Cse Btech Vi Sem Scheme Syllabus Jan 2022 1
Cse Btech Vi Sem Scheme Syllabus Jan 2022 1
Cse Btech Vi Sem Scheme Syllabus Jan 2022 1
VI-Semester
Prerequisite:None
Course Objective:
This course aims to sensitize students with the gamut of skills which facilitate them to enhance
their employability quotient.
Module 4: (06hrs.)
Coding Decoding, Sitting Arrangements, Data sequence/Calendars, Direction Sense Test, Blood
Relation.
Module 5: (06hrs.)
Syllogism, series, Analogy Classification, Clocks, Statements and Arguments, Puzzle Test, Cubes
and dice.
Course Outcome:
1. Understand the basic concepts of quantitativeability.
2. Applying basic mathematics skills to interpret data, draw conclusions, and solveproblems.
3. Developing proficiency in numericalreasoning;
4. Understand the basic concepts of logical reasoningSkills.
5. Develop the puzzle solvingskills.
List of Text / Reference Books:
1. R.S. Aggarwal, “Quantitative Aptitude”,S. Chand Publication,RevisedEdition,2018.
2. M. Tyra, “Magical Book on Quicker Maths”, BSC Publishing Co PvtLtd,2018.
3. K.Kundan,“MagicalBookSeries:DataInterpretation”,BSCPublishingCoPvtLtd,2012.
4. H.William Dettmer , “The Logical Thinking process”, Productivity Press(India)Ltd.,2001.
5. Aditi Agarwal, “An expert guide to problem solving: with practicalexamples”, Createspace
Independent Pub,2016.
6. George J Summers , “The Great Book of Puzzles &Teasers”, Jaico Publishing
House,1989.
IPS Academy, Institute of Engineering & Science
(A UGC Autonomous Institute, Affiliated to RGPV, Bhopal)
Scheme Based on AICTE Flexible Curriculum
Department of Computer Science & Engineering
Bachelor of Technology (B.Tech.) [Computer Science & Engineering]
VI-Semester
Course Objective:
To explain the different stages in the process of compilation.
Module 3: (6 hrs.)
Type checking: type system, specification of simple type checker, equivalence of expression, types,
type conversion, overloading of functions and operations, polymorphic functions. Runtime
Environment: storage organization, Storage allocation strategies, Parameter passing, dynamic storage
allocation, Symbol table, Error Detection & Recovery.
Module 4: (06 hrs.)
Intermediate code generation: Declarations, Assignment statements, Boolean expressions, Case
statements, back patching, Procedure calls Code Generation: Issues in the design of code generator,
Basic block and flow graphs, Register allocation and assignment, DAG representation of basic
blocks, peephole optimization, and generating code from DAG.
Course Outcome:
VI-Semester
Module 2: (07hrs.)
Data Link Layer: Need, Services Provided, Framing, Flow Control, Error control. Data Link Layer
Protocol: Elementary &Sliding Window protocol: 1-bit, Go-Back-N, Selective Repeat, Hybrid
ARQ. Protocol verification: Finite State Machine Models & Petri net models.ARP/RARP.
Module 3: (9 hrs.)
MAC Sub layer: MAC Addressing, Binary Exponential Back-off (BEB) Algorithm,
Distributed Random Access Schemes/Contention Schemes: for Data Services (ALOHA and
Slotted- ALOHA), for Local-Area Networks (CSMA, CSMA/CD, CSMA/CA), Collision Free
Protocols: Basic Bit Map, Binary Count Down, Adaptive Tree Walk, Performance Measuring
Metrics. IEEE Standards 802 series & theirvariant.
Module 4: (08hrs.)
Network L a y e r : Need, Services Provided , Design issues, Routing algorithms: Least Cost
Routing algorithm, Dijkstra's algorithm, Bellman-ford algorithm, Hierarchical Routing, Broadcast
Routing, Multicast Routing. IP Addresses, Header format, Packet forwarding,
Fragmentationandreassembly,ICMP,ComparativestudyofIPv4 &IPv6.
Module 5: (10hrs.)
Transport Layer: Design issues, UDP: Header Format, Per-Segment Checksum, Carrying
Uncast/Multicast Real-Time Traffic, TCP: Connection Management, Reliability of Data Transfers, TCP
Flow Control, TCP Congestion Control, TCP Header Format, TCP Timer Management. Application
Layer: WWW and HTTP, FTP, SSH, Email (SMTP, MIME, IMAP), DNS, Network Management (SNMP).
Course Outcome:
1. Describe basics of computer network, network architecture, TCP/IP protocol suite, OSI
reference models & fundamentals of physicallayer.
2. Classify data link protocol like flow control, error control, bit oriented protocol.
3. Paraphrase multi-channel access protocol, IEEE 802 standards & use Ethernet standards.
4. Explain routing & congestion algorithm. State IP protocol, addressing & subnet.
5. Distinguish various transport & application layer protocols.
List of Experiments:
VI-Semester Elective-II
Foundation of Artificial
3L: 0T: 0P (3
PEC-CS601(A) Intelligence and Machine 3credits
hrs.)
Learning
Module 2: (06hrs.)
Introduction: Basic dentitions, types of learning, hypothesis space and inductive bias, evaluation,
cross-validation. Linear regression, Decision trees, over fitting.
Course Outcome:
1. State the overview of the Artificial intelligence.
2. Explain the types of learning, linear regression and decision tree.
3. Discuss the various classification techniques and convolution neuralnetwork.
4. Explain the Ensemble learning and clustering techniques.
5. Discuss the recommendation system and Bayeslearning.
Perspectives:
1. Artificial intelligence is the simulation of human intelligence processes by machines, especially
computer systems.
2. AI is to enable computers to perform intellectual tasks as decision making, problem solving,
perception, understanding human communication (in any language, and translate among them
3. Machine Learning is an Application of AI & gives devices the ability to learn from their
experiences without doing any coding.
Recommendations:
Students pursuing a concentration in AI & ML must also take the following concentration
Requirements and electives:
VI-Semester Elective-II
Prerequisite: None
Course Objective:
Analyze and resolve security issues in an organization to secure an IT infrastructure.
Module 2: (8 hrs.)
Web jacking, Online Frauds, Software Piracy, Computer Network Intrusions, Password
Sniffing, Identity Theft, cyber terrorism, Virtual Crime, Perception of cyber criminals: hackers,
insurgents and extremist group etc. Web servers were hacking, session hijacking.
Module 5: (06hrs.)
Tools and Methods in Cybercrime: Proxy Servers and Anonymizers,PasswordCracking, Key
loggers and Spyware, virusand worms, Trojan Horses, Backdoors, DoS and DDoS Attacks ,
Buffer and Overflow, Attack on Wireless Networks, Phishing : Method of Phishing, Phishing
Techniques. Introduction to KALILinux.
Course Outcome:
1. Define and explain the concepts of cyber crime and its classification.
2. Delineate the components online frauds, intrusions, virtual crimes andhacking.
3. Knowledge of different act’s in cybersecurity
4. List the various parts of IT act related to electronicrecords.
5. Knowledge of different Cyber Securitytools.
Perspectives:
1. Computer security, cyber security or any other related terminology is the protection of
computers from any harm or damage, either physical or otherwise, by unauthorized users.
2. Cyber Security is a very broad term but is based on three fundamental concepts known as “The
CIA Triad“. It consists of Confidentiality, Integrity, and Availability.
3. Cyber Security study programmers teach you how to protect computer operating systems,
networks, and data from cyber attacks.
4. Confidentiality, honesty, and availability are three basic security principles that are essential for
information on the internet.
Recommendations:
Students pursuing a concentration in Cyber Security must also take the following concentration
Requirements and electives:
Cyber Security are more popular than ever. Living in the digital age means hackers and cyber
terrorists have endless opportunities to exploit individuals, government institutions, and even
Large companies
1. Project-I
2. Project-II
3. Project-III
4. Mobile Application Development
IPS Academy, Institute of Engineering & Science
(A UGC Autonomous Institute, Affiliated to RGPV, Bhopal)
Scheme Based on AICTE Flexible Curriculum
Department of Computer Science & Engineering
Bachelor of Technology (B.Tech.) [Computer Science & Engineering]
VI-Semester Elective-II
Natural Language
PEC-CS601(C) Processing 3L: 0T: 0P (3 hrs.) 3 credits
Course Objective:
To gain the knowledge for developing advanced technology of computer systems like speech
recognition and machine translation.
Module2: (10hrs.)
Computational Phonology: speech sound, phonetic transcription, text to speech, Pronunciation
Variations, Bayesian Method to spelling and pronunciations, Minimum Edit Distance, Weighted
Automata,N-grams.
Perspectives:
1. Natural language processing (NLP) is a branch of artificial intelligence that helps computers
understand, interpret and manipulate human language.
2. NLP (Natural Language Processing) Concerned with building computational tools that do useful
things with language.
3. NLP includes text-to-speech or speech-to-text conversion; machine translation from one language to
another; categorizing, indexing, and summarizing written documents; and identifying mood and
Opinions within text- and voice-based data.
Recommendations:
Students pursuing a concentration in Natural Language Processing must also take the following
concentration requirements and electives:
1. Computational Intelligence
2. Pattern Recognition
3. Web & Information Retrieval
4. Semantic Web & Ontology’s.
IPS Academy, Institute of Engineering & Science
(A UGC Autonomous Institute, Affiliated to RGPV, Bhopal)
Scheme Based on AICTE Flexible Curriculum
Department of Computer Science & Engineering
Bachelor of Technology (B.Tech.) [Computer Science & Engineering]
VI-Semester Elective-II
Information Storage
PEC-CS601(D) & Management 3L: 0T: 0P (3 hrs.) 3 credits
Prerequisite: None
CourseObjective:
To introduce solutions available for data storage, Core elements of a data center infrastructure,
role of each element in supporting business activities
Module 1: (06hrs.)
Introduction to Storage Technology: Data proliferation, evolution of various storage
technologies, Overview of storage infrastructure components, Information Lifecycle Management,
Datacategorization.
Module 2: (12hrs.)
Storage Systems Architecture: Intelligent disk subsystems overview, Contrast of integratedvs.
modular arrays, Component architecture of intelligent disk subsystems, Disk physical structure
components, properties, performance, and specifications, RAIDlevels & parity algorithms, hot
sparing, Front end to host storage provisioning, mapping andoperation.
Module 3: (06hrs.)
Introduction to Networked Storage: JBOD, DAS, NAS, SAN & CAS evolution and comparison.
Applications, Elements, connectivity, standards, management, security and limitations of DAS,
NAS, CAS & SAN.
Module 4: (06hrs.)
Hybrid Storage solutions; Virtualization: Memory, network, server, storage & appliances. Data
center concepts & requirements, Backup & Disaster Recovery: Principles Managing & Monitoring:
Industry management standards (SNMP, SMI-S, CIM), standard framework applications, Key
management metrics (Thresholds, availability, capacity, security, performance).
Module 5: (10hrs.)
Information storage on cloud :Concept of Cloud, Cloud Computing, storage on Cloud, Cloud
Vocabulary, Architectural Framework, Cloud benefits, Cloud computing Evolution, Applications &
services on cloud, Cloud service providers and Models, Essential characteristics of cloud
computing, Cloud Security and integration.
Course Outcome:
After the completion of this course, the students will be able to:
1.To Understand the Concept of Information Storage and Data centre Environment.
2.To understand about Data Protection.
3.To Understand Fiber ChannelSAN.
4.To describe the different backup and recovery topologies and their role in providing disaster
recovery and business continuity capabilities.
5.To Understand Cloud Computing.
Perspectives:
1. Information storage is a central pillar of information technology. A large amount of digital
information is created every moment by individuals and organizations.
2. Information needs to be stored, protected, optimized, and managed in classic, virtualized, rapidly
evolving cloud environments.
3.Information storage technology plays in the availability, performance, integration, and optimization
of the entire IT infrastructure.
4. Information storage has developed into a highly sophisticated technology, providing a variety of
solutions for storing, managing, connecting, protecting, securing, sharing, and optimizing digital
information.
Recommendations:
Data storage and management experts discuss what steps you need to take to properly manage and store
data. Students pursuing a concentration in Information Storage Management must also take the
following concentration requirements and electives:
1. Mobile Application Development
2. Block Chain Technology
3. Cloud Computing
4. Data Mining & Warehousing
IPS Academy, Institute of Engineering & Science
(A UGC Autonomous Institute, Affiliated to RGPV, Bhopal)
Scheme Based on AICTE Flexible Curriculum
Department of Computer Science & Engineering
Entrepreneurship 3L:0T:0P 3
OEC-CS601(A) (3hrs) Credits
Prerequisite(s): NA
Courseoutcomes:
1. To inculcate entrepreneurship skills to students.
2. To aware about industry structure and how to start up a company.
3. To aware about types of Enterprises.
4. To understand E-commerce practices.
5. To understand and practice Digital Marketing.
Course Objectives:
To develop conceptual understanding of the concept of Entrepreneurship
To learn the government’s policy.
To Learn about types of Enterprises
To Learn about E-commerce and its Technological Aspects
To Learn about Digital Marketing
Course Content:
Module 1 (08Hrs)
Entrepreneurship: Definition, requirements to be an entrepreneur, entrepreneur and entrepreneur,
entrepreneur and manager, growth of entrepreneurship in India, women entrepreneurship, rural and
urban entrepreneurship
Module 2 (10Hrs)
Entrepreneurial Motivation
Motivating factors, motivation theories-Maslow’s Need Hierarchy Theory, McClelland’s Acquired
Need Theory, government’s policy actions towards entrepreneurial motivation, entrepreneurship
development programme.
Module 3 (10Hrs)
Types of Enterprises and Ownership Structure: Small scale, medium scale and large scale enterprises,
role of small enterprises in economic development; proprietorship, partnership, Ltd. companies and
co-operatives: their formation, capital structure and source of finance
Module 4 (12Hrs)
E-commerce and its Technological Aspects: Overview of developments in Information Technology
and Defining E-Commerce: The scope of E commerce, Electronic Market, Electronic Data
Interchange, Internet Commerce, Benefits and limitations of E-Commerce, Produce a generic
framework for E-Commerce, Architectural framework of Electronic Commerce, Web based E
Commerce Architecture.
Module5 (10Hrs)
Introduction to Digital Marketing:. Evolution of Digital Marketing from traditional to modern era,
Role of Internet, Search Engine Advertising, Display marketing, Social Media Marketing
Text Books:
1. Koontz &O’ Donnel¸ Essentials of Management, Tata McGraw Hill,NewDelhi,2009
2. Peter F Drucker, The Practice of Management, McGraw Hill, NewYork,1960
3. Peter F.Drucker, Innovation and Development, McGraw Hill, NewYork,2000.
Reference Books:
1. Mohanty SK; Fundamental of Entrepreneurship; PHI, 2005.
2. Davis & Olson; Management Information System; TMH,1985.
Perspective:
Entrepreneurship education cultivates innovative talents, which are an important driving force for
future development. At present, innovation-driven development strategies place new demands on
entrepreneurship education
Recommendation:
Entrepreneurship is not just about start-ups. It is a problem-solving frame of mind that requires
technical expertise, a business sense, an ability to anticipate the future, and an appreciation of social
context
IPS Academy, Institute of Engineering & Science
(A UGC Autonomous Institute, Affiliated to RGPV, Bhopal)
Scheme Based on AICTE Flexible Curriculum
Department of Computer Science & Engineering
Prerequisite(s): NA
Course Objective:
Perspective:
The subject of IPR includes patents (granted to inventions that are new, no obvious, and useful, for a
period of 20 years) designs, trademarks, Copyright etc. Students possess an understanding on IPR so
that they can add more value when they join industries because they can apply these concepts in day
to day scenarios protecting the assets of both the organization and as well as their customers.
Recommendation:
Each industry should evolve its own IPR policies, management style, strategies, and so on depending
on its area of specialty. Pharmaceutical industry currently has an evolving IPR strategy requiring a
better focus and approach in the coming era.
IPS Academy, Institute of Engineering & Science
(A UGC Autonomous Institute, Affiliated to RGPV, Bhopal)
Scheme Based on AICTE Flexible Curriculum
Department of Computer Science & Engineering
3L:0T:0P
OEC-CS601(C) Operation Research 3Credits
(3hrs)
Course Objective:
1. To be familiar with all the OR Techniques and optimization methods.
2. To be familiar with various inventory control techniques.
3. To be familiar with waiting line models and Competitive strategy.
4. To clear idea of the decision making and meta-heuristic algorithm.
5. To understand project network analysis.
Course Content:
Course Outcome:
After completion of the course student will be able to:
1. Understand the concept of optimization and its application.
2. Understand the concept of various inventory control techniques used in industries.
3. Understand the concept of Queuing and Game Theory.
4. Understand the idea of the decision making and application of meta-heuristic algorithm
5. Implement project management concepts, tools and techniques in order to achieve project success
Text Books :
1. Hillier FS and Liberman GJ; Introduction to Operations Research concept and cases; TMH , 8th Ed.
2008.
2. Heera and Gupta,Operation Research, S Chand Pub.reprint with corrections ,2017
3. Sharma JK; Operations Research; Macmillan 3rd Ed. 2006.
4. Heera and Gupta ,Problems in Operations Research Principles and Solutions, S Chand Pub, 4th Ed.
2015.
Reference Books:
1. Taha H; Operations research; PHI, 10th Ed.2019.
2. Jain, pandey & shrivastava; Quantitative techniques for management, New Age publishers.2019
3. Srinivasan G; Quantitative Models In Operations and SCM; PHI Learning, 2017
4. Sen RP; Operations Research-Algorithms and Applications; PHI Learning, 2009
5. Bronson R ;Theory and problems of OR; Schaum Series; TMH, 2016.
Perspective:
Operations Research is interdisciplinary field, intermixing theories and methodologies from
mathematics, management science, computer science, operations management, economics,
engineering, decision support, soft computing and many more.
Recommendation:
Operations research and computers interact in many scientific fields of vital importance to our society.
These include, among others, transportation, economics, investment strategy, inventory control,
logistics. Computers & Operations Research (COR) provides an forum for the application of computers
and operations research techniques to problems in these and related fields.
IPS Academy, Institute of Engineering & Science
(A UGC Autonomous Institute, Affiliated to RGPV, Bhopal)
Scheme Based on AICTE Flexible Curriculum
Department of Computer Science & Engineering
Course Objective: To understand the basic concept of probability, LPP, Index number and perform
the data analysis with suitable forecasting in research and project phases.
Module-5: Index Numbers, Forecasting and Time Series Analysis (10 Hours)
Index numbers: Use of index numbers, Unweighted index numbers, Weighted index numbers, Quantity
index numbers, Volume index numbers, Time reversal test, Factor reversal test, Forecasting:
Introduction, Steps in forecasting, Methods of forecasting, Time series analysis: Components of time
series, Straight line trends, Non-linear trend.
Course Outcomes:
CO1: Apply fundamental concepts of probability to Computer Science & Engineering problem.
CO2: Apply and explain the Correlation & Regression to Computer Science & Engineering project.
CO3: Apply the various test of significance to structure engineering decision-making problems.
CO4: Apply various linear programming methods to Computer Science & Engineering.
CO5: Apply and analyze the index numbers, forecasting analysis and time series analysis on
suitable classified data.
Textbooks/References:
1. Connor, L R and Morreu, A J H, Statistics in Theory and Practice, Pitman, London, 1964.
2. Wannacott and Wannacott, Introductory Statistics, John Wiley & Sons, New York,5th Edition,
1990.
3. Willams, Ken (ed), Statistics and Urban Planning, Charles Knight & Co. Ltd, London, 1975.
4. Yamane, Taro, Statistics – An Introductory Analysis, Harper, New York, 1973.
5. D. C. Montgomery and G. C. Runjer, Applied Statistics & Probability for Engineers, Wiley
Publication, 6thEdition, 2014.
5. A. Ravindran, D. T. Phillips and James J. Solberg, Operations Research- Principles and Practice,
John Wiley & Sons, 2nd Edition 2007.
6. Hamdy A. Taha: Operations Research-An Introduction, Prentice Hall, 10th Edition, 2019.
7. F.S. Hillier, G.J. Lieberman, Introduction to Operations Research- Concepts and Cases, Tata
McGraw Hill, 10th Edition, 2017.
8. C. Chatfield, The Analysis of Time Series - An Introduction, Chapman and Hall, 7th edition 2019.
9. Peter J. Brockwell and Richard A. Davis, Introduction to Time Series and Forecasting, Springer,
3rd Edition 2016.
10. S. Ross, A first course in probability, Pearson education India, 6th edit