text Books:
1. Irma Becerra-Fernandez, Avelino Gonzalez, Rajiv Sabherwal (2004). Knowledge Management Challenges, Solutions, and
Technologies. Prentice Hall. ISBN: 0-13-109931-0.
2. Elias M. Awad, Hassan M. Ghaziri (2004). Knowledge Management. Prentice Hall. ISBN: 0-13- 034820-1
3. Donald Hislop, Knowledge Management in Organizations, Oxford 2nd Edition. Ian Watson (2002).
4. Shelda Debowski, Knowledge Management, Wiley India Edition
5. Keri E Pearlson, Carol S. Saunders, Strategic Management of Information System, Wiley India Edition
6.
References Books:
1. Madanmohan Rao (2004). Knowledge Management Tools and Techniques: Practitioners and Experts Evaluate KM
Solutions. Butterworth-Heinemann. ISBN: 0750678186.
2. Stuart Barnes (Ed.) (2002). Knowledge Management Systems Theory and Practice. Thomson Learning.
3. Kimiz Dalkir, Knowledge Management in Theory and Practice, Elsevier, Butterworth Hinemann.
4. Applying Knowledge Management: Techniques for Building Corporate Memories. Morgan Kaufmann. ISBN:
1558607609.
Online resources:
1. https://onlinecourses.nptel.ac.in/noc19_mg33/preview
2. https://www.udemy.com/course/knowledge-management/
3. https://www.coursehero.com/file/70272191/km-pdf-imppdf/
4. http://cs.unibo.it/~gaspari/www/teaching/slides_KM6.pdf
Assessment:
Test

Course Course Theory Practical Tutorial Theory Practical Tutorial Total
Code Name /Oral
ITDO8021 User 03 -- -- 03 -- -- 03
Interface
Design
Examination Scheme
Theory Marks
Course
Course Code
Name Internal assessment Term
End Practical Oral Total
Sem. Work
Avg. of
Test1 Test 2 Exam
2 Tests
ITDO8021 User
Interface 20 20 20 80 -- -- -- 100
Design
Course Objectives:

1 To stress the importance of good interface design.
2 To understand the importance of human psychology as well as social and emotional aspect in designing good
interfaces.
3 To learn the techniques of data gathering, establishing requirements, analysis and data interpretation.
4 To learn the techniques for prototyping and evaluating user experiences.
5 To understand interaction design process and evaluate design.
6 To bring out the creativity in each student – build innovative applications that are usable, effective and
efficient for intended users.
Course Outcomes:
Bloom’s Taxonomy
1 Identify and criticize bad features of interface designs. L1,L2,L3
2 Predict good features of interface designs. L1,L2,L3
3 Illustrate and analyze user needs and formulate user design specifications. L1,L2,L3
4 Interpret and evaluate the data collected during the process. L1,L2,L3
5 Evaluate designs based on theoretical frameworks and methodological approaches. L1,L2,L3,L4,L5
6 Apply better techniques to improve the user interaction design interfaces. L1,L2,L3
Prerequisite: Software Engineering.
DETAILED SYLLABUS:

Sr. Module Detailed Content Hour CO
No. s Mapping
0 Prerequisite Software Engineering concepts and any 02 NA

programming Language
Self-learning Topics: Web design languages
I Introduction to Good and Poor Design, What is Interaction 05 CO1
Interaction Design, The User Experience, The Process Of
Design Interaction Design, Interaction Design and the
User Experience, Necessity of UI/UX
Self-learning Topics: Study of Various

interactive day to day application
II Understanding Understanding the Problem Space and 05 CO2
and Conceptualizing Design, Conceptual Model,
Conceptualizin Interface Types, Cognitive aspects, Social
g Interaction Interaction and the Emerging Social Phenomena,
Cognitive Emotions and the User Experience, Expressive
aspects and and Frustrating Interfaces, Persuasive
Social, Technologies
Emotional
Interaction Self-learning Topics: Study of Various
interactive Interface Types
III Data Establishing Requirements, Five Key Issues, 08 CO3

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

VI Evaluation The Why, What, Where and When of Evaluation, 05 CO5/
Techniques and Types of Evaluation, case studies, DECIDE CO6
Framework Framework, Usability Testing, conducting
experiments, Field studies, Heuristic Evaluation
and walkthroughs, Predictive models.
Self-learning Topics: Evaluation of any GUI
with usability principles.
Text Books:
1. Interaction Design, by J. Preece, Y. Rogers and H. Sharp. ISBN 0-471-49278-7.

2. Human Computer Interaction, by Alan Dix, Janet Finlay, Gregory D Abowd, Russell Beale
3. Alan Cooper, Robert Reimann, David Cronin, “About Face3: Essentials of Interaction design”,
Wiley publication.
4. Wilbert O. Galitz, “The Essential Guide to User Interface Design”, Wiley publication.
References Books:
1. The UX Book, by Rex Hartson and Pardha S Pyla

2 .Donald A. Norman, “The design of everyday things”, Basic books.
3. Jeff Johnson, “Designing with the mind in mind”, Morgan Kaufmann Publication.
4. UI Design: Key to captivate User Understanding, by Nilakshi Jain, Dhananjay Kalbande
Online References:
1. https://onlinecourses.nptel.ac.in/noc21_ar05/preview
3. https://nptel.ac.in/noc/courses/noc19/SEM1/noc19-ar10/
5. https://www.youtube.com/watch?v=6C2Ye1makdY&list=PLW-zSkCnZ-gD5TDfs1eL5EnH2mQ0f9g6B
6. https://xd.adobe.com/ideas/process/
Assessment:
Test

Course Code Course Theory Practical Tutorial Theory Practical/ Tutorial Tota
Name Oral l
ITDO8022 Robotics 03 -- -- 03 -- -- 03
Examination Scheme
Course Course Theory Marks
Code Name Internal assessment End Term
Avg. of 2 Sem. Work
Test1 Test 2
Tests Exam
ITDO8022 Robotics 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives

1 Learn the basic concepts of Robot.
2 Learn the concepts of Kinematics of Robotics.
3 Learn the different types of Actuators and Sensors in Robot Designing.
4 Learn the concepts of Motions, Velocities and Dynamic Analysis of Force.
5 Learn the concepts of Trajectory and Motion Planning.
6 Learn the different Programming Languages to program Robot.
Course Outcomes:
Sr. Course Outcomes Cognitive
No levels of
attainment
as per
Bloom’s
Taxonomy
1 Understand different types of robot, its characteristics and applications. L1,L2
2 Analyse kinematics parameters of robotic manipulator. L1,L2,L3,L4
3 Identify actuators, sensors and control of a robot for different applications. L1,L2,L3
4 Apply the differential relationships of motion, velocities and dynamic analysis of force. L1,L2,L3
5 Apply the concept of trajectory and motion planning in robot programming. L1,L2,L3
6 Use robot programming languages and acquire skills to program robots. L1,L2,L3
Prerequisite: Mathematical concepts of Geometry, Linear Algebra, Calculus, Basic Electronics
DETAILED SYLLABUS:

No. Mapping
0 Prerequisite Homogenous Coordinate System, Matrix 02 --

Representation and its Operations, Vector Algebra:
Dot and Cross Products, Orthogonal and
Orthonormal Vectors
I Introduction and Automation and its types, definition of Robotics 04 CO1

Fundamentals of and a Robot, History of Robotics, Advantages and
Robotics Disadvantages of Robot, Robotic Manipulators,
Robot Motions, Robot Anatomy, Links and Joints,
Classification of Robots, Specification of Robot,
Applications of Robots
Self-learning Topics: Robot Coordinate System,
Economic and Social Aspects of Robotics
II Direct and Inverse Homogeneous transformation matrices, Inverse 08 CO2
Kinematics transformation matrices, Forward and inverse
kinematic equations for position and orientation,
Denavit-Hartenberg Representation of Forward
Kinematic Equations of Robots, The Inverse
Kinematic Solution of Robots, Case Studies: Three
Axes Planar Articulated Robot Arm (Mini-Drafter)
and Four Axes Adept-1 SCARA robot
Self-learning Topics: Study of Five Axes Rhino
XR- Robot Arm and Six Axes Articulated
Intelledex 660 Robot Arm
III Actuators and Characteristics of Actuating Systems, Comparison 06 CO3
Sensors of Actuating Systems, Hydraulic Devices,
Pneumatic Devices, Electric Motors,
Magnetostrictive Actuators, Sensor
Characteristics, Position Sensors, Velocity
Sensors, Acceleration Sensors, Force and Pressure
Sensors, Torque Sensors, Light and Infrared
Sensors, Touch and Tactile Sensors, Proximity
Sensors, Sniff Sensors, Vision Systems, Voice
Synthesizer
Self-learning Topics: Microprocessor Control of
Electric Motors, Microswitches, Range Finders,
Voice Recognition Devices
IV Motions, velocities Differential relationship, Jacobian, Differential 08 CO4
and dynamic motions of a frame and robot, Inverse Jacobian,
analysis of force Lagrangian mechanics, Moments of Inertia,
Dynamic equations of robots, Transformation of
forces and moment between coordinate frames
Self-learning Topics: Static Force Analysis of
Robots
V Trajectory and Trajectory planning, Joint-space trajectory 05 CO5
Motion Planning planning, Cartesian-space trajectories, Concept of
motion planning, Bug Algorithms – Bug1, Bug2,
Tangent Bug
Self-learning Topics: Case Study based on real
life application of motion planning (eg. Chess
Game, Robotic Race, etc.)
VI Introduction to Definition of Robot Program, Robot Programming 06 CO6
Robot Programming Techniques like Online programming, Lead-
through programming, Walk-through
programming, Offline programming, Task
programming, Motion Programming, Robotic
Programming Language: Overview, Requirements
for Standard Robot Language, Introduction to
Robot Languages like AL, AML, RAIL, RPL,
VAL, etc.
Self-learning Topics: Example of Robot Program
using VAL.
Text Books:
1. Robert Shilling, “Fundamentals of Robotics-Analysis and control”, PHI, 2003.

2. Saeed B. Niku, “Introduction to Robotics Analysis, Systems, Applications”,3 rd Edition, Wiley, 2019.
3. Saha, S.K., “Introduction to Robotics”, 2 nd Edition, McGraw-Hill Higher Education, New Delhi, 2014.
4. Ashitava Ghoshal, “Robotics-Fundamental Concepts and Analysis”, Oxford University Press, Sixth impression, 2010
5. Mukherjee S., “Robotics Process Automation”, 1 st Edition, Khanna Publishing House, New Delhi, 2020.
References Books:
1. John J. Craig, “Introduction to Robotics – Mechanics & Control”, 3rd Edition, Pearson Education, India, 2009
2. Mark W. Spong & M. Vidyasagar, “Robot Dynamics & Control”, 2 nd Wiley India Pvt. Ltd., 2004
3. Aaron Martinez & Enrique Fernandez, “Learning ROS for Robotics Programming”, 1 st Edition, Shroff Publishers, 2013
4. Howie Choset, Kevin M. Lynch, Seth Hutchinson, George Kantor, Wolfram Burgard, Lydia E. Kavraki and Sebastian
Thrun, “Principles of Robot Motion –Theory, Algorithms and Implementations”, Prentice-Hall of India, 2005
5. Fu, Gonzalez, Lee, “Robotics: Control, Sensing, Vision and Intelligence”, 1 st Edition, Mc Graw Hill, India.
Online References:
1. https://swayam.gov.in/nc_details/NPTEL
2. https://www.udemy.com/course/robotics-course/
3. https://www.coursera.org/courses?query=robotics
Assessment:
Test

Course Code Course Theory Practical Tutorial Theory Practical/ Tutorial Tota
Name Oral l
ITDO8023 ERP 03 -- -- 03 -- -- 03
Examination Scheme
Course Course Theory Marks
Code Name Internal assessment End Term
Avg. of 2 Sem. Work
Test1 Test 2
Tests Exam
ITDO8023 ERP 20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives

1 To learn the basic concepts of ERP.
2 To learn different technologies used in ERP.
3 To learn the concepts of ERP Manufacturing Perspective and ERP Modules.
4 To learn what are the benefits of ERP.
5 To study and understand the ERP life cycle.
6 To learn the different tools used in ERP.
Course Outcomes:
No levels of
attainment
as per
Bloom’s
Taxonomy
1 Understand the basic concepts of ERP. L1,L2
2 Identify different technologies used in ERP. L1,L2,L3
3 Understand and apply the concepts of ERP Manufacturing Perspective and ERP L1,L2
Modules.
4 Discuss the benefits of ERP. L1,L2,L3
5 Understand and implement the ERP life cycle. L1,L2
6 Apply different tools used in ERP. L1,L2,L3
Prerequisite: Basics of software.
DETAILED SYLLABUS:

No. Mapping
0 Prerequisite Basics of software. 02 --

I Introduction to Enterprise – An Overview Integrated Management 04 CO1
ERP Information, Business Modeling, Integrated Data
Model
Self-Learning Topics: Study of advantages of
ERP.
II ERP Technologies Business Processing Reengineering(BPR), Data 06 CO2
Warehousing, Data Mining, On-line Analytical
Processing(OLAP), Supply Chain Management
(SCM), Customer Relationship
Management(CRM), MIS - Management
Information System, DSS - Decision Support
System, EIS - Executive Information System
Self-Learning Topics: Study different ERP
technologies.
III ERP MRP - Material Requirement Planning, BOM - 08 CO3
Manufacturing Bill Of Material, MRP - Manufacturing Resource
Perspective and Planning, DRP – Distributed Requirement
ERP Modules Planning, PDM - Product Data Management.
Finance, Plant Maintenance, Quality Management,
Materials Management.
Self-Learning Topics: Study different ERP
modules.
IV Benefits of ERP Reduction of Lead-Time, On-time Shipment, 08 CO4
Reduction in Cycle Time, Improved Resource
Utilization, Better Customer Satisfaction,
Improved Supplier Performance, Increased
Flexibility, Reduced Quality, Costs, Improved
Information Accuracy and Design-making
Capability.
Self-Learning Topics: Study of benefits of ERP
for real time application.
V ERP Life cycle Pre-evaluation Screening, Package Evaluation, 05 CO5
Project Planning Phase, Gap Analysis,
Reengineering, Configuration, Implementation
Team Training, Testing, Going Live, End-user
Training, Post- implementation (Maintenance
mode).
Self-Learning Topics: ERP testing tools.
VI E-Commerce to E- E-Business structural transformation, Flexible 06 CO6
business Business Design, Customer Experience, Create the
new techo enterprise, New generation e-business
leaders, memo to CEO, Empower your customer,
Integrate Sales and Service, Integrated Enterprise
applications. Enterprise resource planning the E-
business Backbone Enterprise architecture,
planning, ERP usage in Real world, ERP
Implementation.
Self-Learning Topics: ERP Applications.
Text Books:
1. Enterprise Resource Planning - Alexis Leon, Tata McGraw Hill.

2. Enterprise Resource Planning – Diversified by Alexis Leon, TMH.
3. Enterprise Resource Planning - Ravi Shankar & S. Jaiswal , Galgotia.
References Books:
1. Guide to Planning ERP Application, Annetta Clewwto and Dane Franklin, McGRaw-Hill, 1997
2. The SAP R/3 Handbook, Jose Antonio, McGraw – Hill
3. E-Business Network Resource planning using SAP R/3 Baan and Peoplesoft : A Practical Roadmap For Success By Dr. Ravi
Kalakota
Online References:
1. https://www.udemy.com/
2. https://www.sap.com/
3. www.oracle.com
Assessment:
Test

Course Code Course Theory Practical Tutorial Theory Practical Tutorial Total
Name /Oral
ITDO8024 Cloud 03 -- -- 03 -- -- 03
Computing
and Services
Examination Scheme
Course Theory Marks
Course Code
Name Internal assessment End Term
Avg. of 2 Sem. Work
Test1 Test 2
Tests Exam
ITDO8024 Cloud
Computing
and 20 20 20 80 -- -- -- 100
Services
Course Objectives:

1 Understand and analyze the basics of cloud computing, service models, deployment models and architecture.
2 Define and understand the concept of virtualization and related technologies.
3 Understand the different cloud computing services and their relevance’s.
4 Describe the various services provided by Amazon Web Services cloud platform.
5 Understand and analyze the functionality of Openstack cloud platform & Severless computing.
6 Describe the aspects of Security & Privacy in cloud computing.
Course Outcomes:
No levels of
attainment
as per
Bloom’s
Taxonomy
1 Explain the basics concepts of cloud computing like service models, deployment L1,L2,L3
models and its architecture.
2 Describe and apply virtualization in cloud computing. L1,L2,L3
3 Use and Analyze different cloud computing services. L1,L2,L3,L4
4 Understand and apply various services provided by Amazon Web Services cloud L1,L2,L3
platform.
5 Discuss the functionality of Openstack cloud platform & Severless computing. L1,L2,L3
6 Recognize and examine the security and privacy concerns in cloud computing. L1,L2,L3
Prerequisite: Computer Network, Operating System.
DETAILED SYLLABUS:

No. Mapping
0 Prerequisite Concepts of Computer Network, Network 02

Security and Operating System.
I Introduction to cloud Introduction to cloud computing, need for cloud 06 CO 1
computing computing and its components, cloud & other
similar configurations, cloud types: NIST and
Cloud Cube Model, characteristics of cloud
computing, deployment models, service models,
advantages and disadvantages of Cloud
Computing.
Study the recent trends in cloud computing
architectures and related technologies.
II Virtualization Characteristics of virtualized environment, 06 CO 2
structures of virtualization, implementation levels
of virtualization, mechanisms of virtualization,
pros and cons of virtualization, virtualization vs
cloud computing, Xen and KVM architecture.
Comparison between different virtualization
platforms.
III Cloud Computing SPI Model of Cloud computing, Everything as a 04 CO 3
Services Service (XaaS): Database as a Service, Storage as
a Service, Security as a Service, Collaboration as
a Service, Monitoring as a Service, Network as a
Service, Disaster Recovery as a service, Identity
management as a Service, Analytics as a Service
and Backup as a Service.
Study of different cloud computing platforms
providing XaaS services.
IV Amazon Web Introduction to the AWS Cloud, AWS core 09 CO 4
Service Cloud services by categories.
Platform Compute Service: Introduction to EC2, EC2
Instances, EC2 Amazon Machine Images,
Instance Types, Instance Lifecycle.
Storage Service: Introducing S3, working with
Buckets, setting bucket security, S3 event and
notification, bucket properties, working with
Elastic Block Store Volumes, Object Storage Vs
Block Storage, Archives versus backups,
Introduction to Glacier.
Virtual Private Cloud: Introduction, Subnet,
Elastic Network Interfaces, Internet Gateways,
Route Tables, Security Groups.
CloudWatch:Introduction, CloudWatch Metrics,
CloudWatch Alarms.
Database as a Service: Introduction to Amazon
Relational Database Service (RDS), Database
Engines, Database Instance Classes, Backup and
Recovery, Non-relational (No-SQL) Databases,
Types of Non relational Databases, Introduction
to DynamoDB, Features, Partition and Hash
Keys.
Comparison of AWS services with other cloud
service platforms like Azure and GCP.
V Openstack Cloud Open source Cloud Platform: Introduction to 05 CO 5
platform & Severless Openstack cloud platform, Components and
Computing modes of Operations, Architecture of Openstack
cloud platform.
Mobile Cloud Computing: Definition,
architecture, benefits and challenges of mobile
cloud computing.
Serverless Computing: Introduction, Working
with Serverless environment,Basics of severless
events and functions, AWS Lambda.
To study different open source cloud computing
platforms and compare them based on different
XaaS services provided by them.
VI Cloud Security & What is security, why is it required in cloud 07 CO 6
Privacy computing, Different types of security in cloud,
attacks, and vulnerabilities, IaaS security, PaaS
security, SaaS security, trust boundary, Audit and
reporting.
Introduction to Identity and access Management
(IAM), IAM Challenges, IAM Definition, IAM
Architecture and Practice, Relevant IAM
Standards and Protocols for Cloud Services.
Privacy: What Is Privacy? What Are the Key
Privacy Concerns in the Cloud?, Legal and
Regulatory Implications: Laws and Regulations,
Governance, Risk, and Compliance (GRC).
To assess and analyze how the security and
privacy is maintained in different cloud
computing platforms.
Text Books:
1. Cloud computing Bible, Barrie Sosinsky, Wiley publication.

2. Cloud Computing Black Book, Kailash Jayaswal, Jagannath Kallalurchi, Donald J. Houde, Dr. Deven Shah, Dreamtech Press
3. Mastering Cloud Computing, Rajkumar Buyya, MGH publication
4. AWS certified solution Architect, Joe Baron et.al, Cybex publication
5. Cloud Security and Privacy, Tim Mather, Subra Kumaraswamy, and Shahed Latif, O’Reilly Publication.
6. Cloud security: A comprehensive guide to secure cloud computing by ronold L Krutz and Russell Dean Vines, Wiley publication.
Reference Books:
1. Distributed and Cloud Computing From Parallel Processing to the Internet of Things, Kai Hwang, Geoffrey C. Fox, Jack
Dongarra, Morgan Kaufmann Publication
2. Cloud Computing for Dummies, Judith Hurwitz, Wiley Publication
3. Cloud Application Architectures: Building Applications and Infrastructure in the Cloud, George Reese, O’Reilly Publication.
4. Cloud computing security: foundation and challenges, John R Vecca, CRC Press
Online References:
1. https://www.aws.amazon.com
2. https://www.nttel.ac.in
Assessment:
Test

Course Code Course Name Credits
ILO8011 Project Management 03
Objectives:
1. To familiarize the students with the use of a structured methodology/approach for each and every
unique project undertaken, including utilizing project management concepts, tools and techniques.
2. To appraise the students with the project management life cycle and make them knowledgeable about
the various phases from project initiation through closure.
Outcomes: Learner will be able to…

1. Apply selection criteria and select an appropriate project from different options.
2. Write work break down structure for a project and develop a schedule based on it.
3. Identify opportunities and threats to the project and decide an approach to deal with them
strategically.
4. Use Earned value technique and determine & predict status of the project.
5. Capture lessons learned during project phases and document them for future reference
Module Detailed Contents Hrs
Project Management Foundation:

Definition of a project, Project Vs Operations, Necessity of project management, Triple
01 constraints, Project life cycles (typical & atypical) Project phases and stage gate process. 5
Role of project manager. Negotiations and resolving conflicts. Project management in
various organization structures. PM knowledge
areas as per Project Management Institute (PMI).
Initiating Projects:
How to get a project started, Selecting project strategically, Project selection models
02 (Numeric /Scoring Models and Non-numeric models), Project portfolio process, Project 6
sponsor and creating charter; Project proposal. Effective project team, Stages of team
development & growth (forming, storming, norming &
performing), team dynamics.
Project Planning and Scheduling:
Work Breakdown structure (WBS) and linear responsibility chart, Interface
03 Co-ordination and concurrent engineering, Project cost estimation and budgeting, Top 8
down and bottoms up budgeting, Networking and Scheduling techniques. PERT, CPM,
GANTT chart. Introduction to Project Management
Information System (PMIS).
Planning Projects:
Crashing project time, Resource loading and leveling, Goldratt's critical chain, Project
04 Stakeholders and Communication plan. 6
Risk Management in projects: Risk management planning, Risk identification
and risk register. Qualitative and quantitative risk assessment, Probability and impact
matrix. Risk response strategies for positive and negative risks

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

engaging with all stakeholders of the projects.
Team management, communication and project meetings.
Monitoring and Controlling Projects:
Earned Value Management techniques for measuring value of work completed; Using
milestones for measurement; change requests and scope creep. Project audit.
Project Contracting
Project procurement management, contracting and outsourcing,
Project Leadership and Ethics:

Introduction to project leadership, ethics in projects.
Multicultural and virtual projects.
Closing the Project:
06 Customer acceptance; Reasons of project termination, Various types of project 6
terminations (Extinction, Addition, Integration, Starvation), Process of project
termination, completing a final report; doing a lessons learned analysis; acknowledging
successes and failures; Project management templates and other
resources; Managing without authority; Areas of further study.
REFERENCES:
1. Jack Meredith & Samuel Mantel, Project Management: A managerial approach, Wiley India, 7 thEd.
2. A Guide to the Project Management Body of Knowledge (PMBOK ® Guide), 5th Ed, Project
Management Institute PA, USA
3. Gido Clements, Project Management, Cengage Learning.
4. Gopalan, Project Management, , Wiley India
5. Dennis Lock, Project Management, Gower Publishing England, 9 th Ed.
Assessment:
Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.
End Semester Theory Examination:

Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question

2. All question carry 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.

ILO8012 Finance Management 03
Objectives:
1. Overview of Indian financial system, instruments and market
2. Basic concepts of value of money, returns and risks, corporate finance, working capital and its
management
3. Knowledge about sources of finance, capital structure, dividend policy

1. Understand Indian finance system and corporate finance
2. Take investment, finance as well as dividend decisions
Overview of Indian Financial System: Characteristics, Components and Functions of

Financial System.
Financial Instruments: Meaning, Characteristics and Classification of Basic Financial
Instruments — Equity Shares, Preference Shares, Bonds-Debentures, Certificates of
Deposit, and Treasury Bills. 06
01 Financial Markets: Meaning, Characteristics and Classification of Financial Markets
— Capital Market, Money Market and Foreign Currency Market Financial
Institutions: Meaning, Characteristics and Classification of Financial Institutions —
Commercial Banks, Investment-Merchant Banks and Stock
Exchanges
Concepts of Returns and Risks: Measurement of Historical Returns and Expected
Returns of a Single Security and a Two-security Portfolio; Measurement of Historical
Risk and Expected Risk of a Single Security and a Two-security Portfolio.
02 Time Value of Money: Future Value of a Lump Sum, Ordinary Annuity, and Annuity 06
Due; Present Value of a Lump Sum, Ordinary Annuity, and Annuity
Due; Continuous Compounding and Continuous Discounting.
Overview of Corporate Finance: Objectives of Corporate Finance; Functions of

Corporate Finance—Investment Decision, Financing Decision, and Dividend Decision.
Financial Ratio Analysis: Overview of Financial Statements—Balance Sheet, Profit and
03 09
Loss Account, and Cash Flow Statement; Purpose of Financial Ratio Analysis; Liquidity
Ratios; Efficiency or Activity Ratios; Profitability Ratios;
Capital Structure Ratios; Stock Market Ratios; Limitations of Ratio Analysis.
Capital Budgeting: Meaning and Importance of Capital Budgeting; Inputs for Capital
Budgeting Decisions; Investment Appraisal Criterion—Accounting Rate of Return,
04 Payback Period, Discounted Payback Period, Net Present Value(NPV), Profitability 10
Index, Internal Rate of Return (IRR), and Modified
Internal Rate of Return (MIRR)

Working Capital Management: Concepts of Meaning Working Capital;
Importance of Working Capital Management; Factors Affecting an Entity’s Working
Capital Needs; Estimation of Working Capital Requirements; Management of
Inventories; Management of Receivables; and Management of Cash and Marketable
Securities.
Sources of Finance: Long Term Sources—Equity, Debt, and Hybrids; Mezzanine
Finance; Sources of Short Term Finance—Trade Credit, Bank Finance, Commercial
Paper; Project Finance.
Capital Structure: Factors Affecting an Entity’s Capital Structure; Overview of Capital 05
05
Structure Theories and Approaches— Net Income Approach, Net Operating Income
Approach; Traditional Approach, and Modigliani-Miller Approach. Relation between
Capital Structure and Corporate Value; Concept of
Optimal Capital Structure
Dividend Policy: Meaning and Importance of Dividend Policy; Factors Affecting an
Entity’s Dividend Decision; Overview of Dividend Policy Theories and Approaches— 03
06
Gordon’s Approach, Walter’s Approach, and Modigliani-
Miller Approach
REFERENCES:
1. Fundamentals of Financial Management, 13th Edition (2015) by Eugene F. Brigham and Joel F.
Houston; Publisher: Cengage Publications, New Delhi.
2. Analysis for Financial Management, 10 th Edition (2013) by Robert C. Higgins; Publishers:
McGraw Hill Education, New Delhi.
3. Indian Financial System, 9th Edition (2015) by M. Y. Khan; Publisher: McGraw Hill
Education, New Delhi.
4. Financial Management, 11th Edition (2015) by I. M. Pandey; Publisher: S. Chand (G/L) &
Company Limited, New Delhi.
Assessment:
Internal:



ILO8013 Enterpreneurship Development and Management 03
Objectives:
1. To acquaint with entrepreneurship and management of business
2. Understand Indian environment for entrepreneurship
3. Idea of EDP, MSME

1. Understand the concept of business plan and ownerships
2. Interpret key regulations and legal aspects of entrepreneurship in India
3. Understand government policies for entrepreneurs
Overview Of Entrepreneurship: Definitions, Roles and Functions/Values of

Entrepreneurship, History of Entrepreneurship Development, Role of Entrepreneurship
in the National Economy, Functions of an Entrepreneur, Entrepreneurship and Forms of 04
01 Business Ownership
Role of Money and Capital Markets in Entrepreneurial Development:
Contribution of Government Agencies in Sourcing information for Entrepreneurship
Business Plans And Importance Of Capital To Entrepreneurship: Preliminary and

Marketing Plans, Management and Personnel, Start-up Costs and Financing as well as
Projected Financial Statements, Legal Section, Insurance, Suppliers and Risks,
02 Assumptions and Conclusion, Capital and its Importance to the Entrepreneur 09
Entrepreneurship And Business Development: Starting a New Business,
Buying an Existing Business, New Product Development, Business Growth and the
Entrepreneur Law and its Relevance to Business Operations
Women’s Entrepreneurship Development, Social entrepreneurship-role and need, EDP

05
03 cell, role of sustainability and sustainable development for SMEs,
case studies, exercises
Indian Environment for Entrepreneurship: key regulations and legal aspects ,
MSMED Act 2006 and its implications, schemes and policies of the Ministry of MSME,
role and responsibilities of various government organisations, departments, banks etc., 08
04 Role of State governments in terms of infrastructure developments and support etc.,
Public private partnerships, National Skill
development Mission, Credit Guarantee Fund, PMEGP, discussions, group exercises etc
Effective Management of Business: Issues and problems faced by micro and small
05 enterprises and effective management of M and S enterprises (risk 08
management, credit availability, technology innovation, supply chain
management, linkage with large industries), exercises, e-Marketing
Achieving Success In The Small Business: Stages of the small business life cycle, four
06 types of firm-level growth strategies, Options – harvesting or closing small business 05
Critical Success factors of small business

REFERENCES:
1. Poornima Charantimath, Entrepreneurship development- Small Business Enterprise, Pearson

2. Education Robert D Hisrich, Michael P Peters, Dean A Shapherd, Entrepreneurship, latest edition, The
McGrawHill Company
3. Dr TN Chhabra, Entrepreneurship Development, Sun India Publications, New Delhi
4. Dr CN Prasad, Small and Medium Enterprises in Global Perspective, New century Publications, New
Delhi
5. Vasant Desai, Entrepreneurial development and management, Himalaya Publishing House
6. Maddhurima Lall, Shikah Sahai, Entrepreneurship, Excel Books
7. Rashmi Bansal, STAY hungry STAY foolish, CIIE, IIM Ahmedabad
8. Law and Practice relating to Micro, Small and Medium enterprises, Taxmann Publication Ltd.
9. Kurakto, Entrepreneurship- Principles and Practices, Thomson Publication
10. Laghu Udyog Samachar
11. www.msme.gov.in
12. www.dcmesme.gov.in
13. www.msmetraining.gov.in
Assessment:
Internal:



ILO8014 Human Resource Management 03
Objectives:
1. To introduce the students with basic concepts, techniques and practices of the human resource
management.
2. To provide opportunity of learning Human resource management (HRM) processes, related with the
functions, and challenges in the emerging perspective of today’s organizations.
3. To familiarize the students about the latest developments, trends & different aspects of HRM.
4. To acquaint the student with the importance of inter-personal & inter-group behavioral skills in an
organizational setting required for future stable engineers, leaders and managers.

1. Understand the concepts, aspects, techniques and practices of the human resource management.
2. Understand the Human resource management (HRM) processes, functions, changes and challenges in
today’s emerging organizational perspective.
3. Gain knowledge about the latest developments and trends in HRM.
4. Apply the knowledge of behavioral skills learnt and integrate it with in inter personal and intergroup
environment emerging as future stable engineers and managers.
Introduction to HR
 Human Resource Management- Concept, Scope and Importance,
Interdisciplinary Approach Relationship with other Sciences,
01 Competencies of HR Manager, HRM functions. 5
 Human resource development (HRD): changing role of HRM – Human
resource Planning, Technological change, Restructuring and rightsizing,
Empowerment, TQM, Managing ethical issues.
Organizational Behavior (OB)
 Introduction to OB Origin, Nature and Scope of Organizational Behavior,
Relevance to Organizational Effectiveness and Contemporary issues
 Personality: Meaning and Determinants of Personality, Personality
development, Personality Types, Assessment of Personality Traits for
Increasing Self Awareness
 Perception: Attitude and Value, Effect of perception on Individual
02 Decision-making, Attitude and Behavior. 7
 Motivation: Theories of Motivation and their Applications for
Behavioral Change (Maslow, Herzberg, McGregor);
 Group Behavior and Group Dynamics: Work groups formal and informal
groups and stages of group development. Team Effectiveness: High performing
teams, Team Roles, cross functional and self-directed team.
 Case study
Organizational Structure &Design

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

stress.
 Leadership: Concepts and skills of leadership, Leadership and
managerial roles, Leadership styles and contemporary issues in
leadership.
 Power and Politics: Sources and uses of power; Politics at workplace,
Tactics and strategies.
Human resource Planning
 Recruitment and Selection process, Job-enrichment, Empowerment - Job-
Satisfaction, employee morale.
04  Performance Appraisal Systems: Traditional & modern methods, 5
Performance Counseling, Career Planning.
 Training & Development: Identification of Training Needs, Training
Methods
Emerging Trends in HR
 Organizational development; Business Process Re-engineering (BPR), BPR
as a tool for organizational development , managing processes &
05 transformation in HR. Organizational Change, Culture, Environment 6
 Cross Cultural Leadership and Decision Making: Cross Cultural
Communication and diversity at work, Causes of diversity, managing
diversity with special reference to handicapped, women and ageing
people, intra company cultural difference in employee motivation.
HR & MIS
Need, purpose, objective and role of information system in HR, Applications in HRD in
various industries (e.g. manufacturing R&D, Public Transport, Hospitals, Hotels and
service industries
Strategic HRM
06 Role of Strategic HRM in the modern business world, Concept of Strategy, 10
Strategic Management Process, Approaches to Strategic Decision Making;
Strategic Intent – Corporate Mission, Vision, Objectives and Goals
Labor Laws & Industrial Relations
Evolution of IR, IR issues in organizations, Overview of Labor Laws in India;
Industrial Disputes Act, Trade Unions Act, Shops and Establishments Act
REFERENCES:
1. Stephen Robbins, Organizational Behavior, 16 th Ed, 2013

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



ILO8015 Professional Ethics and Corporat Social Responsibility (CSR) 03
Objectives:
1. To understand professional ethics in business
2. To recognized corporate social responsibility

1. Understand rights and duties of business
2. Distinguish different aspects of corporate social responsibility
3. Demonstrate professional ethics
4. Understand legal aspects of corporate social responsibility
Professional Ethics and Business: The Nature of Business Ethics; Ethical

01 04
Issues in Business; Moral Responsibility and Blame; Utilitarianism: Weighing Social
Costs and Benefits; Rights and Duties of Business
Professional Ethics in the Marketplace: Perfect Competition; Monopoly
Competition; Oligopolistic Competition; Oligopolies and Public Policy Professional
02 Ethics and the Environment: Dimensions of Pollution and Resource Depletion; Ethics 08
of Pollution Control; Ethics of Conserving
Depletable Resources
Professional Ethics of Consumer Protection: Markets and Consumer Protection;
Contract View of Business Firm’s Duties to Consumers; Due Care Theory; Advertising
03 Ethics; Consumer Privacy 06
Professional Ethics of Job Discrimination: Nature of Job Discrimination;
Extent of Discrimination; Reservation of Jobs.
Introduction to Corporate Social Responsibility: Potential Business Benefits—Triple
bottom line, Human resources, Risk management, Supplier relations; Criticisms and 05
04
concerns—Nature of business; Motives; Misdirection.
Trajectory of Corporate Social Responsibility in India
Corporate Social Responsibility: Articulation of Gandhian Trusteeship Corporate
Social Responsibility and Small and Medium Enterprises (SMEs) in India, Corporate 08
05
Social Responsibility and Public-Private Partnership (PPP) in
India
Corporate Social Responsibility in Globalizing India: Corporate Social Responsibility
Voluntary Guidelines, 2009 issued by the Ministry of Corporate Affairs, Government of 08
06
India, Legal Aspects of Corporate Social
Responsibility—Companies Act, 2013.

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



ILO8016 Research Methodology 03
Objectives:
1. To understand Research and Research Process
2. To acquaint students with identifying problems for research and develop research strategies
3. To familiarize students with the techniques of data collection, analysis of data and interpretation

1. Prepare a preliminary research design for projects in their subject matter areas
2. Accurately collect, analyze and report data
3. Present complex data or situations clearly
4. Review and analyze research findings
Introduction and Basic Research Concepts

Research – Definition; Concept of Construct, Postulate, Proposition, Thesis,
Hypothesis, Law, Principle.Research methods vs Methodology
01 Need of Research in Business and Social Sciences 09
Objectives of Research
Issues and Problems in Research
Characteristics of Research:Systematic, Valid, Verifiable, Empirical and Critical
Types of Research
Basic Research
Applied Research
02 Descriptive Research 07
Analytical Research
Empirical Research
2.6 Qualitative and Quantitative Approaches
Research Design and Sample Design
03 Research Design – Meaning, Types and Significance 07
Sample Design – Meaning and Significance Essentials of a good sampling Stages in
Sample Design Sampling methods/techniques Sampling Errors
Research Methodology
4.1 Meaning of Research Methodology
4.2. Stages in Scientific Research Process:
a. Identification and Selection of Research Problem
b. Formulation of Research Problem
04 c. Review of Literature 08
d. Formulation of Hypothesis
e. Formulation of research Design
f. Sample Design
g. Data Collection
h. Data Analysis
i. Hypothesis testing and Interpretation of Data

j. Preparation of Research Report
Formulating Research Problem
05 5.1 Considerations: Relevance, Interest, Data Availability, Choice of data, Analysis of 04
data, Generalization and Interpretation of analysis
Outcome of Research
06 Preparation of the report on conclusion reached 04
Validity Testing & Ethical Issues
Suggestions and Recommendation
REFERENCES:
1. Dawson, Catherine, 2002, Practical Research Methods, New Delhi, UBS Publishers Distributors.
2. Kothari, C.R.,1985, Research Methodology-Methods and Techniques, New Delhi, Wiley Eastern
Limited.
3. Kumar, Ranjit, 2005, Research Methodology-A Step-by-Step Guide for Beginners, (2nded), Singapore,
Pearson Education
Assessment:
Internal:
class test or at least 6 assignment on complete syllabus or course project.



ILO8017 IPR and Patenting 03
Objectives:
1. To understand intellectual property rights protection system
2. To promote the knowledge of Intellectual Property Laws of India as well as International treaty
procedures
3. To get acquaintance with Patent search and patent filing procedure and applications

1. understand Intellectual Property assets
2. assist individuals and organizations in capacity building
3. work for development, promotion, protection, compliance, and enforcement of Intellectual Property and
Patenting
Module Detailed Contents Hr
Introduction to Intellectual Property Rights (IPR): Meaning of IPR, Different

category of IPR instruments - Patents, Trademarks,Copyrights, Industrial Designs, Plant
variety protection, Geographical indications,Transfer of technology etc.
01 Importance of IPR in Modern Global Economic Environment: Theories of IPR, 05
Philosophical aspects of IPR laws, Need for IPR, IPR as an instrument of
development
Enforcement of Intellectual Property Rights: Introduction, Magnitude of problem,

Factors that create and sustain counterfeiting/piracy, International agreements,
International organizations (e.g. WIPO, WTO) activein IPR enforcement
Indian Scenario of IPR:Introduction, History of IPR in India, Overview of IP laws in
02 07
India, Indian IPR, Administrative Machinery, Major international treaties signed by India,
Procedure for submitting patent and Enforcement of IPR at
national level etc.
03 Emerging Issues in IPR:Challenges for IP in digital economy, e-commerce, 05

human genome,biodiversity and traditional knowledge etc.
Basics of Patents:Definition of Patents, Conditions of patentability, Patentable and non-
patentable inventions, Types of patent applications (e.g. Patent of addition etc), Process
04 Patent and Product Patent, Precautions while patenting, Patent specification Patent 07
claims, Disclosures and non-disclosures, Patent rights
and infringement, Method of getting a patent
Patent Rules: Indian patent act, European scenario, US scenario, Australia scenario,
05 Japan scenario, Chinese scenario, Multilateral treaties where India is a 08
member (TRIPS agreement, Paris convention etc.)
Procedure for Filing a Patent (National and International): Legislation and Salient
Features, Patent Search, Drafting and Filing Patent Applications, Processing of patent,
06 07
Patent Litigation, Patent Publicationetc, Time frame and
cost, Patent Licensing, Patent Infringement

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



ILO8018 Digital Business Management 03
Objectives:
1. To familiarize with digital business concept
2. To acquaint with E-commerce
3. To give insights into E-business and its strategies
Outcomes: The learner will be able to …..

1. Identify drivers of digital business
2. Illustrate various approaches and techniques for E-business and management
3. Prepare E-business plan
Module Detailed content Hours
Introduction to Digital Business-
Introduction, Background and current status, E-market places, structures,

mechanisms, economics and impacts
1 Difference between physical economy and digital economy, 09
Drivers of digital business- Big Data & Analytics, Mobile, Cloud Computing,
Social media, BYOD, and Internet of Things(digitally intelligent
machines/services)
Opportunities and Challenges in Digital Business,
Overview of E-Commerce
E-Commerce- Meaning, Retailing in e-commerce-products and services, consumer

behavior, market research and advertisement
B2B-E-commerce-selling and buying in private e-markets, public B2B exchanges

and support services, e-supply chains, Collaborative Commerce, Intra business EC
and Corporate portals
2 06
Other E-C models and applications, innovative EC System-From E- government
and learning to C2C, mobile commerce and pervasive computing
EC Strategy and Implementation-EC strategy and global EC, Economics and

Justification of EC, Using Affiliate marketing to promote your e- commerce
business, Launching a successful online business and EC project, Legal, Ethics and
Societal impacts of EC

Digital Business Support services: ERP as e –business backbone, knowledge
Tope Apps, Information and referral system
3 06
Application Development: Building Digital business Applications and
Infrastructure
Managing E-Business-Managing Knowledge, Management skills for e-

business, Managing Risks in e –business
Security Threats to e-business -Security Overview, Electronic Commerce Threats,

4 Encryption, Cryptography, Public Key and Private Key Cryptography, Digital 06
Signatures, Digital Certificates, Security Protocols over Public Networks: HTTP,
SSL, Firewall as Security Control, Public Key Infrastructure (PKI) for Security,
Prominent Cryptographic Applications
E-Business Strategy-E-business Strategic formulation- Analysis of

Company’s Internal and external environment, Selection of strategy, E-
5 04
business strategy into Action, challenges and E-Transition (Process of
Digital Transformation)
6 Materializing e-business: From Idea to Realization-Business plan

preparation 08
Case Studies and presentations
References:
1. A textbook on E-commerce, Er Arunrajan Mishra, Dr W K Sarwade,Neha Publishers & Distributors,

2011
2. E-commerce from vision to fulfilment, Elias M. Awad, PHI-Restricted, 2002
3. Digital Business and E-Commerce Management, 6th Ed, Dave Chaffey, Pearson, August 2014
4. Introduction to E-business-Management and Strategy, Colin Combe, ELSVIER, 2006
5. Digital Business Concepts and Strategy, Eloise Coupey, 2nd Edition, Pearson
6. Trend and Challenges in Digital Business Innovation, VinocenzoMorabito, Springer
7. Digital Business Discourse Erika Darics, April 2015, Palgrave Macmillan
8. E-Governance-Challenges and Opportunities in : Proceedings in 2nd International Conference theory and
practice of Electronic Governance
9. Perspectives the Digital Enterprise –A framework for Transformation, TCS consulting journal Vol.5
10. Measuring Digital Economy-A new perspective -DOI:10.1787/9789264221796-enOECD Publishing
Assessment:
Internal:



ILO8019 Environmental Management 03
Objectives:
1. Understand and identify environmental issues relevant to India and global concerns
2. Learn concepts of ecology
3. Familiarise environment related legislations

1. Understand the concept of environmental management
2. Understand ecosystem and interdependence, food chain etc.
3. Understand and interpret environment related legislations
Introduction and Definition of Environment: Significance of Environment

Management for contemporary managers, Career opportunities. 10
01
Environmental issues relevant to India, Sustainable Development, The Energy
scenario.
Global Environmental concerns : Global Warming, Acid Rain, Ozone Depletion,
02 Hazardous Wastes, Endangered life-species, Loss of Biodiversity, Industrial/Man-made 06
disasters, Atomic/Biomedical hazards, etc.
Concepts of Ecology: Ecosystems and interdependence between living 05

03 organisms, habitats, limiting factors, carrying capacity, food chain, etc.
Scope of Environment Management, Role & functions of Government as a planning

04 and regulating agency. 10
Environment Quality Management and Corporate Environmental Responsibility
05 Total Quality Environmental Management, ISO-14000, EMS certification. 05
General overview of major legislations like Environment Protection Act, Air (P & CP)
06 Act, Water (P & CP) Act, Wildlife Protection Act, Forest Act, Factories Act, etc. 03
REFERENCES:
1. Environmental Management: Principles and Practice, C J Barrow, Routledge Publishers

London, 1999
2. A Handbook of Environmental Management Edited by Jon C. Lovett and David G. Ockwell, Edward
Elgar Publishing
3. Environmental Management,T V Ramachandra and Vijay Kulkarni, TERI Press
4. Indian Standard Environmental Management Systems — Requirements With Guidance For Use,
Bureau Of Indian Standards, February 2005
5. Environmental Management: An Indian Perspective, S N Chary and Vinod Vyasulu, Maclillan India,
2000

6. Introduction to Environmental Management, Mary K Theodore and Louise Theodore,
CRC Press
7. Environment and Ecology, Majid Hussain, 3rd Ed. Access Publishing.2015
Assessment:
Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other
is either a class test or assignment on live problems or course project.

Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in
question papers of end semester examination. In question paper weightage of each module will be
proportional to number of respective lecture hours as mention in the syllabus.

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)

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AC:

(REV- 2019 ‘C’ Scheme) from Academic Year 2019 – 20

FACULTY OF SCIENCE & TECHNOLOGY

Syllabus for Approval

1 Title of the Course Final Year Bachelor of Information Technology

After Passing Third Year Engineering as per the

3 Passing Marks 40%

5 No. of Years / Semesters 8 semesters

Dr. S. K. Ukarande Dr Anuradha Muzumdar

Dr. S. K. Ukarande Dr. Anuradha Muzumdar

Dr. S. K. Ukarande Dr Anuradha Muzumdar

Program Specific Outcome for graduate Program in Information Technology

Board of Studies in Information Technology - Team

Ad-hoc Board Information Technology

ITL801 Blockchain Lab -- 2 -- 1 1

Test1 Test2 Avg

ITC801 Blockchain and DLT 20 20 20 80 3 -- -- 100

ITL801 Blockchain Lab -- -- -- -- -- 25 25 50

Students group and load of faculty per week.

Major Project 1 and 2 :

ITDO802X Department Optional Course –6

# Institute Level Optional Course (ILO)

ILO8014 Human Resource Management

Sr.No Course Objectives

Prerequisite: Cryptography and Distributed Systems.

Sr. Module Detailed Content Hours CO

University of Mumbai, B. E. (Information Technology), Rev 2016 273

Block in a Blockchain: Structure of a Block, Block

Self-learning Topics: Blockchain Demo

II Bitcoin What is Bitcoin and the history of Bitcoin, Bitcoin 08 CO2

Bitcoin Network: Bitcoin Core node and API, Peer-to-

Self-learning Topics: Study and compare different

Smart Contracts and Solidity

Development environment and client , Basic of Solidity

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

Smart Contract Deployment: Introduction to Truffle,

Self-learning Topics: Smart contract development using

IV Permissioned Introduction to Framework, Tools and Architecture of 07 CO4

Self-learning Topics: Fundamentals of Hyperledger

Self-learning Topics: Defi, Metaverse, Types of

VI Blockchain Blockchain in IoT, AI, Cyber Security 04 CO6

 Question paper format

A total of four questions need to be answered.

University of Mumbai, B. E. (Information Technology), Rev 2016 276

Sr.No Lab Objectives

Sr.No Lab Outcomes Cognitive levels of

Prerequisite: Programming Langauges.

Sr. Module Detailed Content Hours LO

0 Prerequisite Java, Python, JavaScript 02 —

I Local Blockchain Introduction to Truffle, establishing local Blockchain 02 LO1

Documentation of the Mini Project

The Mini Project Report can be made on following lines:

1. Ethereum Smart Contract Development, Mayukh Mukhopadhyay, Packt publication.

1. Mastering Blockchain, Imran Bashir, Packt Publishing

University of Mumbai, B. E. (Information Technology), Rev 2016 279

Sr.No Lab Objectives

Sr.No Lab Outcomes Cognitive levels of

Prerequisite: Programming Langauges, DBMS.

Sr. Module Detailed Content Hours LO