NOIDA INSTITUTE OF ENGINEERING AND TECHNOLOGY, GREATER NOIDA
(An Autonomous Institute)
Affiliated to
DR. A.P.J. ABDUL KALAM TECHNICAL UNIVERSITY UTTAR PRADESH, LUCKNOW
Evaluation Scheme & Syllabus
For
B.Tech in Computer Science and Engineering (Artificial Intelligence & Machine Learning) (AIML) Second Year
(Effective from the Session: 2021-22)
NOIDA INSTITUTE OF ENGINEERING & TECHNOLOGY, GREATER NOIDA
(An Autonomous Institute)
B.TECH. (AIML)
EVALUATION SCHEME
SEMESTER-III
**List of MOOCs (Coursera) Based Recommended Courses for Second Year (Semester-III) B. Tech Students
S. No.
Subject Code
Course Name
University / Industry Partner Name
No of Hours
Credits
1
AMC0027
Basic Data Descriptors, Statistical Distributions,
and Application to Business Decisions
Rice University
21
1.5
2
AMC0018
Getting Started with AI using IBM Watson
IBM
10
0.5
PLEASE NOTE:-
Internship (3-4 weeks) shall be conducted during summer break after semester-II and will be assessed
during Semester-III
*Non Credit Course
*All Non Credit Courses (a qualifying exam) are awarded zero (0) credit.
*Total and obtained marks are not added in the Grand Total.
Abbreviation Used:-
L: Lecture, T: Tutorial, P: Practical, CT: Class Test, TA: Teacher Assessment, PS: Practical Sessional, TE: Theory End
Semester Exam., PE: Practical End Semester Exam.
Sl.
No.
Subject
Codes
Subject Name
Periods
Evaluation Scheme
End
Semester
Total
Credi
t
L
T
P
CT
TA
TOTAL
PS
TE
PE
WEEKS COMPULSORY INDUCTION PROGRAM
1
AAS0303
Statistics and Probability
3
1
0
30
20
50
100
150
4
2
ACSE0306
Discrete Structures
3
0
0
30
20
50
100
150
3
3
ACSE0305
Computer Organization &
Architecture
3
0
0
30
20
50
100
150
3
4
ACSE0302
Object Oriented Techniques
using Java
3
0
0
30
20
50
100
150
3
5
ACSE0301
Data Structures
3
1
0
30
20
50
100
150
4
6
ACSAI0301
Introduction to Artificial
Intelligence
3
0
0
30
20
50
100
150
3
7
ACSE0352
Object Oriented Techniques
using Java Lab
0
0
2
25
25
50
1
8
ACSE0351
Data Structures Lab
0
0
2
25
25
50
1
9
ACSAI0351
Introduction to Artificial
Intelligence Lab
0
0
2
25
25
50
1
10
ACSE0359
Internship Assessment-I
0
0
2
50
50
1
11
ANC0301/
ANC0302
Cyber Security*/
Environmental Science *
(Non Credit)
2
0
0
30
20
50
50
100
0
12
MOOCs** (For B.Tech.
Hons. Degree)
GRAND TOTAL
1100
24
NOIDA INSTITUTE OF ENGINEERING & TECHNOLOGY, GREATER NOIDA
(An Autonomous Institute)
B. TECH (AIML)
EVALUATION SCHEME
SEMESTER-IV
Sl.
No.
Subject
Codes
Subject Name
Periods
Evaluation Scheme
End
Semester
Total
Credit
L
T
P
CT
TA
TOTAL
PS
TE
PE
1
AAS0404
Optimization and
Numerical Techniques
3
1
0
30
20
50
100
150
4
2
AASL0401
Technical
Communication
2
1
0
30
20
50
100
150
3
3
ACSE0403A
Operating Systems
3
0
0
30
20
50
100
150
3
4
ACSAI0402
Database Management
Systems
3
1
0
30
20
50
100
150
4
5
ACSML0401
Machine Learning
3
0
0
30
20
50
100
150
3
6
ACSE0404
Theory of Automata and
Formal Languages
3
0
0
30
20
50
100
150
3
7
ACSE0453A
Operating Systems Lab
0
0
2
25
25
50
1
8
ACSAI0452
Database Management
Systems Lab
0
0
2
25
25
50
1
9
ACSML0451
Machine Learning Lab
0
0
2
25
25
50
1
10
ACSE0459
Mini Project using Open
Technology
0
0
2
50
50
1
11
ANC0402 /
ANC0401
Environmental Science*/
Cyber Security*(Non
Credit)
2
0
0
30
20
50
50
100
0
12
MOOCs** (For B.Tech.
Hons. Degree)
GRAND TOTAL
1100
24
**List of MOOCs (Coursera) Based Recommended Courses for Second Year (Semester-IV) B. Tech Students
S. No.
Subject Code
Course Name
University / Industry Partner Name
No of Hours
Credits
1
AMC0017
Building AI Powered Chatbots Without
Programming
IBM
9
0.5
2
AMC0045
Machine Learning Foundations: A case Study
University of Washington
19
1.5
PLEASE NOTE:-
Internship (3-4 weeks) shall be conducted during summer break after semester-IV and will be assessed during
semester-V.
*Non Credit Course
*All Non Credit Courses (a qualifying exam) are awarded zero (0) credit.
*Total and obtained marks are not added in the Grand Total.
Abbreviation Used:-
L: Lecture, T: Tutorial, P: Practical, CT: Class Test, TA: Teacher Assessment, PS: Practical Sessional, TE: Theory End
Semester Exam., PE: Practical End Semester Exam.
NOIDA INSTITUTE OF ENGINEERING & TECHNOLOGY, GREATER NOIDA
(An Autonomous Institute)
B. TECH (AIML)
AICTE Guidelines in Model Curriculum:
A student will be eligible to get Under Graduate degree with Honours only, if he/she completes the additional
MOOCs courses such as Coursera certifications, or any other online courses recommended by the Institute
(Equivalent to 20 credits). During Complete B.Tech. Program Guidelines for credit calculations are as follows.
1. For 6 to 12 Hours =0.5 Credit
2. For 13 to18 =1 Credit
3. For 19 to 24 =1.5 Credit
4. For 25 to 30 =2 Credit
5. For 31 to 35 =2.5 Credit
6. For 36 to 41 =3 Credit
7. For 42 to 47 =3.5 Credit
8. For 48 and above =4 Credit
For registration to MOOCs Courses, the students shall follow Coursera registration details as per the assigned
login and password by the Institute these courses may be cleared during the B. Tech degree program (as per the
list provided). After successful completion of these MOOCs courses, the students shall provide their successful
completion status/certificates to the Controller of Examination (COE) of the Institute through their
coordinators/Mentors only.
The students shall be awarded Honours Degree as per following criterion.
i. If he / she secures 7.50 as above CGPA.
ii. Passed each subject of that degree program in the single attempt without any grace.
iii. Successful completion of MOOCs based 20 credits.
B. TECH. SECOND YEAR
Course Code
AAS0303
L T P
Credit
Course Title
Statistics And Probability
3 1 0
4
Course objective: The objective of this course is to familiarize the engineers with concept of Statistical
techniques, probability distribution, hypothesis testing and ANOVA and numerical aptitude. It aims to show
case the students with standard concepts and tools from B. Tech to deal with advanced level of mathematics and
applications that would be essential for their disciplines.
Pre-requisites: Knowledge of Mathematics I and II of B. Tech or equivalent
Course Contents / Syllabus
UNIT-I
Descriptive measures
8 Hours
Measures of central tendency – mean, median, mode, measures of dispersion – mean deviation, standard
deviation, quartile deviation, variance, Moment, Skewness and kurtosis, least squares principles of curve fitting,
Covariance, Correlation and Regression analysis, Correlation coefficient: Karl Pearson coefficient, rank
correlation coefficient, uni-variate and multivariate linear regression, application of regression analysis, Logistic
Regression, time series analysis- Trend analysis (Least square method).
UNIT-II
Probability and Random variable
8 Hours
Probability Definition, The Law of Addition, Multiplication and Conditional Probability, Bayes’ Theorem,
Random variables: discrete and continuous, probability mass function, density function, distribution function,
Mathematical expectation, mean, variance. Moment generating function, characteristic function, Two
dimensional random variables: probability mass function, density function,
UNIT-III
Probability distribution
8 Hours
Probability Distribution (Continuous and discrete- Normal, Exponential, Binomial, Poisson distribution),
Central Limit theorem
UNIT-IV
Test of Hypothesis & Statistical Inference
8 Hours
Sampling and population, uni-variate and bi-variate sampling, re-sampling, errors in sampling, Sampling
distributions, Hypothesis testing- p value, z test, t test (For mean), Confidence intervals, F test; Chi-square test,
ANOVA: One way ANOVA,
Statistical Inference, Parameter estimation, Least square estimation method, Maximum Likelihood estimation.
UNIT-V
Aptitude-III
8 Hours
Time & Work, Pipe & Cistern, Time, Speed & Distance, Boat & Stream, Sitting Arrangement, Clock &
Calendar.
Course outcome: After completion of this course students will be able to:
CO 1
Understand the concept of moments, skewness, kurtosis, correlation, curve fitting
and regression analysis.
K1, K3
CO 2
Understand the concept of Probability and Random variables.
K1, K3
CO 3
Remember the concept of probability to evaluate probability distributions
K3, K4
CO 4
Apply the concept of hypothesis testing and estimation of parameter.
K2
CO 5
Solve the problems of Time & Work, Pipe & Cistern, Time, Speed & Distance, Boat
&Stream, Sitting Arrangement, Clock & Calendar.
K3
Text books
(1) P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory, Universal Book Stall,
2003(Reprint)
(2) S. Ross: A First Course in Probability, 6th Ed., Pearson Education India, 2002
(3) W. Feller, An Introduction to Probability Theory and its Applications, Vol. 1, 3rd Ed., Wiley, 1968.
Reference Books
(1) B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 35th Edition, 2000.
(2) T.Veerarajan : Engineering Mathematics (for semester III), Tata McGraw-Hill, New Delhi
(3) R.K. Jain and S.R.K. Iyenger: Advance Engineering Mathematics; Narosa Publishing House, New Delhi.
(4) J.N. Kapur: Mathematical Statistics; S. Chand & Sons Company Limited, New Delhi.
(5) D.N.Elhance,V. Elhance& B.M. Aggarwal: Fundamentals of Statistics; KitabMahal Distributers, New Delhi.
Link:
Unit 1
https://youtu.be/wWenULjri40
https://youtu.be/mL9-WX7wLAo
https://youtu.be/nPsfqz9EljY
https://youtu.be/nqPS29IvnHk
https://youtu.be/aaQXMbpbNKw
https://youtu.be/wDXMYRPup0Y
https://youtu.be/m9a6rg0tNSM
https://youtu.be/Qy1YAKZDA7k
https://youtu.be/Qy1YAKZDA7k
https://youtu.be/s94k4H6AE54
https://youtu.be/lBB4stn3exM
https://youtu.be/0WejW9MiTGg
https://youtu.be/QAEZOhE13Wg
https://youtu.be/ddYNq1TxtM0
https://youtu.be/YciBHHeswBM
https://youtu.be/VCJdg7YBbAQ
https://youtu.be/VCJdg7YBbAQ
https://youtu.be/yhzJxftDgms
Unit 2
https://youtu.be/bhp4nVkqA9o
https://youtu.be/8sJ9dFj_ydg
https://youtu.be/u_x8zQvWWLk
https://youtu.be/3rYYPWN_QS0
https://youtu.be/HZGCoVF3YvM
https://youtu.be/z4e4E9igjIE
https://youtu.be/dOr0NKyD31Q
https://youtu.be/YXLVjCKVP7U
https://youtu.be/l0ecMiNUZu8
https://youtu.be/L0zWnBrjhng
https://youtu.be/cbmfYoepHPk
https://youtu.be/_DWnI-gk0ys
https://youtu.be/d_9KT2abCAY
https://youtu.be/sSUCwLvmCLg
https://youtu.be/H2Ji-Q4MfqU
https://youtu.be/TwN79BuwiMM
https://youtu.be/yXsvMlqoiK4
Unit 3
https://youtu.be/gT26Y_VJmOM
https://youtu.be/onFv73Btdno
https://youtu.be/mYFygtQrDxc
https://youtu.be/S8YrED3mf5s
https://youtu.be/z5gongqrMv8
https://youtu.be/4vsGyghhxVg
https://youtu.be/CW-3qjcw-GA
https://youtu.be/RqiqhrZE6Uk
Unit 4
https://youtu.be/L3wQw0wva3g
https://youtu.be/n9qpktdFfLU
https://youtu.be/_Qlxt0HmuOo
https://youtu.be/YSwmpAmLV2s
https://youtu.be/KLnGOL_AUgA
https://youtu.be/cQp_bJdxjWw
https://youtu.be/geB0A7CPGaQ
https://youtu.be/zmyh7nCjmsg
https://youtu.be/ohquDY3fZqk
https://youtu.be/izGZLnB-mEo
https://youtu.be/q48uKU_KWas
https://youtu.be/lZFmFuZGQTk
https://youtu.be/iin6vthyzsQ
https://youtu.be/ysjkkBspbYY
https://youtu.be/pXjaMY29k1g
https://youtu.be/pvvoK4rlzqQ
Unit 5
https://www.youtube.com/playlist?list=PLFqNfk5W2ZuzjUsRqDp1Zj3S8n9yfdmN9
https://youtu.be/x3SEYdBUGaA
https://youtu.be/B7sMHZj_p18
https://youtu.be/4HRLswVPOG8
https://youtu.be/aHEWcn_bPYc
https://youtu.be/ePQiVq8WtL8
B. TECH. SECOND YEAR
Course Code
ACSE0306
L T P
Credits
Course Title
Discrete Structures
3 0 0
3
Course objective:
The subject enhances one’s ability to develop logical thinking and ability to problem solving. The objective of
discrete structure is to enables students to formulate problems precisely, solve the problems, apply formal proofs
techniques and explain their reasoning clearly.
Pre-requisites:
1. Basic Understanding of mathematics
2. Basic knowledge algebra.
3. Basic knowledge of mathematical notations
Course Contents / Syllabus
Unit 1
Set Theory, Relation, Function
8 Hours
Set Theory: Introduction to Sets and Elements, Types of sets, Venn Diagrams, Set Operations, Multisets, Ordered
pairs. Proofs of some general Identities on sets.
Relations: Definition, Operations on relations, Pictorial Representatives of Relations, Properties of relations,
Composite Relations, Recursive definition of relation, Order of relations.
Functions: Definition, Classification of functions, Operations on functions, Growth of Functions.
Combinatorics: Introduction, basic counting Techniques, Pigeonhole Principle.
Recurrence Relation & Generating function: Recursive definition of functions, Recursive Algorithms, Method
of solving Recurrences.
Proof techniques: Mathematical Induction, Proof by Contradiction, Proof by Cases, Direct Proof.
Unit 2
Algebraic Structures
8 Hours
Algebraic Structures:Definition, Operation, Groups, Subgroups and order, Cyclic Groups, Cosets, Lagrange's
theorem, Normal Subgroups, Permutation and Symmetric Groups, Group Homomorphisms, Rings, Internal
Domains, and Fields.
Unit 3
Lattices and Boolean Algebra
8 Hours
Ordered set, Posets, Hasse Diagram of partially ordered set, Lattices: Introduction, Isomorphic Ordered set, Well
ordered set, Properties of Lattices, Bounded and Complemented Lattices, Distributive Lattices.
Boolean Algebra: Introduction, Axioms and Theorems of Boolean Algebra, Algebraic Manipulation of Boolean
Expressions, Simplification of Boolean Functions.
Unit 4
Propositional Logic
8 Hours
Propositional Logic: Introduction, Propositions and Compound Statements, Basic Logical Operations, Well-
formed formula, Truth Tables, Tautology, Satisfiability, Contradiction, Algebra of Proposition, Theory of
Inference.
Predicate Logic: First order predicate, Well-formed formula of Predicate, Quantifiers, Inference Theory of
Predicate Logic.
Unit 5
Tree and Graph
8 Hours
Trees: Definition, Binary tree, Complete and Extended Binary Trees, Binary Tree Traversal, Binary Search Tree.
Graphs: Definition and terminology, Representation of Graphs, Various types of Graphs, Connectivity,
Isomorphism and Homeomorphism of Graphs, Euler and Hamiltonian Paths, Graph Coloring
Course outcome: After completion of this course students will be able to:
CO1
Apply the basic principles of sets, relations & functions and mathematical
induction in computer science & engineering related problems.
K3
CO2
Understand the algebraic structures and its properties to solve complex
problems.
K2
CO3
Describe lattices and its types and apply Boolean algebra to simplify digital
circuit.
K2, K3
CO4
Infer the validity of statements and construct proofs using predicate logic
formulas.
K3, K5
CO5
Design and use the non-linear data structure like tree and graphs to solve real
world problems.
K3, K6
Text books:
1) B. Kolman, R.C. Busby, and S.C. Ross, Discrete Mathematical Structures, 5/e, Prentice Hall, Edition 6th, 2018.
2) Liptschutz, Seymour, “Discrete Mathematics”, McGraw Hill, Edition 3rd, 2017.
3) Trembley, J.P & R. Manohar, “Discrete Mathematical Structure with Application to Computer Science”,
McGraw Hill, Edition 1st, 2017.
4) Liu and Mohapatra, “Elements of Discrete Mathematics”, McGraw Hill.
Reference Books:
1) Deo & Narsingh, “Graph Theory With application to Engineering and Computer Science.”, PHI.
2) Krishnamurthy, V., “Combinatorics Theory & Application”, East-West Press Pvt. Ltd., New Delhi.
3) Koshy, Discrete Structures, Elsevier Pub. 2008 Kenneth H. Rosen, Discrete Mathematics and Its Applications,
6/e, Mc Graw-Hill, Edition 7
th
, 2017.
Links:
Unit 1
https://www.youtube.com/watch?v=hGtOLG3SsjI&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=9
https://www.youtube.com/watch?v=rGcTcGFx9_s&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=10
https://www.youtube.com/watch?v=oU60TuGHxe0&list=PL0862D1A947252D20&index=11
Unit 2
https://www.youtube.com/watch?v=M8nh83bFJAA&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=38
https://www.youtube.com/watch?v=CjmWE-f3vEc&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=41
Unit 3
https://www.youtube.com/watch?v=c6ARWh6lVgc&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=24
https://www.youtube.com/watch?v=QKP6sOnu1vg&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=22
Unit 4
https://www.youtube.com/watch?v=hklHg9oMkGA&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=3
https://www.youtube.com/watch?v=ASDaXWCExzo&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=4
Unit 5
https://www.youtube.com/watch?v=AtDgXyluW-Y&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=12
https://www.youtube.com/watch?v=cwbZUjfz_I0&list=PLwdnzlV3ogoVxVxCTlI45pDVM1aoYoMHf&index=13
B. TECH. SECOND YEAR
Course Code
ACSE0305
L T P
Credit
Course Title
Computer Organization & Architecture
3 0 0
3
Course objective:
To understand the types of organizations, structures and functions of computer, design of arithmetic and
logic unit and float point arithmetic. To understand the concepts of memory system, communication with
I/O devices and interfaces.
Pre-requisites:
Basic knowledge of computer system.
Logic gates and their operations.
Course Contents / Syllabus
UNIT-I
Introduction
8 Hours
Computer Organization and Architecture, Functional units of digital system and their interconnections,
buses, bus architecture, types of buses and bus arbitration and it’s types. Register, bus and memory transfer.
Process or organization, general registers organization, stack organization and addressing modes.
UNIT-II
ALU Unit
8 Hours
Arithmetic and logic unit: Lookahead carries adders. Multiplication: Signed operand multiplication,
Booth’s algorithm and array multiplier. Division and logic operations. Floating point arithmetic operation,
Arithmetic &logic unit design. IEEE Standard for Floating Point Numbers.
UNIT-III
Control Unit
8Hours
Control Unit: Instruction types, formats, instruction cycles and sub cycles (fetch and execute etc.), micro-
operations, execution of a complete instruction. Program Control, Reduced Instruction Set Computer,
Complex Instruction Set Computer, Pipelining. Hardwire and microprogrammed control, Concept of
horizontal and vertical microprogramming, Flynn's classification.
UNIT-IV
Memory Unit
8Hours
Memory: Basic concept and hierarchy, semiconductor RAM memories, 2D & 2 1/2D memory organization.
ROM memories. Cache memories: concept and design issues & performance, address mapping and
replacement Auxiliary memories: magnetic disk, magnetic tape and optical disks Virtual memory: concept
implementation, Memory Latency, Memory Bandwidth, Memory Seek Time.
UNIT-V
Input / Output
8 sHours
Peripheral
devices,
I/O
interface,
I/O
ports, Interrupts: interrupt hardware, types
of interrupts and
exceptions.
Modes of
Data
Transfer: Programmed I/O, interrupt initiated
I/O and
Direct
Memory Access,
I/O
channels
and
processors.
Serial Communication:
Synchronous &
asynchronous
communication.
Course outcome: After completion of this course students will be able to:
CO 1
Understand the basic structure and operation of a digital computer system.
K1, K2
CO 2
Analyzethe design of arithmetic & logic unit and understand the fixed point
and floating-point arithmetic operations.
K1, K4
CO 3
Implement control unit techniques and the concept of Pipelining
K3
CO 4
Understand the hierarchical memory system, cache memories and virtual
memory.
K2
CO 5
Understand different ways of communicating with I/O devices and standard
I/O interfaces.
K2
Text books:
1) M. Mano, “Computer System Architecture”, 3rd Edition, Pearson Publication, 2007.
2) John P. Hayes, Computer Architecture and Organization, Tata McGraw Hill, Third Edition, 1998.
3) William Stallings, Computer Organization and Architecture-Designing for Performance, Pearson
Education, Seventhedition,2006.
Reference Books:
1) Carl Hamacher, ZvonkoVranesic, SafwatZaky Computer Organization, McGraw-Hill, Fifth Edition,
Reprint2012
2) Ray A K, Bhurchandi K M, “Advanced Microprocessors and Peripherals”, TM.
Links:
Unit 1
https://www.youtube.com/watch?v=L9X7XXfHYdU&list=PLxCzCOWd7aiHMonh3G6QNKq53C6oN
XGrX
Unit 2
https://www.youtube.com/watch?v=WLgXUPOjKEc
Unit 3
https://www.youtube.com/watch?v=BPhWlFIU1rc
Unit 4
https://www.youtube.com/watch?v=6R7JDkpG1Wk&list=PLrjkTql3jnm8HbdMwBYIMAd3UdstWC
hFH
Unit 5
https://www.youtube.com/watch?v=nxryfWg5Hm4
B.TECH SECOND YEAR
Course Code
ACSE0302
L T P
Credit
Course Title
Object Oriented Techniques using Java
3 0 0
3
Course objective:
The objective of this course is to understand the object-oriented methodology and its techniques to design and
develop conceptual models and demonstrate the standard concepts of object-oriented techniques modularity,
I/O. and other standard language constructs. The basic objective of this course is to understand the fundamental
concepts of object-oriented programming in Java language and also implement the Multithreading concepts,
GUI based application and collection framework.
Pre-requisites:
Student must know at least the basics of how to use a computer, and should be able to start a command
line shell.
Knowledge of basic programming concepts, as covered in ‘Programming Basic” course is necessary.
Course Contents / Syllabus
UNIT-I
Introduction
8 Hours
Object Oriented Programming: Introduction and Features: Abstraction, Encapsulation, Polymorphism, and
Inheritance.
Modeling Concepts: Introduction,Class Diagram and Object Diagram.
Control Statements: Decision Making, Looping and Branching, Argument Passing Mechanism: Command
Line Argument.
UNIT-II
Basics of Java Programming
8 Hours
Class and Object: Object Reference, Constructor, Abstract Class, Interface and its uses, Defining Methods, Use
of “this” and “super” keyword, Garbage Collection and finalize () Method.
Inheritance: Introduction and Types of Inheritance in Java, Constructors in Inheritance.
Polymorphism: Introduction and Types, Overloading and Overriding.
Lambda expression: Introduction and Working with Lambda Variables.
Arrays: Introduction and its Types.
UNIT-III
Packages, Exception Handling and String Handling
8 Hours
Packages: Introduction and Types, Access Protection in Packages, Import and Execution of Packages.
Exception Handling,Assertions and Localizations: Introduction and Types, Exceptions vs. Errors, Handling
of Exception. Finally, Throws and Throw keyword, Multiple Catch Block, Nested Try and Finally Block,
Tokenizer. Assertions and Localizations Concepts and its working.
String Handling: Introduction and Types, Operations, Immutable String, Method of String class, String Buffer
and String Builder class.
UNIT-IV
Concurrency in Java and I/O Stream
8 Hours
Threads: Introduction and Types, Creating Threads, Thread Life-Cycle, Thread Priorities, Daemon Thread,
Runnable Class, Synchronizing Threads.
I/O Stream: Introduction and Types, Common I/O Stream Operations, Interaction with I/O Streams Classes.
Annotations: Introduction, Custom Annotations and Applying Annotations.
UNIT-V
GUI Programming, Generics and Collections
8 Hours
GUI Programming: Introduction and Types, Swing, AWT, Components and Containers, Layout Managers and
User-Defined Layout and Event Handling.
Generics and Collections: Introduction, Using Method References, Using Wrapper Class, Using Lists, Sets,
Maps and Queues, Working with Generics.
Course outcome: After completion of this course students will be able to:
CO1
Identify the concepts of object-oriented programming and relationships among
them needed in modeling.
K2
CO2
Demonstrate the Java programs using OOP principles and also implement the
concepts of lambda expressions.
K3
CO3
Implement packages with different protection level resolving namespace collision
and evaluate the error handling concepts for uninterrupted execution of Java
program.
K3, K5
CO4
Implement Concurrency control, I/O Streams and Annotations concepts by using
Java program.
K3
CO5
Design and develop the GUI based application, Generics and Collections in Java
programming language to solve the real-world problem.
K6
Text books:
1) Herbert Schildt,” Java - The Complete Reference”, McGraw Hill Education 12
th
edition
2) Herbert Schildt,” Java: A Beginner’s Guide”, McGraw-Hill Education 2
nd
edition
3) James Rumbaugh et. al, “Object Oriented Modeling and Design”, PHI 2
nd
Edition
Reference Books:
1) Cay S. Horstmann, “Core Java Volume I – Fundamentals”, Prentice Hall
2) Joshua Bloch,” Effective Java”, Addison Wesley
3) E Balagurusamy, “Programming with Java A Primer”, TMH, 4th edition.
Link:
Unit 1
https://www.youtube.com/watch?v=r59xYe3Vyks&list=PLS1QulWo1RIbfTjQvTdj8Y6yyq4R7g-
Al
Unit 2
https://www.youtube.com/watch?v=ZHLdVRXIuC8&list=PLS1QulWo1RIbfTjQvTdj8Y6yyq4R7g
-Al&index=18
Unit 3
https://www.youtube.com/watch?v=hBh_CC5y8-s
Unit 4
https://www.youtube.com/watch?v=qQVqfvs3p48
Unit 5
https://www.youtube.com/watch?v=2qWPpgALJyw
B. TECH. SECOND YEAR
Course Code
ACSE0301
L T P
Credits
Course Title
Data Structures
3 1 0
4
Course objective:
Learn the basic concepts of algorithm analysis, along with implementation of linear and non-linear data
structures, hashing and file structures.
Pre-requisites: Basics of C/Python programming, Identifiers, Constants, Operators, Conditional
statements, Switch-case statements, Iterative statements, Functions, Structures.
Course Contents / Syllabus
UNIT-I
Introduction to data structure, Arrays, Searching, Sorting and
Hashing
8 Hours
Data types: Primitive and non-primitive, Types of Data Structures- Linear & Non-Linear Data Structures.
Time and Space Complexity of an algorithm, Asymptotic notations (Big Oh, Big Theta and Big Omega),
Abstract Data Types (ADT).
Arrays: Definition, Single and Multidimensional Arrays, Representation of Arrays: Row Major Order, and
Column Major Order, Derivation of Index Formulae for 1-D,2-D,3-D and n-D Array Application of Arrays,
Sparse Matrices and their Representations.
Searching: Linear search, Binary search. Sorting: Bubble sort, Insertion sort, Selection sort, Radix Sort,
Merge sort, Quick sort.
Hashing: The symbol table, Hashing Functions, Collision-Resolution Techniques.
UNIT-II
Stacks and Queues
8 Hours
Stacks: Primitive Stack operations: Push & Pop, Array and Linked Implementation of Stack, Application
of stack: Infix, Prefix, Postfix Expressions and their mutual conversion, Evaluation of postfix expression.
Recursion: Principles of recursion, Tail recursion, Removal of recursion, Problem solving using iteration
and recursion with examples such as binary search, Fibonacci series, and Tower of Hanoi, Trade-offs
between iteration and recursion.
Queues: Array and linked implementation of queues, Operations on Queue: Create, Insert, Delete, Full and
Empty, Circular queues, Dequeue and Priority Queue.
UNIT-III
Linked lists
8 Hours
Advantages of linked list over array, Self-referential structure, Singly Linked List, Doubly Linked List,
Circular Linked List.
Operations on a Linked List: Insertion, Deletion, Traversal, Reversal, Searching, Polynomial
Representation and Addition of Polynomials.
Implementation of Stack and Queue using Linked lists.
UNIT-IV
Trees
8 Hours
Basic terminology used with Tree, Binary Trees, Binary Tree Representation: Array Representation and
Pointer (Linked List) Representation, Binary Search Tree, Strictly Binary Tree, Complete Binary Tree, An
Extended Binary Trees.
Tree Traversal algorithms: In-order, Pre-order and Post-order. Constructing Binary Tree from given Tree
Traversal, Operation of Insertion, Deletion, Searching & Modification of data in Binary Search tree, Binary
Heaps, Heap sort, Threaded Binary trees, Traversing Threaded Binary trees, AVL Tree, B-Tree & Binary
Heaps, Heap sort.
UNIT-V
Graphs and File Structure
8 Hours
Graphs: Terminology used with Graph, Data Structure for Graph Representations: Adjacency matrices,
Adjacency List.
Graph Traversal: Depth First Search and Breadth First Search. Connected Component, Spanning Trees,
Minimum Cost Spanning Trees: Prim’ s and Kruskal’s algorithm. Transitive Closure and Shortest Path
algorithms: Dijkstra Algorithm.
File Structure: Concepts of files, records and files, Sequential, Indexed and Random File Organization,
Indexing structure for index files, hashing for direct files, Multi-Key file organization and Access Methods.
Course outcome: After completion of this course students will be able to:
CO 1
Describe the need of data structure and algorithms in problem solving and
analyze Time space trade-off.
K2, K4
CO 2
Describe how arrays are represented in memory and how to use them for
implementation of matrix operations, searching and sorting along with their
computational efficiency.
K2, K6
CO 3
Compare and contrast the advantages and disadvantages of linked lists over
arrays and implement operations on different types of linked list.
K4, K6
CO 4
Design, implement and evaluate the real-world applications using stacks,
queues and non-linear data structures.
K5, K6
CO 5
Identify and develop the alternative implementations of data structures with
respect to its performance to solve a real-world problem.
K1, K3,
K5, K6
Text books:
1) Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, “Data Structures and Algorithms in
Python (An Indian Adaptation)”, Wiley Publication
2) Aaron M. Tenenbaum, YedidyahLangsam and Moshe J. Augenstein, “Data Structures Using C and
C++”, PHI Learning Private Limited, Delhi India
3) Horowitz and Sahani, “Fundamentals of Data Structures”, Galgotia Publications Pvt Ltd Delhi India.
4) Lipschutz, “Data Structures” Schaum’s Outline Series, Tata McGraw-hill Education (India) Pvt. Ltd.
Reference Books:
1) Thareja, “Data Structure Using C” Oxford Higher Education.
2) AK Sharma, “Data Structure Using C”, Pearson Education India.
3) P. S. Deshpandey, “C and Data structure”, Wiley Dreamtech Publication.
4) R. Kruse etal, “Data Structures and Program Design in C”, Pearson Education.
5) Berztiss, AT: Data structures, Theory and Practice, Academic Press.
6) Jean Paul Trembley and Paul G. Sorenson, “An Introduction to Data Structures with applications”,
McGraw Hill.
Link:
Unit 1
https://nptel.ac.in/courses/106/106/106106127/
https://www.youtube.com/watch?v=zWg7U0OEAoE&list=PLBF3763AF2E1C572F
https://www.youtube.com/watch?v=4OxBvBXon5w&list=PLBF3763AF2E1C572F&index=22
https://www.youtube.com/watch?v=cR4rxllyiCs&list=PLBF3763AF2E1C572F&index=23
Unit 2
https://nptel.ac.in/courses/106/106/106106127/
Unit 3
https://nptel.ac.in/courses/106/106/106106127/
https://www.youtube.com/watch?v=g1USSZVWDsY&list=PLBF3763AF2E1C572F&index=2
Unit 4
https://nptel.ac.in/courses/106/106/106106127/
https://www.youtube.com/watch?v=tORLeHHtazM&list=PLBF3763AF2E1C572F&index=6
https://www.youtube.com/watch?v=eWeqqVpgNPg&list=PLBF3763AF2E1C572F&index=7
Unit 5
https://nptel.ac.in/courses/106/106/106106127/
https://www.youtube.com/watch?v=9zpSs845wf8&list=PLBF3763AF2E1C572F&index=24
https://www.youtube.com/watch?v=hk5rQs7TQ7E&list=PLBF3763AF2E1C572F&index=25
https://www.youtube.com/watch?v=KW0UvOW0XIo&list=PLBF3763AF2E1C572F&index=5
B. TECH.SECONDYEAR
Course Code
ACSAI0301
L T P
Credits
Course Title
Introduction to Artificial Intelligence
3 0 0
3
Course objective:
Introductory knowledge of historical perspective of AI and its foundations and familiarity with principles of
AI toward problem solving, inference, perception, knowledge representation, and learning. Acquiring the
knowledge various forms of learning and computation statistics.
Pre-requisites:Basic knowledge of AI and Machine Learning Concepts.
Course Contents / Syllabus
UNIT-I
Introduction
8 Hours
Introduction to Artificial Intelligence, Historical developments of Artificial Intelligence, well defined learning
problems, Designing a Learning System, Basics of problem-solving: problem representation paradigms, state
space, satisfiability vs optimality, pattern classification problems, example domains.
UNIT-II
Search Techniques
8 Hours
Searching for solutions, Uninformed Search Strategies: DFS, BFS, Informed Search Strategies: Local search
algorithms and optimistic problems, adversarial Search, Search for games, minimax, Alpha - Beta pruning,
Heuristic Search techniques, Hill Climbing, Best-first search, Problem reduction, Constraint satisfaction,
Means Ends Analysis, Iterative deepening Heuristic Search and A*.
UNIT-III
Logic and Knowledge Representation
8 Hours
Introduction of Logic, Propositional Logic Concepts, Semantic Tableaux and Resolution in Propositional
logic, FOPL, Semantic Tableaux and Resolution in FOPL, Logic Programming in Prolog. Production systems
and rules for some AI problems: Water Jug Problem, Missionaries-Cannibals Problem, n-Queen problem,
monkey banana problem, Travelling Salesman Problem. Knowledge representation, semantic nets, partitioned
nets, parallel implementation of semantic nets. Frames, Common Sense reasoning and thematic role frames.
UNIT-IV
Expert System
8 Hours
Architecture of knowledge-Based System, Rule-based systems, Forward and Backward Chaining, Frame
Based systems. Architecture of Expert System, Forward & Backward chaining, Resolution, Probabilistic
reasoning, Utility theory, Hidden Markov Models (HMM), Bayesian Networks.
UNIT-V
Planning and Uncertainty
8 Hours
Planning with state Space Search, Conditional Planning, Continuous planning, Multi-Agent Planning, Forms
of learning, inductive learning, Reinforcement Learning, learning decision trees, Neural Net learning and
Genetic learning. Probabilistic Methods, Bayesian Theory, Dempster Shafer Theory, Bayes Network.
Evolutionary computation: Swarm Intelligence, ant colony optimization Agents, Intelligent Agents, Structure
of Intelligent Agents, Virtual Agents, Multi-agent systems.
Case Study:Health Care, E Commerce, Smart Cities.
Course outcome: After completion of this course students will be able to
CO 1
Understand fundamental understanding of the history of artificial
intelligence (AI) and its foundations
K2
CO 2
Apply principles of AI in solutions that require problem solving, inference
and perception
K3
CO 3
Explain strong familiarity with a number of important AI techniques,
including in particular intelligent search methods and solutions
K3
CO 4
Apply the concepts of knowledge & reasoning of predicate logic and
representing knowledge using rules, Probabilistic reasoning.
K3
CO 5
Assess/ Evaluate critically the techniques presented and apply them to real
world problems
K5
Text books:
1) Stuart Russell, Peter Norvig, “Artificial Intelligence – A Modern Approach”, Pearson Education.
Fourth Edition 2021
2) Elaine Rich and Kevin Knight, “Artificial Intelligence”, McGraw-Hill 3
rd
Edition 2010
Reference Books:
1) Patrick Henry Winston, “Artificial Intelligence”, Pearson Education Inc., Third edition.
2) Python Machine Learning: Learn Python in a Week and Master It. An Hands-On Introduction to
Artificial Intelligence Coding, a Project-Based Guide with Practical Exercises (7 Days Crash Course,
Book 2) 2020.
3) Nils J.Nilsson, “Artificial Intelligence - A New Synthesis", Harcourt Asia Pvt. Ltd.
4) AI in the Wild: Sustainability in the Age of Artificial Intelligence 2020.
5) Knowledge-Based Systems Techniques and Applications (4-Volume Set).
Links:
Unit 1
https://nptel.ac.in/courses/106/106/106106198/
Unit 2
https://nptel.ac.in/courses/111/107/111107137/
Unit 3
https://nptel.ac.in/courses/106/106/106106202/
Unit 4
https://nptel.ac.in/courses/106/106/106106213/
Unit 5
https://nptel.ac.in/courses/106/105/106105152/
B. TECH. SECOND YEAR
Course Code
ACSE0352
L T P
Credit
Course Title
Object Oriented Techniques using Java Lab
0 0 2
1
List of Experiments:
Sr.
No.
Name of Experiments
Q.NO.
(Codetantra)
CO
1.
Write a simple program in Java.
1
CO1
2.
Write a Java program to display default values of all primitive data types
2
CO1
3.
Write a Java program to understand Command line arguments.
3
CO1
4.
Write a Java program to understand if-then-else statement
5
CO1
5.
Write a Java Program to find the Factorial of a given number
6
CO1
6.
Write a Java Program to check whether the given number is Palindrome
or not
7
CO1
7.
Write a JAVA program to display Fibonacci series.
8
CO1
8.
Write a JAVA program to implement class mechanism. Create a class,
methods and invoke them inside main method.
-
CO2
9.
Write a Java program to illustrate the abstract class concept
24
CO2
10.
Write a Java program to Access the instance variables by using this
keyword
27
CO2
11.
Write a Java class to show the concept of static class
26
CO2
12.
Write a Java program to Access the Class members using super
Keyword
20
CO2
13.
Write a JAVA program to implement Single Inheritance.
-
CO2
14.
Write a JAVA program to implement multi-level inheritance.
19
CO2
15.
Write a Java program to implement Interface
22
CO2
16.
Write a JAVA program to implement constructor and constructor
overloading.
18
CO2
17.
Write a JAVA program implement method overloading and method
overriding.
-
CO2
18.
Write a JAVA program to implement a user defined functional interface
using lambda expressions.
-
CO2
19.
Write a program prints a multidimensional array of integers.
9
CO2
20.
Write a JAVA program to show the multiplication of two matrices using
arrays.
11
CO2
21.
Write a Java program to Search an element using Linear Search
13
CO2
22.
Write a Java program to Search an element using Binary Search
14
CO2
23.
Write a Java Program to Sort elements using Insertion Sort
15
CO2
24.
Write a Java Program to Sort elements using Selection Sort - Largest
element method
16
CO2
25.
Write a Java program to Sort elements using Bubble Sort
17
CO2
26.
Write a Java program to handle an Arithmetic Exception - divided by
zero
33
CO3
27.
Write a program to implement user defined exception in java.
-
CO3
28.
Write a Java program to illustrate Finally block
34
CO3
29.
Write a Java program to illustrate Multiple catch blocks
35
CO3
30.
Write a Java program for creation of illustrating throw
36
CO3
31.
To implement the concept of assertions in JAVA programming
language.
-
CO3
32.
To implement the concept of localization in JAVA programming
language.
-
CO3
33.
Write a Java program to print the output by appending all the capital
letters in the input in a string.
30
CO3
34.
Write a JAVA program to show the usage of string builder.
31
CO3
35.
Write a JAVA program to show the usage of string buffer.
32
CO3
36.
Write a JAVA program to implement even and odd thread by using
Thread class and Runnable interface.
-
CO4
37.
Write a JAVA program to synchronize the threads by using Synchronize
statements and Synchronize block
-
CO4
38.
To demonstrate the concept of type annotations in JAVA programming
language.
-
CO4
39.
To demonstrate the concept of user defined annotations in JAVA
programming language.
-
CO5
40.
Write a JAVA program to implement the concept of Generic and
Collection classes.
-
CO5
Lab Course Outcome: After completion of this course students will be able to
CO1
To understand how to design and implement basic data types, command line arguments
and control statements
K2
CO2
To demonstrate the Java programs using OOP principles and also implement the concepts
of lambda expressions and arrays.
K3
CO3
To demonstrate, understand and use of different exceptional handling mechanisms,
assertions, localizations and string handling.
K3
CO4
To solve the real time problems using multithreading and annotations concept.
K3
CO5
To design and develop collections and generic classes in JAVA programming language
K6
B. TECH. SECOND YEAR
Course Code
ACSE0351
L T P
Credit
Course Title
Data Structures Lab
0 0 2
1
List of Experiments:
Sr.
No.
Name of Experiment
CO
1
Program to create and display Linear Array
CO1
2
Program to insert a data item at any location in a linear Array
CO1
3
Program to delete a data item from a Linear Array
CO1
4
Program to implement multiplication of two matrices.
CO1
5
Program to create sparse matrix.
CO1
6
Program to implement linear search in an Array.
CO4
7
Program to implement binary search in an Array.
CO4
8
Program to implement bubble sort in a non-recursive way.
CO4
9
Program to implement selection sort in a non-recursive way.
CO4
10
Program to implement insertion sort in a non-recursive way.
CO4
11
Program to implement Merge sort in a non-recursive way.
CO4
12
Program to implement Merge sort in a recursive way.
CO4
13
Program to implement Quick sort in a recursive way.
CO4
14
Program to implement Queue Using array.
CO3
15
Program to implement Circular Queue Using array.
CO3
16
Program to implement Stack Operation using array.
CO3
17
Program to implement the Single Linked List
a. Insertion
b. Deletion
c. Traversal
d. Reversal
e. Searching
f. Updation
g. Sorting
h. Merging
CO2
18
Program to implement the doubly Linked List
a. Insertion
b. Deletion
c. Traversal
d. Reversal
e. Searching
f. Updation
g. Merging
CO2
19
Program to implement the circularly Single Linked List
a. Insertion
b. Deletion
c. Traversal
d. Reversal
e. Searching
f. Updation
CO2
20
Program to implement Queue Using linked list.
CO3
21
Program to implement Circular Queue Using linked list.
CO3
22
Program to implement Priority Queue Using linked list.
CO3
23
Program to implement Stack Operation using Linked list.
CO3
24
Program to convert infix to postfix expression.
CO3
25
Program to evaluate postfix expression.
CO3
26
Program to compute factorial using tail recursion
CO3
27
Program to implement Tower of Hanoi.
CO3
28
Program implementing Addition of two polynomials via Linked Lists.
CO2
29
Program to implement binary tree using linked list
a. Insertion
b. Deletion
c. Traversal
d. Searching
CO5
30
Program to implement binary search tree using linked list
a. Insertion
b. Deletion
c. Traversal
d. Searching
CO5
31
Program to implement Heap sort in a non-recursive way
CO5
32
Program to implement Radix sort.
CO4
33
Program to implement BFS algorithm.
CO5
34
Program to implement DFS algorithm.
CO5
35
Program to implement the minimum cost spanning tree.
CO5
36
Program to implement the shortest path algorithm.
CO5
Lab Course Outcome: After completion of this course students will be able to
CO 1
Implement operations on single and multi-dimensional array.
K3
CO 2
Implement various linear data structures like single Linked-list, doubly Linked-list,
Circular linked-list.
K3, K6
CO 3
Implement Stack and Queue using array and linked list.
K3
CO 4
Analyze and Implement sorting and searching algorithms.
K4, K6
CO5
Solve complex problems using non-linear data structures like tree and graph.
K6
B. TECH. SECOND YEAR
Course Code
ACSAI0351
L T P
Credit
Course Title
Introduction to Artificial Intelligence Lab
0 0 2
1
List of Experiments:
Sr. No.
Name of Experiment
CO
1
Write a python program to implement simple Chat-bot.
CO1
2
Implement Tic-Tac-Toe using A* algorithm.
CO1
3
Implement alpha-beta pruning graphically with proper example and justify the
pruning.
CO2
4
Write a python program to implement Water Jug Problem.
CO2
5
Use Heuristic Search Techniques to Implement Best first search (Best-Solution
but not always optimal) and A* algorithm (Always gives optimal solution).
CO3
6
Use Heuristic Search Techniques to Implement Hill-Climbing Algorithm.
CO5
7
Write a program to implement Hangman game using python.
CO5
8
Write a program to solve the Monkey Banana problem
CO4
9
Write a python program to implement Simple Calculator program.
CO4
10
Write a python program to POS (Parts of Speech) tagging for the give sentence
using NLTK
CO5
11
Solve 8-puzzle problem using best first search
CO5
12
Solve Robot (traversal) problem using means End Analysis.
CO5
13
Implementation of Image features Processing using OPENCV AND OPEN
VINO
CO4
14
Write a program to implement Naïve Bayes Algorithm
CO5
15
Write a Program to implement alpha-beta Pruning.
CO2
Lab Course Outcome: After completion of this course students will be able to
CO 1
Apply searching problems using various algorithms. Explain functionality of Chat-bot.
K3
CO 2
Identify problems that are amenable to solution by AI methods, and which AI methods may
be suited to solving a given problem.
K1
CO 3
Implement the program to POS (Parts of Speech) tagging for the give sentence using NLTK.
K3
CO 4
Design and carry out an empirical evaluation of different algorithms on a problem
formalization, and state the conclusions that the evaluation supports.
K3
CO5
Implement basic AI algorithms (e.g., standard search algorithms or dynamic programming).
K3
B. TECH. SECOND YEAR
Course Code
ANC0301
L T P
Credit
Course Title
Cyber Security
2 0 0
0
Course objective:
Achieve knowledge about Security of Information system and Risk factors and examine security threats and
vulnerability in various scenarios, understand concept of cryptography and encryption technique to protect the
data from cyber-attackand provide protection for software and hardware.
Pre-requisites: Basics recognition in the domain of Computer Science.
Concept of network and operating system.
Commands of programming language.
Course Contents / Syllabus
UNIT-I
Introduction
8 Hours
Introduction to Information Systems: Types of Information Systems, Development of Information Systems,
Need for Information Security, Threats to Information Systems, Information Assurance, Guidelines for Secure
Password and WI-FI Security and social media and Windows Security, Security Risk Analysis, and Risk
Management.
UNIT-II
Application Layer Security
8 Hours
Data Security Considerations-Backups, Archival Storage and Disposal of Data,Security Technology-Firewall,
Intrusion Detection, Access Control, Security Threats -Viruses, Worms, Trojan
Horse,Bombs,Trapdoors,Spoofs, E-mail Viruses, Macro Viruses, Malicious Software,Network and Denial of
Services Attack, Security,Threats to E-Commerce: Electronic Payment System, e- Cash, Issues with
Credit/Debit Cards.
UNIT-III
Secure System Development
8 Hours
Application Development Security, Architecture & Design,Security Issues in Hardware: Data Storage and
Downloadable Devices, Mobile Protection,Security Threats involving in social media, Physical Security of IT
Assets, Access Control, CCTV and Intrusion Detection Systems, Backup Security Measures.
UNIT-IV
Cryptography And Network Security
8 Hours
Public key cryptography: RSA Public Key Crypto with implementation in Python,Digital Signature Hash
Functions,Public Key Distribution.
Symmetric key cryptography: DES (Data Encryption Standard), AES (Advanced Encryption Standard), Secure
hash algorithm(SHA-1).
Real World Protocols: Basic Terminologies, VPN, Email Security Certificates, Transport Layer Security, TLS,
IP security, DNS Security.
UNIT-V
Security Policy
8 Hours
Policy design Task, WWW Policies, Email based Policies, Policy Revaluation Process-Corporate Policies-
Sample Security Policies,Publishing and Notification Requirement of the updated and new Policies.
Resent trends in security.
Course outcome: At the end of course, the student will be able to
CO 1
Analyze the cyber security needs of an organization.
K4
CO 2
Identify and examine software vulnerabilities and security
solutions.
K1,K3
CO 3
Comprehend IT Assets security (hardware and Software)
and performance indicators
K2
CO 4
Measure the performance and encoding strategies of
security systems.
K3, K5
CO 5
Understand and apply cyber security methods and policies
to enhance current scenario security.
K2, K3
Text books:
1) Charles P. Pfleeger, Shari LawerancePfleeger, “Analysing Computer Security”, Pearson Education India
2) V.K.Pachghare, “Cryptography and information Security”, PHI Learning Private Limited, Delhi India
3) Sarika Gupta & Gaurav Gupta, Information Security and Cyber Laws, Khanna Publishing House
4) Michael E.Whitman and Herbert J Mattord "Principle of Information Security" Cengage
Reference Books:
1) Schou, Shoemaker, “Information Assurance for the Enterprise”, Tata McGraw Hill.
2) CHANDER, HARISH,” Cyber Laws and It Protection”, PHI Learning Private Limited,Delhi
3) V.K. Jain, Cryptography and Network Security, Khanna Publishing House, Delhi
4) William Stallings, Network Security Essentials: Applications and Standards, Prentice Hall, 4th edition, 2010
E-books& E-Contents:
1) https://prutor.ai/welcome/
2) https://crypto.stanford.edu/cs155old/cs155-spring11/lectures/03-ctrl-hijack.pdf
3) https://cybermap.kaspersky.com/stats
4) https://www.fireeye.com/cyber-map/threat-map.html
Reference Links:
1) https://crypto.stanford.edu/cs155old/cs155-spring11/lectures/03-ctrl-hijack.pdf
2) https://cs155.stanford.edu/lectures/03-isolation.pdf
3) http://uru.ac.in/uruonlinelibrary/Cyber_Security/Cryptography_and_Network_Security.pdf
NPTEL/ Youtube/ Faculty Video Link:
1) https://www.youtube.com/watch?v=vv1ODDhXW8Q
2) https://www.youtube.com/watch?v=fQ3ESFfvchg&list=PLUtfVcb-iqn834VGI9faVXGIGSDXZMGp8
3) https://www.youtube.com/watch?v=iTVyKbDCJrA&list=PLgMDNELGJ1CbdGLyn7OrVAP-IKg-0q2U2
4) https://www.youtube.com/watch?v=1plMO7ChXMU&list=PLJ5C_6qdAvBFAuGoLC2wFGruY_E2gYtev
5) https://www.youtube.com/watch?v=_9QayISruzo
B. TECH. SECOND YEAR
Course Code
ANC0302
L T P
Credits
Course Title
Environmental Science
2 0 0
0
Course objective:
1
To help the students in realizing the inter-relationship between man and environment. and
help the students in acquiring basic knowledge about environment.
2
To develop the sense of awareness among the students about environment and its various problems.
3
To create positive attitude about environment among the student.
4
To develop proper skill required for the fulfilment of the aims of environmental education and educational
evaluations
5
To develop the capability of using skills to fulfil the required aims, to realise and solve environmental problems
through social, political, cultural and educational processes
Pre-requisites: Basic knowledge of nature.
Course Contents / Syllabus
UNIT-I
Basic Principle of Ecology
8 Hours
Definition, Scope and basic principles of ecology and environment. Ecosystem: Basic concepts, components of
ecosystem. Food chains and food webs. Ecological pyramids, Energy flow in ecological systems, Characteristics of
different ecosystems. Biogeochemical Cycles: Importance, gaseous and sedimentary cycles. Carbon, Nitrogen,
Phosphorus and Sulphur Cycles.
Basic concepts of sustainable development, SDGs, Ecosystem services, UN Decade for Ecorestoration.
UNIT-II
Natural Resources and Associated Problems
8 Hours
Natural resources and associated problems. Forest resources: Use and over-exploitation, deforestation. Timber
extraction, mining, dams and their effects on forest and tribal people. Mineral resources: Use and exploitation,
environmental effects of extracting and using mineral resources. Food resources: World food problems, changes caused
by agriculture and over-grazing, effects of modern agriculture, fertilizer-pesticide problems, water logging, salinity.
Land resources: Land as a resource, land degradation, man induced landslides. Equitable use of resources for sustainable
lifestyles.
Non-Renewable Energy Resources: Fossil fuels and their reserves, Nuclear energy, types, uses and effects, Renewable
Energy Resources: hydropower, Solar energy, geothermal, tidal and wind energy, Biomass energy, biogas and its
advantages.
UNIT-III
Biodiversity Succession and Non-Renewable Energy Resources
8 Hours
Biodiversity and their importance, Threats to biodiversity, major causes, extinction’s, vulnerability of species to
extinction, IUCN threat categories, Red data book.
Strategies for biodiversity conservation, principles of biodiversity conservation in-situ and ex-situ conservation
strategies Mega diversity zones and Hot spots, concepts, distribution and importance.
Succession: Concepts of succession, Types of Succession. Trends in succession. Climax and stability.
UNIT-IV
Pollution and Solid Waste Management
8 Hours
Air pollution: sources of air pollution, Primary and secondary air pollutants. Origin and effects of SOX, NOX, Cox,
CFC, Hydrocarbon, control of air pollution. Water pollution: sources and types of water pollution, Effects of water
pollution, Eutrophication, Soil pollution: Causes of soil pollution, Effects of soil pollution, Major sources of and effects
of noise pollution on health, Radioactive and thermal pollution sources and their effects on surrounding environment.
Solid waste disposal and its effects on surrounding environment, Climate change, global warming, acid rain, ozone layer
depletion.
UNIT-V
Role of Community and Environmental Protection Acts
8 Hours
Role of community, women and NGOs in environmental protection, Bioindicators and their role, Natural hazards,
Chemical accidents and disasters risk management, Environmental Impact Assessment (EIA), Salient features of
following Acts: a. Environmental Protection Act, 1986, Wildlife (Protection) Act, 1972.b. Water (Prevention and control
of pollution) Act, 1974.c. Air (Prevention and control of pollution) Act, 1981. Forest (Conservation) Act, 1980.d.
Wetlands (Conservation and Management) Rules, 2017; e. Chemical safety and Disaster Management law. F. District
Environmental Action Plan. Climate action plans.
Course outcome: After completion of this course students will be able to
CO 1
Understand the basic principles of ecology and environment. Ecosystem: Basic concepts,
components of ecosystem., food chains and food webs. Ecological pyramids
K2
CO 2
Understand the different types of natural recourses like food, forest, minerals and energy and their
conservation
K2
CO 3
Understand the importance of biodiversity, Threats of biodiversity and different methods of
biodiversity conservation.
K2
CO 4
Understand the different types of pollution, pollutants, their sources, effects and their control
methods
K3
CO 5
Understand the basic concepts of sustainable development, Environmental Impact Assessment
(EIA) and different acts related to environment
K3
Text books:
1. Brady, N.C. 1990. The nature and properties of Soils, Tenth Edition. Mac Millan Publishing Co., New York.
2. Botkin, D.B and Kodler E.A., 2000, Environmental Studies: The earth as a living planet. John Wiley and Sons Inc.
3. Rao M.N. and H.V.N. Rao, 1989: Air Pollution, Tata McGraw Hill Publishing Co. Ltd., New Delhi
4. Singh J.S., Singh S.P. and Gupta S.R., 2006, Ecology Environment and Resource Conservation, Anamaya Publishers,
New Delhi.
5.Environmental Studies -Benny Joseph-Tata McgrawHill-2005
6. Environmental Studies- Dr. D.L. Manjunath, Pearson Education-2006.
7. Environmental studies- R, Rajagopalan -Oxford Pubtiotion2005.
Reference Books:
1.Sodhi G.S. 2005, Fundamentals of Environmental Chemistry: Narosa Publishing House, New Delhi.
2.Dash, M.C. (1994), Fundamentals of Ecology, Tata Mc Graw Hill, New Delhi.
3. Sharma P. D. (1996). Environmental Biology, Rastogi Publications, Meerut.
4. Verma P.S. and V.K. Agarwal. (1985). Principles of Ecology. S. Chand and Company (Pub.), New Delhi.
5.Principles of Environmental Sciences and Engineering -P. Venugoplan Rao, Prenitice Hall of India.
6. Environmental Science and Engineering Meenakshi, Prentice Hall India.
NPTEL/ Youtube/ Faculty Video Link:
Unit 1
https://www.youtube.com/watch?v=T21OO0sBBfc,
https://www.youtube.com/watch?v=qt8AMjKKPDohttps://www.youtube.com/watch?v=yAK-
m91Nxrshttps://www.youtube.com/watch?v=ha_O-1uOWkk, https://www.youtube.com/watch?v=brF0RWJyx9w
Unit 2
https://www.youtube.com/watch?v=mOwyPENHhbc,https://www.youtube.com/watch?v=yqev1G2iy20,
https://www.youtube.com/watch?v=_74S3z3IO_I, https://www.youtube.com/watch?v=jXVw6M6m2g0
Unit 3
https://www.youtube.com/watch?v=GK_vRtHJZu4,https://www.youtube.com/watch?v=b6Ua_zWDH6U,
https://www.youtube.com/watch?v=7tgNamjTRkk,https://www.youtube.com/watch?v=ErATB1aMiSU,
https://www.khanacademy.org/science/high-school-biology/hs-ecology/hs-human-impact-on-
ecosystems/v/conservation-and-the-race-to-save-biodiversity
Unit 4
https://www.youtube.com/watch?v=7qkaz8ChelI,https://www.youtube.com/watch?v=NuQE5fKmfME,
https://www.youtube.com/watch?v=9CpAjOVLHII,https://www.youtube.com/watch?v=yEci6iDkXYw,
https://www.youtube.com/watch?v=yEci6iDkXYw
Unit 5
https://www.youtube.com/watch?v=ad9KhgGw5iA,https://www.youtube.com/watch?v=nW5g83NSH9M,
https://www.youtube.com/watch?v=xqSZL4Ka8xo,https://www.youtube.com/watch?v=WAI-hPRoBqs,
https://www.youtube.com/watch?v=o-WpeyGlV9Y, https://www.youtube.com/watch?v=EDmtawhADnY
B. TECH. SECOND YEAR
Course Code
AAS0404
L T P
Credit
Course Title
Optimization and Numerical Techniques
3 1 0
4
Course objective: The objective of this course is to familiarize the engineers with concept of Linear
Programming Problem (LPP), Integer Programming Problems, Constraint programming, various numerical
techniques for mathematical task such as roots, integration, differential equations and numerical aptitude. It
aims to show case the students with standard concepts and tools from B. Tech to deal with advanced level of
mathematics and applications that would be essential for their disciplines.
Pre-requisites: Knowledge of Mathematics I and II of B. Tech or equivalent.
Course Contents / Syllabus
UNIT-I
Linear Programming
8 Hours
Introduction, Mathematical formulation of LP Models, Graphical Method, Description of simplex method,
Big-M method, Two phase method, Alternative optimum solutions, unbounded solutions, Degeneracy,
Duality in LPP.
UNIT-II
Integer Programming
8 Hours
Introduction, Importance of Integer Programming Problems, Gomory’s Cutting Plane method, Branch-and-
Bound Method, Cargo Loading for Knapsack problem, Applications of Integer Programming.
UNIT-III
Non-linear programming
8 Hours
Basic facts of maxima, minima & convex optimization, Convex sets and convex functions, Continuity and
differentiable properties of convex functions, Constrained Optimization- Local and Global Solution
Introduction, Elements of Constraint Programming, Lagrange multiplier method, Kuhn Tucker Condition.
UNIT-IV
Numerical Techniques
8 Hours
Errors analysis, Zeroes of transcendental and polynomial equations using Bisection method, Regula-falsi
method and Newton-Raphson method, Interpolation: Finite differences, Newton’s forward and backward
interpolation, Lagrange’s and Newton’s divided difference formula for unequal intervals.
Solution of system of linear equations, Crout’s method, Gauss- Seidel method. Numerical integration,
Trapezoidal rule, Simpson’s one third and three-eight rules, Solution of first order ordinary differential
equations by fourth-order Runge- Kutta methods.
UNIT-V
Aptitude-IV
8 Hours
Number System, Permutation & Combination, Probability, Function, Data Interpretation, Syllogism.
Course outcome: After completion of this course students will be able to
CO 1
Understand the concepts to formulate and to solve a Linear Programming Problem.
K1, K3
CO 2
Understand the concepts of Integer Programming Problem.
K1, K3
CO 4
Apply the concept of numerical techniques to evaluate the zeroes of the
Equation, concept of interpolation and numerical methods for various mathematical
K3
operations and tasks, such as integration, the solution of linear system of equations and the
solution of differential equation.
CO 5
Solve the problems of Number System, Permutation & Combination, Probability, Function,
Data Interpretation, Syllogism.
K3
Text books:
(1) Sharma J K - Operations Research (Pearson, 3rd Edition.
(2) Rao S.S,”Optimization – Theory and applications”, Wiley Easter Ltd., 1979.
(3) Introduction to Linear Optimization by Dimitris Bertsimas & John N. Tsitsiklis, Athena Scientific 1997.
(4) TahaHamdy - Operations Research - An Introduction (Prentice-Hall, 9th edition).
(5) B. S. Grewal, Higher Engineering Mathematics, Khanna Publisher, 2005.
Reference Books:
(1) An introduction to Optimization by Edwin P K Chong, Stainslaw Zak.
(2) Hillier F S and Lieberman G J, Operations Research, Holden Day Inc., San Francisco.
(3) David G.Luerbeggan, “Introduction to Linear and Non Linear Programming”, Addison Wesley Publishing
Co. 1973.
(4)Cordan C.C. Beveridge and Robert S. Schedther, “Optimization, Theory and Practice” McGraw Hill
Co.1970.
Link:
Unit 1
https://youtu.be/a2QgdDk4Xjw
https://youtu.be/XEA1pOtyrfo
https://youtu.be/qxls3cYg8to
https://youtu.be/DUFcNysR-w8
https://youtu.be/OUduOnhO94k
https://youtu.be/_uRKG9tkrew
https://youtu.be/7w30ueP5ayI
https://youtu.be/gmDwUCvOJQ8
Unit 2
https://youtu.be/gxLQ7Q26SkE
https://youtu.be/PkFKuoJQrN4
https://youtu.be/-cBkrzNdQn4
https://youtu.be/-Cg-aL1D8CM
https://youtu.be/-cLsEHP0qt0
Unit 3
https://youtu.be/jGwA4hknYp4
https://youtu.be/ejol5TMpYJc
https://youtu.be/tJfizPGPo34
https://youtu.be/nZ40jnChzbs
https://youtu.be/nZ40jnChzbs
https://youtu.be/PlpJShHvNfQ
Unit 4
https://youtu.be/QH2WL92bzLs
https://youtu.be/DGmNbs5Cywo
https://youtu.be/FliKUWUVrEI
https://youtu.be/7eHuQXMCOvA
https://youtu.be/ZkvQR3ajm3k
https://youtu.be/zdyUwzOm1zw
https://youtu.be/BBuV14-isyU
https://youtu.be/xPr7YFSnmiQ
https://youtu.be/ajJD0Df5CsY
https://youtu.be/iviiGB5vxLA
https://youtu.be/Ym1EUjTWMnE
Unit 5
https://youtu.be/Dsi7x-A89Mw
https://youtu.be/mrCrjeqJv6U
https://youtu.be/jZXHzpq-vmM
https://youtu.be/KSFnfUYcxoI
https://youtu.be/i72ptXTEmkk
B. TECH. SECOND YEAR
Course Code
AASL0401
L T P
Credit
Course Title
Technical Communication
2 1 0
3
Course objective:
1
To help the students develop communication and critical thinking skills necessary for
securing a job, and succeeding in the diverse and ever-changing workplace of the twenty
first century
2
To enable students to communicate effectively in English at the workplace.
Pre-requisites:
The student must have a good degree of control over simple grammatical forms and some complex
grammatical forms of English language.
The student should be able to speak English intelligibly.
Course Content / Syllabus
UNIT-I
Introduction to Technical Communication and Reading
4 Hours
Fundamentals of technical communication
Role of technical communication
Reading Comprehension - central idea, tone, and intention
Critical reading strategies
UNIT-II
Technical Writing 1
5 Hours
Characteristics of technical writing; technical vocabulary, etymology
Business letters /emails – types, format, style and language
Notices, agenda and minutes
Job application, CV and resume
UNIT-III
Technical Writing 2
5 Hours
Technical reports – types & formats
Structure of a report
Technical Proposal - structure and types
Technical/ Scientific paper writing
UNIT-IV
Public Speaking
5 Hours
Components of effective speaking (emphasis on voice dynamics)
Seminar and conference presentation
Conducting/ participating in meetings
Appearing for a job interview
Mobile etiquettes
UNIT-V
Manuscript Preparation
5 Hours
Short report writing
Copy editing and referencing
Developing writing style – Jargons, Abbreviations
Ethical writing
Course outcome: At the end of the course the students will be able to Levels.
CO 1
Comprehend the fundamental principles of technical communication with special
reference to reading.
K2
CO 2
Write various kinds of professional correspondence.
K5
CO 3
Recognise and produce different kinds of technical documents.
K2
CO 4
Apply effective speaking skills to communicate at the workplace.
K3
CO 5
Demonstrate their understanding of various ethical concerns in written
communication.
K3
Textbook:
1. Technical Communication – Principles and Practices by Meenakshi Raman & Sangeeta Sharma, Oxford
Univ. Press, 2016, New Delhi.
Reference Books:
1. Personality Development and Soft Skills by Barun K Mitra, Oxford Univ. Press, 2012, New Delhi.
2. Spoken English- A Manual of Speech and Phonetics by R K Bansal & J B Harrison, Orient Blackswan,
2013, New Delhi.
3. Business Correspondence and Report Writing by Prof. R C Sharma & Krishna Mohan, Tata McGraw Hill
& Co. Ltd., 2001, New Delhi.
4. Practical Communication: Process and Practice by L U B Pandey; A.I.T.B.S. Publications India Ltd.;
Krishan Nagar, 2014, Delhi.
5. Modern Technical Writing by Sherman, Theodore A (et.al); Apprentice Hall; New Jersey; USA.
6. A Textbook of Scientific and Technical Writing by S D Sharma; Vikas Publication, Delhi.
7. Skills for Effective Business Communication by Michael Murphy, Harvard University, USA.
8. A Complete Guide to Write Right by Agarwal, Deepa. Scholastic, 1
st
edition.
9. Technical writing and communication, R S Sharma, V.P. Publication, 1
st
edition.
10. Business Communication for Managers by Payal Mehra, Pearson Publication, Delhi.
B. TECH. SECOND YEAR
Course Code
ACSE0403A
L T P
Credits
Course Title
Operating Systems
3 0 0
3
Course objective:
The objective of the course is to provide an understanding of the basic modules and architecture of an
operating system and the functions of the modules to manage, coordinate and control all the parts of the
computer system. This course cover processor scheduling, deadlocks, memory management, process
synchronization, system call and file system management.
Pre-requisites:
1. Basic knowledge of computer fundamentals, Data structure and Computer organization.
Course Contents / Syllabus
UNIT-I
Fundamental Concepts of Operating System
8 Hours
Introduction, Functions of Operating System, Characteristics of Operating System, Computer System
Structure, Evolution of Operating Systems-Bare Machine, Single Processing, Batch
Processing,Multiprogramming,Multitasking,Multithreaded,Interactive, Time sharing, Real Time System,
Distributed System, Multiprocessor Systems, Multithreaded Systems, System Calls, System Programs and
System Boot, Interrupt Handling, Operating System Structure- Simple structure, Layered Structure,
Monolithic, Microkernel and Hybrid, System Components, Operating System Services, Case Studies:
Windows, Unix and Linux.
UNIT-II
Process Management
8 Hours
Scheduling Concepts, Performance Criteria, Process States, Process Transition Diagram, Schedulers, Process
Control Block (PCB), Process Address Space, Process Identification Information, Threads and their
management, Types of Scheduling: Long Term Scheduling, Mid Term Scheduling, Short Term Scheduling,
Pre-emptive and Non Pre-emptive Scheduling, Dispatcher, Scheduling Algorithm: FCFS, Non Pre-emptive
SJF, Pre-emptive SJF, Non Pre-emptive Priority, Pre-emptive Priority, Round Robin, Multilevel Queue
Scheduling and Multilevel Feedback Queue Scheduling.
UNIT-III
Deadlock and Concurrent Processing
8 Hours
Deadlock: System model, Deadlock characterization, Prevention, Avoidance and detection, Recovery from
Deadlock,Principle of Concurrency, Process Synchronization, Producer / Consumer Problem, Mutual
Exclusion, Critical Section Problem, Peterson’s Solution, Lamport Bakery Solution, Semaphores, Test and
Set Operation; Critical Section Problems and their solutions - Bound Buffer Problem, Reader-Writer
Problem, Dining Philosopher Problem, Sleeping Barber Problem; Inter Process Communication Models and
Schemes, Process Generation.
UNIT-IV
Memory Management
8 Hours
Memory Management function, Address Binding Loading : Compile Time, Load Time and Execution Time,
MMU, Types of Linking, Types of Loading, Swapping, Multiprogramming with Fixed Partitions,
Multiprogramming with variable partitions, Memory Allocation: Allocation Strategies First Fit, Best Fit, and
Worst Fit, Paging, Segmentation, Paged Segmentation, Virtual Memory Concepts, Demand Paging,
Performance of Demand Paging, Page Replacement Algorithms: FIFO,LRU, Optimal and LFU,
Belady’sAnomaly, Thrashing, Cache Memory Organization, Locality of Reference.
UNIT-V
I/O Management and Disk Scheduling
8 Hours
I/O Devices, and I/O Subsystems, I/O Buffering, I/O Ports, Disk Storage: Seek Time, Rotational Latency,
Data Transfer Time, Average Access Time and Controller Time,DiskStorage Strategies, Disk
Scheduling:FCFS, SSTF, SCAN, C-SCAN, LOOK and C-LOOK. Directory and Directory Structure, File
System: File concept, File Access Mechanism: - Sequential Access, Direct Access and Index Access
methods, File Allocation Method: Contiguous, Linked and Indexed, Free Space Management: -Bit Vector,
Linked List, Grouping and Counting File System Implementation Issues, File System Protection and Security,
RAID.
Course outcome: After completion of this course students will be able to:
CO 1
Understand the fundamentals of an operating systems, functions and their structure and
functions.
K1, K2
CO 2
Implement concept of process management policies, CPU Scheduling and thread
management.
K5
CO 3
Understand and implement the requirement of process synchronization and apply
deadlock handling algorithms.
K2, K5
CO 4
Evaluate the memory management and its allocation policies.
K5
CO 5
Understand and analyze the I/O management and File systems
K2, K4
Text books:
1) Operating System Concepts Essentials. Abraham Silberschatz, Peter Baer Galvin and Greg Gagne.
Reference Books:
1) Operating Systems: Internals and Design Principles. William Stallings.
2) Operating System: A Design-oriented Approach. Charles Patrick Crowley.
3) Operating Systems: A Modern Perspective. Gary J. Nutt.
4) Design of the Unix Operating Systems. Maurice J. Bach.
5) Understanding the Linux Kernel, Daniel Pierre Bovet, Marco Cesati.
Link:
Unit 1
https://www.youtube.com/watch?v=783KAB-tuE4
https://www.youtube.com/watch?v=Bxx2_aQVeeg
https://www.youtube.com/watch?v=ZaGGKFCLNc0
https://nptel.ac.in/courses/106/105/106105214/
Unit 2
https://www.youtube.com/watch?v=NShBeqTkXnQ
https://www.youtube.com/watch?v=4hCih9eLc7M
https://www.youtube.com/watch?v=9YRxhlvt9Zo
Unit 3
https://www.youtube.com/watch?v=UczJ7misUEk
https://www.youtube.com/watch?v=_IxqinTs2Yo
Unit 4
https://www.youtube.com/watch?v=IwESijQs9sM
https://www.youtube.com/watch?v=-orfFhvNBzY
https://www.youtube.com/watch?v=2OobPx246zg&list=PL3-wYxbt4yCjpcfUDz-
TgD_ainZ2K3MUZ&index=10
Unit 5
https://www.youtube.com/watch?v=AnGOeYJCv6s
https://www.youtube.com/watch?v=U1Jpvni0Aak
B. TECH. SECOND YEAR
Course Code
ACSAI0402
L T P
Credit
Course Title
Database Management Systems
3 1 0
4
Course objective:
The objective of the course is to present an introduction to database management systems, with an emphasis on
how to organize, maintain and retrieve - efficiently, and effectively - information in relational and non-relation
Database.
Pre-requisites:The student should have basic knowledge of discrete mathematics and data structures.
Course Contents / Syllabus
UNIT-I
Introduction
8 Hours
Overview, Database system Vs File system, Database system concepts, architecture and structures, data model
schema and instances, Data independence and Database language and Interfaces, DDL, DML.
Data Modeling using the Entity Relationship Model: ER model concepts, notation for ER diagram, mapping
constraints, keys, Concepts of Super Key, Candidate key, Primary key, Generalization, Aggregation,
Reduction of an ER diagrams to tables, Extended ER model, Relationship of higher degree.
UNIT-II
Relational Data Model and Language
8 Hours
Relational data model Concepts, Integrity constraints, Entity integrity, Referential integrity, Keys constraints,
Domain constraints, Relational algebra, Relational calculus, Tuple and Domain calculus.
Introduction on SQL: Characteristics of SQL, advantage of SQL. SQL data type and literals. Types of SQL
commands. SQL operators and their procedure. Tables, Views and indexes. Queries and sub queries.
Aggregate functions. Insert, Update and Delete operations, Joins, Unions, Intersection, Minus, Cursors,
Triggers, Procedures in SQL/PL SQL.
UNIT-III
Database Design-Normalization
8 Hours
Normalization, Normal Form (NF), Functional Dependencies (FD), Closure of an attribute set and FD sets,
Canonical Cover of FD Sets, Normal Forms based on Functional Dependencies (1 NF, 2 NF, 3 NF, BCNF),
Multivalued Dependencies (MVDs) and 4NF, Join Dependencies (JDs) and 5NF and Domain Key Normal
Formal (DKNF or 6NF), Inclusion Dependencies, Loss-Less Join Decompositions.
UNIT-IV
Transaction Processing and Recovery Concept
8 Hours
Transaction system, Testing of serializability, Serializability of schedules, Conflict &View serializable
schedule, Recoverability, Recovery from transaction failures, Log based recovery, Checkpoints, Deadlock
handling.
Control Concurrency Techniques: Concurrency Control, Locking Techniques for concurrency control, Time
stamping protocols for concurrency control, Validation-based protocol, Multiplegranularity, Multi version
schemes, Recovery with concurrent transaction, Case study of Oracle.
Distributed Database: -Introduction Distributed Database, Centralized and Distributed System Database
System.
UNIT-V
Introduction No-SQL with cloud Database
8 Hours
Definition of NoSQL, History of NoSQL and Different NoSQL products, Exploring Mongo DB, Interfacing
and Interacting with NoSQL, NoSQL Storage Architecture, CRUD operations with MongoDB, Querying,
Modifying and Managing NoSQL Data stores, Indexing and ordering datasets(MongoDB).
Cloud database: - Introduction of Cloud database, NoSQL with Cloud Database, Introduction to Real time
Database.
Course outcome: After completion of this course students will be able to:
CO 1
Analyze database used to solve real world and complex problem and design the
ER, EER Model.
K4
CO 2
Analyze and apply Structured Query Language (SQL) or Procedural Query
Language (PL/SQL) to solve the complex queries. Implement relational model,
integrity constraints.
K4,K3
CO 3
Design and implement database for storing, managing data efficiently by
applying the Normalization process on the database.
K6
CO 4
Synthesize the concepts of transaction management, concurrency control and
recovery.
K5
CO 5
Understand and implement the concepts of NoSQL with cloud database.
K2, K5
Text books:
1) Korth, Silbertz, Sudarshan,” Database System Concepts”, Seventh Edition, McGraw - Hill.
2) Elmasri, Navathe, “ Fundamentals of Database Systems”, Seventh Edition, Addision Wesley.
3) Ivan Bayross “SQL,PL/SQL The programming language Oracle, Forth Edition, BPB Publication.
Reference Books:
1) Thomas Cannolly and Carolyn Begg, “Database Systems: A Practical Approach to Design, Implementation
and Management”, Third Edition, Pearson Education, 2007.
2) Raghu Ramakrishan and Johannes Gehrke “Database Management Systems” Third Edition, McGraw-Hill.
3) NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software First Edition by Ted
Hills.
4) Brad Dayley “NoSQL with MongoDB in 24 Hours” First Edition, Sams Publisher.
NPTEL/ Youtube/ Faculty Video Link:
Unit 1
https://www.youtube.com/watch?v=TlbJk78TqYY
http://www.nptelvideos.com/lecture.php?id=6472
http://www.nptelvideos.com/lecture.php?id=6473
Unit 2
http://www.nptelvideos.com/lecture.php?id=6474
http://www.nptelvideos.com/lecture.php?id=6475
http://www.nptelvideos.com/lecture.php?id=6476
http://www.nptelvideos.com/lecture.php?id=6477
http://www.nptelvideos.com/lecture.php?id=6478
http://www.nptelvideos.com/lecture.php?id=6479
http://www.nptelvideos.com/lecture.php?id=6480
http://www.nptelvideos.com/lecture.php?id=6481
Unit 3
http://www.nptelvideos.com/lecture.php?id=6484
http://www.nptelvideos.com/lecture.php?id=6485
http://www.nptelvideos.com/lecture.php?id=6486
http://www.nptelvideos.com/lecture.php?id=6487
http://www.nptelvideos.com/lecture.php?id=6493
http://www.nptelvideos.com/lecture.php?id=6495
http://www.nptelvideos.com/lecture.php?id=6496
http://www.nptelvideos.com/lecture.php?id=6497
Unit 4
http://www.nptelvideos.com/lecture.php?id=6499
http://www.nptelvideos.com/lecture.php?id=6500
http://www.nptelvideos.com/lecture.php?id=6501
http://www.nptelvideos.com/lecture.php?id=6502
http://www.nptelvideos.com/lecture.php?id=6503
http://www.nptelvideos.com/lecture.php?id=6504
http://www.nptelvideos.com/lecture.php?id=6505
http://www.nptelvideos.com/lecture.php?id=6506
http://www.nptelvideos.com/lecture.php?id=6508
http://www.nptelvideos.com/lecture.php?id=6509
http://www.nptelvideos.com/lecture.php?id=6514
http://www.nptelvideos.com/lecture.php?id=6516
http://www.nptelvideos.com/lecture.php?id=6517
http://www.nptelvideos.com/lecture.php?id=6518
http://www.nptelvideos.com/lecture.php?id=6519
Unit 5
http://www.nptelvideos.com/lecture.php?id=6516
http://www.nptelvideos.com/lecture.php?id=6517
http://www.nptelvideos.com/lecture.php?id=6518
http://www.nptelvideos.com/lecture.php?id=6519
https://www.youtube.com/watch?v=2yQ9TGFpDuM
B. TECH. SECOND YEAR
Course Code
ACSML0401
L T P
Credits
Course Title
Machine Learning
3 0 0
3
Course objective:
Introduce to the basic techniques of Machine Learning. Develop the skills of understanding the challenges
of Machine Learning. Capability to enhance the skills for problem solving. Analytic power for underlying
mathematical relationships within and across Machine Learning algorithms and the paradigms of supervised
and un-supervised learning.
Pre-requisites:Basic Knowledge of Machine Learning Concepts.
Course Contents / Syllabus
UNIT-I
Introduction
8 Hours
INTRODUCTION-Learning, Types of Learning, well defined learning problems, designing a Learning
System, History of ML, Introduction of Machine Learning Approaches, General-to-specific ordering of
hypotheses, Find-S, List then eliminate algorithm, Candidate elimination algorithm, Inductive bias, Issues
in Machine Learning and Data Science Vs Machine Learning.
UNIT-II
Machine Learning Regression Techniques
6Hours
REGRESSION AND ITS TYPES: Regression Terminologies: Dependent variable, independent variable,
outliers, Multicollinearity, Underfitting and overfitting, Types of Regression: Linear Regression Logistic
Regression, Polynomial Regression etc. Application of Regression in Machine Learning.
UNIT-III
Machine Learning Techniques
10Hours
INSTANCE-BASED LEARNING: k-Nearest Neighbor Learning.
DECISION TREE LEARNING - Decision tree learning algorithm, Inductive bias, Inductive inference
with decision trees, Entropy and information theory, Information gain, ID-3 Algorithm, Issues in Decision
tree learning.
SUPPORT VECTOR MACHINE: Introduction, Types of support vector kernel – (Linear kernel,
polynomial kernel, and Gaussian kernel, Hyperplane – (Decision surface), Properties of SVM, and Issues in
SVM.
BAYESIAN LEARNING - Bayes theorem, Concept learning, Bayes Optimal Classifier, Naïve Bayes
classifier, Bayesian belief networks, EM Algorithm.
CLUSTERING AND ITS TYPES: k-means clustering, Hierarchical Clustering, partitioning clustering,
Training and Evaluation of a model,Loss functions,Evaluation,Confusion Matrix,Dataset split and Cross-
validation,Underfitting and Overfitting,Feature Engineering.
UNIT-IV
ARTIFICIAL NEURAL NETWORKS
8 Hours
Neuron, Nerve structure and synapse, Artificial Neuron and its model, activation functions, Neural network
architecture: Single layer and Multilayer feed forward networks, recurrent networks. Various learning
techniques; Perception and Convergence rule, Hebb Learning. Perceptron’s, Multilayer perceptron,
Gradient descent and the Delta rule, Multilayer networks, Derivation of Backpropagation Algorithm.
Introduction to Deep Learning.
UNIT-V
REINFORCEMENT LEARNING
8 Hours
Introduction to Reinforcement Learning, Learning Task, Example of Reinforcement Learning in Practice,
Learning Models for Reinforcement – (Markov Decision process, Q Learning – Q Learning function, Q
Learning Algorithm), Application of Reinforcement Learning, Introduction to Deep Q Learning.
Case study:Health Care, E Commerce, Smart Cities
Course outcome: After completion of this course students will be able to
CO 1
Understand the need for machine learning for various problem solving
K2
CO 2
apply knowledge of machine learning algorithm to solve various types of learning
task/
Understand a wide variety of learning algorithms and how to evaluate models
generated from data
K3
CO 3
Apply decision tree and Bayesian learning techniques.
K3
CO 4
Apply machine learning solutions to classification, regression, and clustering
problems
K3
CO 5
Evaluate and interpret the results of machine learning algorithms.
K4
Text books:
1) Tom M. Mitchell, ―Machine Learning, McGraw-Hill Education (India) Private Limited 2013.
2) EthemAlpaydin, ―Introduction to Machine Learning (Adaptive Computation andMachine Learning),
The MIT Press. 2014
Reference Books:
1) Stephen Marsland, ―Machine Learning: An Algorithmic Perspective, CRC Press 2015.
2) Bishop, C., Pattern Recognition and Machine Learning. Berlin: Springer-Verlag.2011
NPTEL/ Youtube/ Faculty Video Link:
Unit 1
https://nptel.ac.in/courses/106/106/106106198/
Unit 2
https://nptel.ac.in/courses/111/107/111107137/
Unit 3
https://nptel.ac.in/courses/106/106/106106202/
Unit 4
https://nptel.ac.in/courses/106/106/106106213/
Unit 5
https://nptel.ac.in/courses/106/105/106105152/
B. TECH. SECOND YEAR
Course Code
ACSE0404
L T P
Credits
Course Title
Theory of Automata and Formal Languages
3 0 0
3
Course objective:
To teach mathematical foundations of computation including automata theory, provide the design concepts of
abstract computation model of finite automata, push down automata and turing Machine and familiarize the
notions of algorithm, decidability, complexity, and computability.
Pre-requisites:
Discrete Mathematics
Fundamental of Computer System
Course Contents / Syllabus
UNIT-I
Basic Concepts of Formal Language and Automata Theory
8 Hours
Introduction to Theory of Computation- Alphabet, Symbol, String, Formal Languages, Grammar, Derivation
and Language generation by Grammar, Chomsky Hierarchy, Finite Automata, Deterministic Finite
Automaton (DFA)- Definition, Representation, Acceptability of a String and Language, Non-Deterministic
Finite Automaton (NFA), Equivalence of DFA and NFA, NFA with ∊-Transition, Equivalence of NFA’s
with and without ∊-Transition, Finite Automata with output- Moore Machine, Mealy Machine, Equivalence
of Moore and Mealy Machine, Minimization of Finite Automata, Myhill-Nerode Theorem, Simulation of
DFA and NFA.
UNIT-II
Regular Language and Finite Automata
8 Hours
Regular Expressions, Transition Graph, Kleen’s Theorem, Finite Automata and Regular Expression- Arden’s
theorem, Algebraic Method Using Arden’s Theorem, Regular Grammars-Right Linear and Left Linear
grammars, Conversion of FA into Regular grammar and Regular grammar into FA, Regular and Non-
Regular Languages- Closure properties of Regular Languages, Pigeonhole Principle, Pumping Lemma,
Application of Pumping Lemma.
Decidability- Decision properties, Finite Automata and Regular Languages, Simulation of Transition Graph
and Regular language.
UNIT-III
Context Free Language and Grammar
8 Hours
Context Free Grammar (CFG)-Definition, Derivations, Languages, Derivation Trees and Ambiguity,
Simplification of CFG, Normal Forms- Chomsky Normal Form (CNF), Greibach Normal Form (GNF),
Pumping Lemma for CFL, Closure properties of CFL, Decision Properties of CFL
UNIT-IV
Push Down Automata
8 Hours
Pushdown Automata- Definition, Representation, Instantaneous Description (ID), Acceptance by PDA,
Nondeterministic Pushdown Automata (NPDA)- Definition, Moves, Pushdown Automata and Context Free
Language, Pushdown Automata and Context Free Grammar, Two stack Pushdown Automata.
UNIT-V
Turing Machine and Undecidability
8 Hours
Turing Machine Model, Representation of Turing Machines, Language Acceptability of Turing Machines,
Techniques for Turing Machine Construction, Variations of Turing Machine, Turing Machine as Computer
of Integer Functions, Universal Turing machine, Linear Bounded Automata, Church’s Thesis, Recursive and
Recursively Enumerable language, Closure Properties of Recursive and Recursively Enumerable Languages,
Non-Recursively Enumerable and Non-Recursive Languages, Undecidability, Halting Problem,
Undecidability of Halting Problem, Post’s Correspondence Problem.
Course outcome: After completion of this course students will be able to:
CO 1
Design and Simplify automata for formal languages and transform non-deterministic finite
automata to deterministic finite automata.
K6
CO 2
Identify the equivalence between the regular expression and finite automata and apply
closure properties of formal languages to construct finite automata for complex problems.
K3
CO 3
Define grammar for context free languages and use pumping lemma to disprove a formal
language being context- free.
K3
CO 4
Design pushdown automata (PDA) for context free languages and Transform the PDA to
context free grammar and vice-versa.
K6
CO 5
Construct Turing Machine for recursive and recursive enumerable languages. Identify the
decidable and undecidable problems.
K6
Text books:
(1) Introduction to Automata theory, Languages and Computation, J.E. Hopcraft, R. Motwani, and Ullman.
3
rd
edition, Pearson Education Asia.
(2) Theory of Computer Science-Automata Language and Computation, K.L.P. Mishra, and N.
Chandrasekharan, 3
rd
Edition, PHI.
(3) An Introduction to Formal Languages and Automata, P. Linz, 6
th
Edition, Jones & Bartlett Learning
Publication.
Reference Books:
(1) Finite Automata and Formal Languages- A simple Approach, A. M. Padma Reddy, Cengage Learning
Inc.
(2) Elements and Theory of Computation, C Papadimitrou and C. L. Lewis, PHI.
(3) Introduction to languages and the theory of computation, J Martin, 3rd Edition, Tata McGraw Hill.
(4) Introduction to The Theory of Computation, M Sipser, 3
rd
Edition, Cengage Learning Inc.
Links:
Unit I
https://nptel.ac.in/courses/106/104/106104028/Lecture 1 -10, Lecture 16, 17 18, 19
https://nptel.ac.in/courses/113/11111/1003016/
https://www.youtube.com/results?search_query=%23AutomataTheory
Unit II
https://nptel.ac.in/courses/106/104/106104028/Lecture 11 -15
https://nptel.ac.in/courses/113/11111/1003016/
https://www.youtube.com/results?search_query=%23AutomataTheory
Unit III
https://nptel.ac.in/courses/106/104/106104028/Lecture 20 -30
https://nptel.ac.in/courses/106/106/106106049/
https://www.youtube.com/results?search_query=%23AutomataTheory
Unit IV
https://nptel.ac.in/courses/106/104/106104028/Lecture 31 -33
https://nptel.ac.in/courses/113/11111/1003016/
https://www.youtube.com/results?search_query=%23AutomataTheory
Unit V
https://nptel.ac.in/courses/106/104/106104028/Lecture 34-42
https://nptel.ac.in/courses/113/11111/1003016/
https://www.youtube.com/results?search_query=%23AutomataTheory
B. TECH. SECOND YEAR
Course Code
ACSE0453A
L T P
Credits
Course Title
Operating Systems Lab
0 0 2
1
List of Experiments:
Sr. No.
Name of Experiment
CO
1. Linux based
Commands
Lab1: Execute Various types of Linux Commands (Miscellaneous, File oriented,
Directory oriented)
Lab2: Shell Programming
Write a shell program, which accepts the name of a file from standard input and
perform the following test on it:
i. File readable
ii. File writable
iii. Both readable and writable
CO1
2. CPU
Scheduling
Algorithms
Lab3: Implement CPU Scheduling Algorithms:
1. FCFS
2. SJF
3. PRIORITY
Lab4:
4. Round Robin
5. Multi-level Queue Scheduling
CO3
3. Deadlock
Management
Lab5: Implementation of Banker’s algorithm for the purpose of Deadlock
Avoidance.
CO3
4. Memory
Management
Techniques
Lab6: Write a program to simulate the following contiguous memory allocation
techniques:
a) First fit
b) Best fit
c) Worst Fit
Lab7: a) Write a Program for implementation of Contiguous memory fixed
partition technique.
b) Write a program for implementation of Contiguous memory variable partition
technique.
Lab8: Write a program to simulate page replacement algorithms:
a) FIFO
b) LRU
c) Optimal
CO4
5. Disk
Scheduling
Techniques
Lab9: Write a program to simulate Disk Scheduling Algorithms:
a) FCFS
b) SSTF
Lab 10: c) SCAN & C-SCAN
d) Look & C-LOOK
CO5
6. Process
Synchronization
Lab11: Write a program to simulate Producer Consumer problem
CO2
Lab Course Outcome: After completion of this course students will be able to
CO1
Gain all round knowledge of various Linux Commands.
K2
CO2
Analyze and implement Process Synchronization technique.
K4,K5
CO3
Analyze and implement CPU scheduling algorithms.
K4, K5
CO4
Analyze and implement Memory allocation and Memory management techniques.
K4, K5
CO5
Analyze and implement Disk Scheduling Policies.
K4, K5
B. TECH. SECOND YEAR
Course Code
ACSAI0452
L T P
Credit
Course Title
Database Management Systems Lab
0 0 2
1
List of Experiments:
Sr. No.
Name of Experiment
CO
1.
Installing ORACLE/ MYSQL/NOSQL.
CO1
2.
Creating Entity-Relationship Diagram using case tools with Identifying (entities,
attributes, keys and relationships between entities, cardinalities, generalization,
specialization etc.)
CO1
3.
I. Implement DDL commands –Create, Alter, Drop etc.
II. Implement DML commands- Insert, Select, Update, Delete
CO2
4.
I. Implement DCL commands-Grant and Revoke
II. Implement TCL commands- Rollback, Commit, Save point
III. Implement different type key: -Primary Key, Foreign Key and Unique etc.
CO2
5.
Converting ER Model to Relational Model (Represent entities and relationships in
Tabular form, Represent attributes as columns, identifying keys).
CO1, CO2
6.
Practice Queries using COUNT, SUM, AVG, MAX, MIN, GROUP BY,
HAVING, VIEWS Creation and Dropping.
CO2
7.
Practicing Queries using ANY, ALL, IN, EXISTS, NOT EXISTS, UNION,
INTERSECT, CONSTRAINTS etc.
CO2
8.
Practicing Sub queries (Nested, Correlated) and Joins (Inner, Outer and Equi).
CO2
9.
Practicing on Triggers - creation of trigger, Insertion using trigger, Deletion using
trigger, Updating using trigger
CO4
10.
Procedures- Creation of Stored Procedures, Execution of Procedure, and
Modification of Procedure
CO4
11.
Cursors- Declaring Cursor, Opening Cursor, Fetching the data, closing the cursor.
CO4
12.
Study of Open Source NOSQL Database: MongoDB (Installation, Basic CRUD
operations, Execution)
CO5
13.
Design and Develop MongoDB Queries using CRUD operations. (Use CRUD
operations, SAVE method, logical operators)
CO5
14.
Implement aggregation and indexing with suitable example using MongoDB.
CO5
15.
Mini project (Design & Development of Data and Application) for following: -
a) Inventory Control System.
b) Material Requirement Processing.
c) Hospital Management System.
d) Railway Reservation System.
e) Personal Information System.
CO1
f) Web Based User Identification System.
g) Timetable Management System.
h) Hotel Management System
Lab Course Outcome: After completion of this course students will be able to
CO 1
Design and implementthe ER, EER model to solve the real-world problem and
transform an information model into a relational database schema and to use a data.
K6
CO 2
Formulate and evaluate query using SQL solutions to a broad range of query and
data update problems.
K6
CO 3
Apply and create PL/SQL blocks, procedure functions, packages and triggers,
cursors.
K3, K6
CO 4
Analyze entity integrity, referential integrity, key constraints, and domain
constraints on database.
K4
CO5
Demonstrate understanding of MongoDB and its query operations.
K3
B. TECH. SECOND YEAR
Course Code
ACSML0451
L T P
Credit
Course Title
Machine Learning Lab
0 0 2
1
List of Experiments:
Sr. No.
Name of Experiment
CO
1.
Write a program to perform various types of regression (Linear &
Logistic)
CO1, CO2, CO3,
CO4
2.
Demonstrate the working of the decision tree based ID3 algorithm. Use
an appropriate data set for building the decision tree and apply this
knowledge to classify a new sample.
CO1, CO2, CO3,
CO4
3.
Build an Artificial Neural Network by implementing the Back-
propagation algorithm and test the same using appropriate data sets.
CO1, CO2, CO3,
CO4
4.
Implement naïve Bayesian Classifier model. Write the program to
calculate the accuracy, precision, and recall for your data set.
CO1, CO2, CO3,
CO4
5.
Apply EM algorithm to cluster a set of data. Use the same data set for
clustering using k-Means algorithm. Compare the results of these two
algorithms and comment on the quality of clustering.
CO1, CO2, CO3,
CO4
6.
Implement k-Nearest Neighbour algorithm to classify the iris data set.
Print both correct and wrong predictions.
CO1, CO2, CO3,
CO4
7.
Implement Support Vector Machine using Scikit-learn
CO1, CO2, CO 3,
CO4
8.
Implement the non-parametric Locally Weighted Regression algorithm
in order to fit data points. Select appropriate data set for your
experiment and draw graphs.
CO1, CO2, CO3,
CO4
9.
Implementation of Image features Processing using OPENCV AND
OPEN VINO
CO3
10.
For a given set of training data examples stored in a. CSV file,
implement and demonstrate the Candidate-Elimination algorithm to
output a description of the set of all hypotheses consistent with the
training examples.
CO3, CO4
Lab Course Outcome: On completion of the course, student will be able to
CO 1
Understand the implementation procedures for the ML algorithms.
K2
CO 2
Design python programs for various learning algorithms.
K6
CO 3
Apply appropriate data sets to the machine learning algorithms.
K3
CO 4
Identify and apply machine learning algorithms to solve real world problems.
K2
B. TECH. SECOND YEAR
Course Code
ANC0402
L T P
Credits
Course Title
Environmental Science
2 0 0
0
Course objective:
1
To help the students in realizing the inter-relationship between man and environment. and
help the students in acquiring basic knowledge about environment.
2
To develop the sense of awareness among the students about environment and its various problems.
3
To create positive attitude about environment among the student.
4
To develop proper skill required for the fulfilment of the aims of environmental education and educational
evaluations
5
To develop the capability of using skills to fulfil the required aims, to realise and solve environmental problems
through social, political, cultural and educational processes
Pre-requisites: Basic knowledge of nature.
Course Contents / Syllabus
UNIT-I
Basic Principle of Ecology
8 Hours
Definition, Scope and basic principles of ecology and environment. Ecosystem: Basic concepts, components of
ecosystem. Food chains and food webs. Ecological pyramids, Energy flow in ecological systems, Characteristics of
different ecosystems. Biogeochemical Cycles: Importance, gaseous and sedimentary cycles. Carbon, Nitrogen,
Phosphorus and Sulphur Cycles.
Basic concepts of sustainable development, SDGs, Ecosystem services, UN Decade for Ecorestoration.
UNIT-II
Natural Resources and Associated Problems
8 Hours
Natural resources and associated problems. Forest resources: Use and over-exploitation, deforestation. Timber
extraction, mining, dams and their effects on forest and tribal people. Mineral resources: Use and exploitation,
environmental effects of extracting and using mineral resources. Food resources: World food problems, changes caused
by agriculture and over-grazing, effects of modern agriculture, fertilizer-pesticide problems, water logging, salinity.
Land resources: Land as a resource, land degradation, man induced landslides. Equitable use of resources for sustainable
lifestyles.
Non-Renewable Energy Resources: Fossil fuels and their reserves, Nuclear energy, types, uses and effects, Renewable
Energy Resources: hydropower, Solar energy, geothermal, tidal and wind energy, Biomass energy, biogas and its
advantages.
UNIT-III
Biodiversity Succession and Non-Renewable Energy Resources
8 Hours
Biodiversity and their importance, Threats to biodiversity, major causes, extinction’s, vulnerability of species to
extinction, IUCN threat categories, Red data book.
Strategies for biodiversity conservation, principles of biodiversity conservation in-situ and ex-situ conservation
strategies Mega diversity zones and Hot spots, concepts, distribution and importance.
Succession: Concepts of succession, Types of Succession. Trends in succession. Climax and stability.
UNIT-IV
Pollution and Solid Waste Management
8 Hours
Air pollution: sources of air pollution, Primary and secondary air pollutants. Origin and effects of SOX, NOX, Cox,
CFC, Hydrocarbon, control of air pollution. Water pollution: sources and types of water pollution, Effects of water
pollution, Eutrophication, Soil pollution: Causes of soil pollution, Effects of soil pollution, Major sources of and effects
of noise pollution on health, Radioactive and thermal pollution sources and their effects on surrounding environment.
Solid waste disposal and its effects on surrounding environment, Climate change, global warming, acid rain, ozone layer
depletion.
UNIT-V
Role of Community and Environmental Protection Acts
8 Hours
Role of community, women and NGOs in environmental protection, Bioindicators and their role, Natural hazards,
Chemical accidents and disasters risk management, Environmental Impact Assessment (EIA), Salient features of
following Acts: a. Environmental Protection Act, 1986, Wildlife (Protection) Act, 1972.b. Water (Prevention and control
of pollution) Act, 1974.c. Air (Prevention and control of pollution) Act, 1981. Forest (Conservation) Act, 1980.d.
Wetlands (Conservation and Management) Rules, 2017; e. Chemical safety and Disaster Management law. F. District
Environmental Action Plan. Climate action plans.
Course outcome: After completion of this course students will be able to
CO 1
Understand the basic principles of ecology and environment. Ecosystem: Basic concepts,
components of ecosystem., food chains and food webs. Ecological pyramids
K2
CO 2
Understand the different types of natural recourses like food, forest, minerals and energy and their
conservation
K2
CO 3
Understand the importance of biodiversity, Threats of biodiversity and different methods of
biodiversity conservation.
K2
CO 4
Understand the different types of pollution, pollutants, their sources, effects and their control
methods
K3
CO 5
Understand the basic concepts of sustainable development, Environmental Impact Assessment
(EIA) and different acts related to environment
K3
Text books:
1. Brady, N.C. 1990. The nature and properties of Soils, Tenth Edition. Mac Millan Publishing Co., New York.
2. Botkin, D.B and Kodler E.A., 2000, Environmental Studies: The earth as a living planet. John Wiley and Sons Inc.
3. Rao M.N. and H.V.N. Rao, 1989: Air Pollution, Tata McGraw Hill Publishing Co. Ltd., New Delhi
4. Singh J.S., Singh S.P. and Gupta S.R., 2006, Ecology Environment and Resource Conservation, Anamaya Publishers,
New Delhi.
5.Environmental Studies -Benny Joseph-Tata McgrawHill-2005
6. Environmental Studies- Dr. D.L. Manjunath, Pearson Education-2006.
7. Environmental studies- R, Rajagopalan -Oxford Pubtiotion2005.
Reference Books:
1.Sodhi G.S. 2005, Fundamentals of Environmental Chemistry: Narosa Publishing House, New Delhi.
2.Dash, M.C. (1994), Fundamentals of Ecology, Tata Mc Graw Hill, New Delhi.
3. Sharma P. D. (1996). Environmental Biology, Rastogi Publications, Meerut.
4. Verma P.S. and V.K. Agarwal. (1985). Principles of Ecology. S. Chand and Company (Pub.), New Delhi.
5.Principles of Environmental Sciences and Engineering -P. Venugoplan Rao, Prenitice Hall of India.
6. Environmental Science and Engineering Meenakshi, Prentice Hall India.
NPTEL/ Youtube/ Faculty Video Link:
Unit 1
https://www.youtube.com/watch?v=T21OO0sBBfc,
https://www.youtube.com/watch?v=qt8AMjKKPDohttps://www.youtube.com/watch?v=yAK-
m91Nxrshttps://www.youtube.com/watch?v=ha_O-1uOWkk, https://www.youtube.com/watch?v=brF0RWJyx9w
Unit 2
https://www.youtube.com/watch?v=mOwyPENHhbc,https://www.youtube.com/watch?v=yqev1G2iy20,
https://www.youtube.com/watch?v=_74S3z3IO_I, https://www.youtube.com/watch?v=jXVw6M6m2g0
Unit 3
https://www.youtube.com/watch?v=GK_vRtHJZu4,https://www.youtube.com/watch?v=b6Ua_zWDH6U,
https://www.youtube.com/watch?v=7tgNamjTRkk,https://www.youtube.com/watch?v=ErATB1aMiSU,
https://www.khanacademy.org/science/high-school-biology/hs-ecology/hs-human-impact-on-
ecosystems/v/conservation-and-the-race-to-save-biodiversity
Unit 4
https://www.youtube.com/watch?v=7qkaz8ChelI,https://www.youtube.com/watch?v=NuQE5fKmfME,
https://www.youtube.com/watch?v=9CpAjOVLHII,https://www.youtube.com/watch?v=yEci6iDkXYw,
https://www.youtube.com/watch?v=yEci6iDkXYw
Unit 5
https://www.youtube.com/watch?v=ad9KhgGw5iA,https://www.youtube.com/watch?v=nW5g83NSH9M,
https://www.youtube.com/watch?v=xqSZL4Ka8xo,https://www.youtube.com/watch?v=WAI-hPRoBqs,
https://www.youtube.com/watch?v=o-WpeyGlV9Y, https://www.youtube.com/watch?v=EDmtawhADnY
B. TECH. SECOND YEAR
Course Code
ANC0401
L T P
Credit
Course Title
Cyber Security
2 0 0
0
Course objective:
Achieve knowledge about Security of Information system and Risk factors and examine security threats and
vulnerability in various scenarios, understand concept of cryptography and encryption technique to protect the
data from cyber-attackand provide protection for software and hardware.
Pre-requisites: Basics recognition in the domain of Computer Science.
Concept of network and operating system.
Commands of programming language.
Course Contents / Syllabus
UNIT-I
Introduction
8 Hours
Introduction to Information Systems: Types of Information Systems, Development of Information Systems,
Need for Information Security, Threats to Information Systems, Information Assurance, Guidelines for Secure
Password and WI-FI Security and social media and Windows Security, Security Risk Analysis, and Risk
Management.
UNIT-II
Application Layer Security
8 Hours
Data Security Considerations-Backups, Archival Storage and Disposal of Data, Security Technology-Firewall,
Intrusion Detection, Access Control, Security Threats -Viruses, Worms, Trojan
Horse,Bombs,Trapdoors,Spoofs, E-mail Viruses, Macro Viruses, Malicious Software,Network and Denial of
Services Attack.
E-Commerce: Electronic Payment System, e- Cash, Issues with Credit/Debit Cards.
UNIT-III
Secure System Development
8 Hours
Application Development Security, Architecture &Design,Security Issues in Hardware: Data Storage and
Downloadable Devices, Mobile Protection,SecurityThreats involving in social media, Physical Security of IT
Assets, Access Control, CCTV and Intrusion Detection Systems, Backup Security Measures.
UNIT-IV
Cryptography And Network Security
8 Hours
Public key cryptography: RSA Public Key Crypto with implementation in Python,Digital Signature Hash
Functions,Public Key Distribution.
Symmetric key cryptography: DES (Data Encryption Standard), AES (Advanced Encryption Standard), Secure
hash algorithm(SHA-1).
Real World Protocols: Basic Terminologies, VPN, Email Security Certificates, Transport Layer Security, TLS,
IP security, DNS Security.
UNIT-V
Security Policy
8 Hours
Policy design Task, WWW Policies, Email based Policies, Policy Revaluation Process-Corporate Policies-
Sample Security Policies,Publishing and Notification Requirement of the updated and new Policies.
Resent trends in security.
Course outcome: At the end of course, the student will be able to
CO 1
Analyze the cyber security needs of an organization.
K4
CO 2
Identify and examine software vulnerabilities and security
solutions.
K1,K3
CO 3
Comprehend IT Assets security (hardware and Software)
and performance indicators
K2
CO 4
Measure the performance and encoding strategies of
security systems.
K3, K5
CO 5
Understand and apply cyber security methods and policies
to enhance current scenario security.
K2, K3
Text books:
1) Charles P. Pfleeger, Shari LawerancePfleeger, “Analysing Computer Security”, Pearson Education India
2) V.K.Pachghare, “Cryptography and information Security”, PHI Learning Private Limited, Delhi India
3) Sarika Gupta & Gaurav Gupta, Information Security and Cyber Laws, Khanna Publishing House
4) Michael E.Whitman and Herbert J Mattord "Principle of Information Security" Cengage
Reference Books:
1) Schou, Shoemaker, “Information Assurance for the Enterprise”, Tata McGraw Hill.
2) CHANDER, HARISH,” Cyber Laws and It Protection”, PHI Learning Private Limited,sDelhi
3) V.K. Jain, Cryptography and Network Security, Khanna Publishing House, Delhi
4) William Stallings, Network Security Essentials: Applications and Standards, Prentice Hall, 4th edition, 2010
E-books& E-Contents:
1) https://prutor.ai/welcome/
2) https://crypto.stanford.edu/cs155old/cs155-spring11/lectures/03-ctrl-hijack.pdf
3) https://cybermap.kaspersky.com/stats
4) https://www.fireeye.com/cyber-map/threat-map.html
Reference Links:
1) https://crypto.stanford.edu/cs155old/cs155-spring11/lectures/03-ctrl-hijack.pdf
2) https://cs155.stanford.edu/lectures/03-isolation.pdf
3) http://uru.ac.in/uruonlinelibrary/Cyber_Security/Cryptography_and_Network_Security.pdf
NPTEL/ Youtube/ Faculty Video Link:
1) https://www.youtube.com/watch?v=vv1ODDhXW8Q
2) https://www.youtube.com/watch?v=fQ3ESFfvchg&list=PLUtfVcb-iqn834VGI9faVXGIGSDXZMGp8
3) https://www.youtube.com/watch?v=iTVyKbDCJrA&list=PLgMDNELGJ1CbdGLyn7OrVAP-IKg-0q2U2
4) https://www.youtube.com/watch?v=1plMO7ChXMU&list=PLJ5C_6qdAvBFAuGoLC2wFGruY_E2gYtev
5) https://www.youtube.com/watch?v=_9QayISruzo
