Post on 01-Jun-2020
CSE 2016 BATCH 1
CURRICULUM FOR 2016 BATCH STUDENTS
COMPUTER SCIENCE & ENGINEERING
SEMESTER I
SEMESTER II
Course Course Name L
T P Total Credits
Code
MA 105 Calculus 3 1 0 8
PH 107 Quantum physics 2 1 0 6
CH 105 Organic chemistry and Inorganic chemistry 2 0 0 4
CH 107 Physical chemistry 2 0 0 4
CH 117 Chemistry laboratory 0 0 3 3
CS 101
Computer programming and Utilization 3
0
2
8
NO 101 National Sports Organisation 0 0 0 P/NP
Total Credits 33
Course Course Name L
T P Total Credits
Code
MA 106 Linear Algebra 2 0 0 4
MA 108 Differential equations 2 0 0 4
PH 108 Electricity and Magnetism 2 1 0 6
CS 113 Data Structure and Algorithms 3 0 0 6
CS 193 Data Structure and Algorithms Laboratory 0 0 3 3
ME 119 Engineering Graphics & Drawing 5 0 5 8
PH 117 Physics Laboratory 0 0 3 3
BB 101 Biology 2 1 0 6
NO 102 National Sports Organisation 0 0 0 P/NP
Total Credits 40
CSE 2016 BATCH 2
SEMESTER III
Course Course Name L
T P Total Credits
Code
CS 207 Discrete Structures 3 0 0 6
EE 215 Data Analysis 3 0 0 6
HS 101 Economics 3 0 0 6
EE 101
Introduction to Electrical and Electronics
Circuits 0
0
3
8
CS 251 Software Systems Laboratory 1 3 0 8
Total Credits 34
SEMESTER IV
Course Course Name L
T P Total Credits
Code
CS 310 Automata Theory 3 1 0 6
CS 348 Computer Networks 3 0 0 6
CS 218 Design and Analysis of Algorithms 3
0 0 6
EE 204 Digital Systems 3 0 0 6
MA 214
Numerical Analysis 3
1
0
8
CS 212 Computer Networks Laboratory 0 0 3 3
EE 214 Digital Circuits Laboratory 0 0 3 3
Total Credits 38
CSE 2016 BATCH 3
SEMESTER 6
* Only for those CSE students who have taken DSP as an elective course in V
semester.
COMPUTER SCIENCE AND ENGINEERING
(2016 BATCH) - SEMESTER V
Course
Code Course Name Course Structure
L T P C
CS 301 Computer Architecture 3 0 0 6
CS 303 Data Bases and Information Systems 3 0 0 6
Elective I 3 0 0 6
Elective II 3 0 0 6
HSS Elective – I (Phil/Lit) 3 0 0 6
CS 311 Computer Architecture Laboratory 0 0 3 3
CS 313 Data Bases and Information Systems
Laboratory 0 0 3 3
Total Credits 36
Electives (I & II)
Course Code Course Name L T P Total Credits
CS 305 Graph Theory and Combinatorics 3 0 0 6
EE 305 Digital Signal Processing 3 0 0 6
EE 307 Probability and Random Processes 3 0 0 6
MA 301 Elementary Algebra and Number
Theory 3 0 0 6
HS 301 Philosophy 3 0 0 6
HS 303 Introduction to Literature 3 0 0 6
Course Course name
Credit Structure
Code
L T P C
CS 302 Artificial Intelligence 3 0 0 6
CS 304 Operating systems 3 0 0 6
CS 305 Software Engineering 3 0 0 6
CH 301 Environmental studies 3 0 0 6
CS 312 Artificial Intelligence Lab 0 0 3 3
CS 314 Operating systems Lab 0 0 3 3
Elective III 3 0 0 6
Total 36
EE 313 Digital Signal Processing lab* 0 0 3 3
CSE 2016 BATCH 4
Electives common for VI semester
Course Code Course name
Credit Structure
S. No.
L T P
C
1 EE 304 Robotics 2 0 2 6
2 MA 302
Algebraic codes and 3
0 0 6
Combinatorics
3 PH 301 Astrophysics for Engineers 3 0 0 6
4 MA 303
Fourier series and Fourier 3
0 0 6
transforms
5 CH 302
Sustainable energy and energy 3
0 0 6
materials
6 MA 304
Graph Theory and its 3
0 0 6
applications.
7 Introduction to Artificial
CS 306 Neural Networks & Deep 3 0 0 6
Learning
8 CS 307
Topics in Design and Analysis 3
0 0 6
of Algorithms
9 ME 305 Synthesis of Mechanisms 3 0 0 6
10 ME 306 Theory of Elasticity 3 0 0 6
11 ME 307 Turbulence and Modelling 3 0 0 6
12 HS 302 Modernism and the ‘Hero’ 3 0 0 6
13 HS 304
Intellectual Property 3
0 0 6
Management
14 EE 304 Power Systems 2 1 0 6
15 EE 314 Electronics Design Lab* 1 0 4 6
*offered for Computer science students
COMPUTER SCIENCE AND ENGINEERING
(2016 BATCH)
SEMESTER VII
Course Code Course Name Course Structure
L T P C
Elective IV 6/8
Elective V 6/8
Elective VI / Project 6/8
Total Credits
2016 Batch CSE 5
List of Electives for VII semester
S. No. Course Name Course Structure Prerequisites
L T P C
1 Power-aware Computing 3 0 2 8
Exposure to Computer
Architecture, Operating
Systems
2 Distributed Systems 3 0 0 6
Exposure to Operating
Systems, Data
Structures and
Algorithms,
Programming in C++
3 Compilers 3 0 2 8
Exposure to Data
Structures and
Algorithms, Computer
Architecture, Automata
Theory
4 Graph Theory and
Combinatorics 3 0 0 6
Exposure to Discrete
Structures
5 Advanced Algorithms 3 0 0 6
Exposure to Discrete
Mathematics, Design
and Analysis of
algorithms, Data
structures and
Algorithms
6 Computer Graphics 3 0 2 8
Exposure to C/C++
Programming is
desirable, Data
Structures and
Algorithms, Basic
Linear Algebra.
7 Introduction to Logic 3 0 0 6 Exposure to Discrete
Mathematics
8 Principles of Programming
Languages 3 0 0 6
Exposure to Discrete
Mathematics, Computer
Programming
9 Machine Learning and Pattern
Recognition 3 0 0 6
Exposure to Calculus or
equivalent
10 Speech Processing 3 0 0 6
Exposure to Signals and
systems or Digital
signal processing or
Probability Theory
11 Power System Dynamics and
Control 2 0 1 6
Exposure to Power
System, Electrical
Machines
12 Wireless Communication 3 0 0 6
Exposure to Signals and
Systems, Probability,
Principles/Fundamental
s of Communications
13 Advanced topics in signal
processing 3 0 0 6
Exposure to Signals and
systems and/or digital
signal processing
14 Artificial Neural Networks &
Deep Learning 3 0 0 6
Exposure to Calculus,
Linear Algebra,
Probability, Random
2016 Batch CSE 6
Processes, Ability to
code in Python
15 Advanced Analog Circuits 3 0 0 6
Exposure to Electronic
devices and UG analog
circuits
16 Introduction to Combustion 3 0 0 6
Exposure to Fluid
Mechanics,
Thermodynamics, Heat
transfer
17 Introduction to Computational
Fluid Dynamics 3 0 0 6
Exposure to Fluid
Mechanics; Heat
Transfer; Numerical
Analysis; Computer
Programming
18 Finite Element Analysis 3 0 0 6 Nil
19 Fatigue and Fracture
Mechanics 3 0 0 6
Exposure to Strength of
Materials/Mechanics of
Materials & Theory of
Elasticity
20 Vibrations of Linear Systems 3 0 0 6 Exposure to SOM
21
Composite Materials:
Manufacturing, Properties &
Applications’
3 0 0 6 Nil
22 Quantum Mechanics 2 1 0 6
Exposure to Quantum
Physics and
Application, Linear
Algebra
23 Astrophysics for Engineers 3 1 0 8
Exposure to Electricity
& Magnetism, Calculus,
Linear Algebra and
Differential Equations
24 Classical Electrodynamics 2 1 0 6
Exposure to Electricity
& Magnetism, Calculus,
Linear Algebra and
Differential Equations
26 Statistical Mechanics 2 1 0 6
Exposure to Physics,
Chemistry and
Mathematics
27 Quantum Field Theory 2 1 0 6
Exposure to Physics,
Chemistry and
Mathematics
28 VLSI Design 3 0 0 6 Digital Systems
29 Advanced Power Electronics
and Drives 3 0 0 6
Exposure to Circuits,
Semiconductor devices
and Electric Machine &
Power Electronics
30 Basics of Accounting and
Financial Management 3 0 0 6 Nil
2016 Batch CSE 7
2016 Batch (SEMESTER I)
Academic Unit: Mathematics
Level: B. Tech.
Programme: B.Tech.
i Title of the course MA 105 Calculus
ii Credit Structure (L-T-P-C) (3-1-0-8)
iii Type of Course Core course
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content Review of limits, continuity, differentiability. Mean value
theorem, Taylors Theorem, Maxima and Minima. Riemann integrals, Fundamental theorem of Calculus,
Improper integrals, applications to area, volume.
Convergence of sequences and series, power series.
Partial Derivatives, gradient and directional derivatives,
chain rule, maxima and minima, Lagrange multipliers.
Double and Triple integration, Jacobians and change of
variables formula. Parametrization of curves and surfaces,
vector fields, line and surface integrals. Divergence and
curl, Theorems of Green, Gauss, and Stokes.
viii Texts/References 1. B.V. Limaye and S. Ghorpade, A Course in Calculus
and Real Analysis, Springer UTM (2004)
2. B.V. Limaye and S. Ghorpade, A Course in
Multivariable Calculus and Analysis, Springer UTM
(2010)
3. James Stewart, Calculus (5th Edition), Thomson
(2003).
4. T. M. Apostol, Calculus, Volumes 1 and 2 (2nd
Edition), Wiley Eastern (1980).
5. Marsden and Tromba, Vector calculus (First Indian
Edition), Springer (2012)
ix Name(s) of Instructor(s) BVL
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the This is a fundamental mathematics course which is
2016 Batch CSE 8
course essential for any branch of engineering
Name of Academic Unit: Physics
Level: B.Tech.
Programme: B.Tech.
i Title of the Course PH 107: Quantum Physics
ii Credit Structure (L-T-P-C) (2-1-0-6)
iii Type of Course Core course
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Full Course
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content Quantum nature of light: Photoelectric Effect and
Compton Effect.
Stability of atoms and Bohr`s rules. Wave particle duality: De Broglie wavelength, Group
and Phase velocity, Uncertainty Principle, Double Slit Experiment.
Schrödinger Equation. Physical interpretation of Wave Function,
Elementary Idea of Operators, Eigen-value Problem. Solution of Schrödinger equation for simple
boundary value problems. Reflection and Transmission Coefficients. Tunneling. Particle in a three dimensional box, Degenerate
states. Exposure to Harmonic Oscillator and Hydrogen
Atom without deriving the general solution. Quantum Statistics: Maxwell Boltzmann, Bose
Einstein and Fermi Dirac Statistics by detailed balance arguments.
Density of states. Applications of B-E statistics: Lasers. Bose-Einstein
Condensation. Applications of F-D statistics: Free electron model of
electrons in metals. Concept of Fermi Energy. Elementary Ideas of Band Theory of Solids. Exposure to Semiconductors, Superconductors,
Quantum Communication and Quantum Computing.viii Texts/References (separate sheet may 1. Quantum Physics: R. Eisberg and R. Resnick, John
be used, if necessary) Wiley 2002, 2nd Edition. 2. Introduction to Modern Physics: F. K. Richtmyer, E. H. Kennard and J.N. Cooper, Tata Mac Graw Hill
1976, 6th Edition. 3. Modern Physics: K. S. Krane, John Wiley 1998, 2nd
Edition.
4. Introduction to Modern Physics: Mani and Mehta,
East-West Press Pvt. Ltd. New Delhi 2000.
2016 Batch CSE 9
5. Elements of Modern Physics: S. H. Patil, Tata
McGraw Hill, 1984.
6. Concepts of Modern Physics, A Beiser, Tata
McGraw Hill, 2009.
ix Name(s) of Instructor(s) RP
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the No
same/ other academic unit(s) which
is/ are equivalent to this course? If so,
please give details.
xii Justification/ Need for introducing This course develops the concepts of Quantum
the course Mechanics such that the behavior of the physical universe can be understood from a fundamental point of view. It provides a basis for further study of
quantum mechanics.
It is necessary for students to undertake this course, as
the course sheds light on topics like, the basic
principles behind the working of semiconductor
devices, superconductors, etc. It is important to note
that, such devices occupy the central stage in current
technological advancements. The course also deals
with the basic concepts behind the most advanced
techniques like quantum communication and quantum
computation.
2016 Batch CSE 10
Name of Academic Unit: Chemistry
Level: B.Tech.
Programme: B.Tech.
i Title of the course
CH 105 Organic Chemistry and
Inorganic Chemistry
ii Credit Structure (L-T-P-C) (2-0-0-4)
iii Type of Course Common for all
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Half
Course
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content
Molecular orbitals of common functional groups,
Qualitative Huckel MOs ofconjugated polyenes and
benzene.Aromaticity. Configuration, molecular chirality
and isomerism, Conformation of alkanes and
cycloalkanes, Reactivity of carbonyl group), Functional
group interconversions involving oxidation and reduction,
Periodic properties: trends in size, electron affinity,
ionization potential and electronegativity, Use of
Ellingham diagram and thermodynamics in the extraction
of elements, Transition metal chemistry: inorganic
complexes, bonding theories, magnetism, bonding aspects
and structural distortion, Bioinorganic chemistry: storage
and transport proteins, Catalysis: hydrogenation,
hydroformylation and olefin metathesis.
Viii Text / References
1)P. Volhardt and N. Schore, Organic Chemistry: Structure and
Function, 5th Edition, W. H Freeman & Co, 2006 (2)T. W. G.
Solomons, C. B. Fryhle, Organic Chemistry, 9th Edition,
WilelyIndia Pvt. Ltd., 2009 (3)R. T. Morrison and R. N. Boyd,
Organic Chemistry, 6th edition, Pearson Com., 1992 (4)L. G.
Wade, Organic Chemistry, Pearson Education 6th edition,
2006. (5)M. J. Sienko and R. A. Plane, Chemical Principles and
Applications, McGraw Hill, 1980. (6)J. D. Lee, Concise
Inorganic Chemistry, 4th Edition, ELBS, 1991. (7)D. D.
Ebbing, General Chemistry, Houghton Miffin Co., 1984.
ix Name(s) of Instructor(s) --
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii
Justification/ Need for introducing
the course
Nil
2016 Batch CSE 11
Name of Academic Unit: Chemistry
Level: B.Tech.
Programme: B.Tech.
i Title of the course CH 107 Physical Chemistry
ii Credit Structure (L-T-P-C) (2-0-0-4)
iii Type of Course Common for all
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Half
Course
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content
Schrodinger equation,Origin of quantization, Born
interpretation of wave function, Hydrogen atom: solution
to -part, Atomic orbitals, many electron atoms and spin
orbitals. Chemical bonding: MO theory: LCAO molecular
orbitals, Structure, bonding and energy levels of diatomic
molecules.Concept of sp, sp2and sp3hybridization;
Bonding and shape of many atom molecules;
IntermolecularForces; Potential energy surfaces-Rates of
reactions; Steady state approximationand its applications;
Concept of pre-equilibrium; Equilibrium and
relatedthermodynamic quantities
Viii Text / References
(1)P. Atkins and J. de Paula, Atkins’ Physical Chemistry,
Oxford University Press, 8th edition, 2006. (2)I. N. Levine,
Physical Chemistry, 5th edition, Tata McGraw-Hill, New
Delhi, 2002. (3)D. A. McQuarrie and J.D. Simon, Physical
Chemistry - a molecular approach, Viva Books Pvt. Ltd.
(1998).
ix Name(s) of Instructor(s) --
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii
Justification/ Need for introducing
the course
Nil
2016 Batch CSE 12
Name of Academic Unit: Chemistry
Level: B.Tech.
Programme: B.Tech.
i Title of the course CH 117 Chemistry Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-4)
iii Type of Course Core course
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content Experimentsillustratingtheconceptsof1)
Electrochemical Cell, (2) Chemical kinetics, (3)
Estimation of Iron, (4) Oscillatory Chemical Reactions,
(5a) Electrolytic Conductance (5b) Crystalline Solids
(6) Colorimetric Analysis (7) Complexometric Titration
(8) Thin Layer Chromatography
viii Texts/References 1.Physical Chemistry, P.W. Atkins, 5th Edition
(ELBS/OUP) 1994.
2.Vogel’s Textbook of Quantitative Analysis revised by
G. H. Jeffery, J. Basset J. Mendham and R. C. Denny,
5th Edition.
3.Organic Chemistry, Morrison and Boyd, 6th Edition.
4.“Patterns in Time and Space - Generated by
Chemistry”, I. R. Epstein, C and E News, March 1987.
5.“An Oscillating Iodine Clock”, T. S. Brigg and W.C.
Rauischer, Journal of chemical education., Vol no. 50,
Issue no 7, Page no 496, year 1973.
6.“Oscillating Chemical Reactions”,I.R. Epstein, K.
Kustin, P. DeKepper and M.Orban, Scientific
American, Vol no.248, Page no.112, year 1983.
7.“Physical Chemistry”, G.K.Vemulapalli (1997).
8.Calimente, S.; Strand, S. M.; Chang, S-C.; Lewis, D.
E. J. Chem. Ed. 1999, 76, 82-83.
9.Wagner, A.J.; Miller, S.M.; Naguyen, S.; Lee, G. Y.;
Rychnovsky, S.; Link, R.D. J. Chem. Ed. 2014, 91, 716-
721.
ix Name(s) of Instructor(s) --
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii
Justification/ Need for introducing
the course
Nil
Name of Academic Unit: Computer Science and Engineering
2016 Batch CSE 13
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 101 Computer Programming and Utilization
ii Credit Structure (L-T-P-C) (3-0-2-8)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the Nil
students) – specify course number(s)
vii Course Content This course provides an introduction to problem solving
with computers using a modern language such as Java or
C/C++. Topics covered will include:
Utilization: Developer fundamentals such as editor,
integrated programming environment, Unix shell,
modules, libraries.
Programming features: Machine representation,
primitive types, arrays and records, objects, expressions,
control statements, iteration, procedures, functions, and
basic i/o.
Applications: Sample problems in engineering, science,
text processing, and numerical methods.
viii Texts/References 1. An Introduction to Programming through C++, 1st
edition, by Abhiram G. Ranade, McGraw Hill Education, 2014.
2. C++ Program Design: An introduction to
Programming and Object-Oriented Design, 3rd Edition,
by Cohoon and Davidson, Tata McGraw Hill, 2003. Other references
1. Thinking in C++ 2nd Edition, by Bruce Eckel
(avaiLaboratoryle online).
2. How to Solve It by Computer, by G. Dromey,
Prentice-Hall, Inc., Upper Saddle River, NJ, 1982.
3. How to Solve _It (2nd ed.), by Polya, G., Doubleday
and co, 1957.
4. Let Us C, by Yashwant Kanetkar, Allied Publishers,
1998.
5. The Java Tutorial, Sun Microsystems, Addison-
Wesley, 1999.
ix Name(s) of Instructor(s) --
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
2017 Batch (II SEMESTER)
2016 Batch CSE 14
2016 Batch (SEMESTER II)
Name of Academic Unit: Mathematics
Level: B. Tech.
Programme: B.Tech.
i Title of the course MA 106 Linear Algebra
ii Credit Structure (L-T-P-C) (3-1-0-4)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Course Half
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content Vectors in Rn, notion of linear independence and dependence, linear span of a set of vectors, vector
subspaces of Rn, basis of a vector subspace. Systems of linear equations, matrices and Gauss elimination, row
space, null space, and column space, rank of a matrix.
Determinants and rank of a matrix in terms of
determinants. Abstract vector spaces, linear
transformations, matrix of a linear transformation,
change of basis and similarity, rank-nullity theorem.
Innerproductspaces,Gram-Schmidtprocess,
orthonormal bases, projections and least squares
approximation. Eigenvalues and eigenvectors,
characteristic polynomials, eigenvalues of special matrices
(orthogonal, unitary, hermitian, symmetric, skew-
symmetric, normal). Algebraic and geometric multiplicity,
diagonalization by similarity transformations, spectral
theorem for real symmetric matrices, application to
quadratic forms.
viii Texts/References 1. H. Anton, Elementary linear algebra with applications
(8th Edition), John Wiley (1995).
2. G. Strang, Linear algebra and its applications (4th
Edition), Thomson (2006)
3. S. Kumaresan, Linear algebra - A Geometric
approach, Prentice Hall of India (2000)
4. E. Kreyszig, Advanced engineering mathematics (10th
Edition), John Wiley (1999)
ix Name(s) of Instructor(s) --
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii
Justification/ Need for introducing the
course
This is a fundamental mathematics course which is essential for any branch of engineering
2016 Batch CSE 15
Name of Academic Unit: Mathematics
Level: B. Tech.
Programme: B.Tech.
i Title of the course MA 108 Differential Equations
ii Credit Structure (L-T-P-C) (3-1-0-4)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Course Half
vi Pre-requisite(s), if any (For the Nil
students) – specify course number(s)
vii Course Content
Review of solution methods for first order as well as
second order equations, Power Series methods with
properties of Bessel functions and Legendre
polynomials.Existence and Uniqueness of Initial Value
Problems: Picard`s and Peano`s Theorems, Gronwall`s
inequality, continuation of solutions and maximal interval
of existence, continuous dependence.Higher Order Linear
Equations and linear Systems: fundamental solutions,
Wronskian, variation of constants, matrix exponential
solution, behaviour of solutions.Two Dimensional
Autonomous Systems and Phase Space Analysis: critical
points, proper and improper nodes, spiral points and
saddle points.Asymptotic Behavior: stability (linearized
stability and Lyapunov methods).Boundary Value
Problems for Second Order Equations: Green`s function,
Sturm comparison theorems and oscillations, eigenvalue
problems.
viii Texts/References
M. Hirsch, S. Smale and R. Deveney, Differential Equations,
Dynamical Systems and Introduction to Chaos, Academic Press,
2004L. Perko, Differential Equations and Dynamical Systems,
Texts in Applied Mathematics, Vol. 7, 2nd Edition, Springer
Verlag, New York, 1998. M. Rama Mohana Rao, Ordinary
Differential Equations: Theory and Applications. Affiliated East-
West Press Pvt. Ltd., New Delhi, 1980.D. A. Sanchez, Ordinary
Differential Equations and Stability Theory: An Introduction,
Dover Publ. Inc., New York, 1968.
ix Name(s) of Instructor(s) --
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the This is a fundamental mathematics course which is
course essential for any branch of engineering
2016 Batch CSE 16
Name of Academic Unit: Physics
Level: B.Tech.
Programme: B.Tech.
i Title of the Course PH 108: Electricity and Magnetism
ii Credit Structure (L-T-P-C) (2-1-0-6)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content Review of vector calculus: Spherical polar and
cylindrical coordinates; gradient, divergence and
curl;
Divergence and Stokes` theorems;
Divergence and curl of electric field, Electric
potential, properties of conductors;
Poisson’s and Laplace’s equations, uniqueness
theorems, boundary value problems, separation of
variables, method of images, multipoles;
Polarization and bound charges, Gauss` law in the
presence of dielectrics, Electric displacement D and
boundary conditions, linear dielectrics;
Divergence and curl of magnetic field, Vector
potential and its applications;
Magnetization, bound currents, Ampere`s law in
magnetic materials, Magnetic field H, boundary
conditions, classification of magnetic materials;
Faraday’s law in integral and differential forms,
Motional emf, Energy in magnetic fields,
Displacement current, Maxwell’s equations,
Electromagnetic (EM) waves in vacuum and media,
Energy and momentum of EM waves, Poynting`s
theorem;
Reflection and transmission of EM waves across
linear media.
viii Texts/References (separate sheet may (1) Introduction to Electrodynamics (4th ed.), David J.
be used, if necessary) Griffiths, Prentice Hall, 2015.
(2) Classical Electromagnetism, J. Franklin, Pearson
Education, 2005.
ix Name(s) of Instructor(s) DN/RP
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
2016 Batch CSE 17
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the The course introduces the principles of electricity and
course magnetism. This is a fundamental and necessary
course of physics; which every B. Tech. students have
to undergo at least once.
2016 Batch CSE 18
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 113 Data Structures and Algorithms
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the Exposure to Computer Programming (CS 102)
students) – specify course number(s)
vii Course Content Introduction: data structures, abstract data types,
analysis of algorithms. Creation and manipulation of data structures: arrays,
lists, stacks, queues, trees, heaps, hash tables, balanced
trees, tries, graphs. Algorithms for sorting and searching,
order statistics, depth-first and breadth-first search,
shortest paths and minimum spanning tree.
viii Texts/References 1. Introduction to Algorithms, 3rd edition, by T.
Cormen, C. Leiserson, R. Rivest, C. Stein, MIT Press
and McGraw-Hill, 2009.
2. Data structures and algorithms in C++, by Michael
T. Goodrich, Roberto Tamassia, and David M. Mount,
Wiley, 2004.
ix Name(s) of Instructor(s) SRB
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the Basic course in data structures and algorithms.
course
2016 Batch CSE 19
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 193 Data Structures and Algorithms Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core course
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the Exposure to Computer Programming (CS 102)
students) – specify course number(s)
vii Course Content
Laboratory course for CS 211 is based on creating
and
manipulating various data structures and
implementation of algorithms.
viii Texts/References 1. Introduction to Algorithms, 3rd edition, by T.
Cormen, C. Leiserson, R. Rivest, C. Stein, MIT Press
and McGraw-Hill, 2009.
2. Data structures and algorithms in C++, by Michael T.
Goodrich, Roberto Tamassia, and David M. Mount,
Wiley, 2004.
x Name(s) of Instructor(s) SRB
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the
Basic Laboratory course in data structures and
algorithms.
course
2016 Batch CSE 20
Name of Academic Unit: Mechanical Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the Course ME 119: Engineering Graphics
ii Credit Structure (L-T-P-C) (5-0-5-8)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the Nil
students) – specify course number(s)
vii Course Content
Introduction to engineering drawing and orthographic projections; Projection of points and straight line; Projection of planes and solids; Projection of simple machine elements; Development of surfaces, Intersection of surfaces; Construction of isometric views from orthographic projections. v
viii Texts/References (separate sheet
Bhatt N. D. and Panchal V. M., Engineering Drawing, Charotar Publishers, Anand, 2007. Luzadder Warren J. and Duff Jon M., Fundamentals of Engineering Drawing, Prentice Hall of India, 2001. French Thomas E. and Vierck Charles J., Engineering Drawing and Graphic Technology, McGraw Hill, 1993. Jolhe Dhananjay A., Engineering Drawing, Tata McGraw Hill, 2007. Shah M. B. and Rana B. C., Engineering Drawing, Dorling Kindersley (India) Pvt. Ltd, Pearson Education,
ix Name(s) of Instructor(s) DN/RP
x Name(s) of other Departments/ NA
Academic Units to whom the course
is relevant
xi Is/Are there any course(s) in the No
same/ other academic unit(s) which
is/ are equivalent to this course? If
so, please give details.
xii Justification/ Need for introducing The course introduces to the practical aspects of
the course Mechanics, Electricity & Magnetism, optics, etc.
2016 Batch CSE 21
Name of Academic Unit: Physics
Level: B.Tech.
Programme: B.Tech.
i Title of the Course PH 117: Physics Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the Nil
students) – specify course number(s)
vii Course Content Experiments on
Young’s Modulus by Koenig’s Method
Thermal Conductivity by Lee’s Disc
Helmholts Coils
LCR Circuit
Speific Charge of Electron
Grating Spectrometer
Fresnel’s Bi-Prism
Single Slit Diffraction
viii Texts/References (separate sheet (1) Practical Physics: S. L. Squires, Cambridge University
may be used, if necessary) Press, 2017. (2) Advanced Practical Physics, B. L. Worsnop and H. T. Flint, Littlehampton Book Services Ltd, 1951.
(3) Physics, Vols. 1 & 2, D. Halliday, R. Resnick, and K.
S. Krane, Wiley, 2007, 5th edition. (4) Fundamentals of Optics, F.A. Jenkins and H. E. White,
McGraw Hill Education, 2017, 4th
edition.
ix Name(s) of Instructor(s) DN/RP
x Name(s) of other Departments/ NA
Academic Units to whom the course
is relevant
xi Is/Are there any course(s) in the No
same/ other academic unit(s) which
is/ are equivalent to this course? If
so, please give details.
xii Justification/ Need for introducing The course introduces to the practical aspects of
the course Mechanics, Electricity & Magnetism, optics, etc.
2016 Batch CSE 22
Name of Academic Unit: Biosciences and Bioengineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course BB 101: Biology
ii Credit Structure (L-T-P-C) (3-0-1-7)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the Nil
students) – specify course number(s)
vii Course Content Quantitative views of modern biology. Importance of
illustrations and building quantitative/qualitative models. Role of estimates. Cell size and shape. Temporal scales.
Relative time in Biology. Key model systems – a
glimpse. Management and transformation of energy in
cells. Mathematical view – binding, gene expression and
osmotic pressure as examples. Metabolism. Cell
communication. Genetics. Eukaryotic genomes. Genetic
basis of development. Evolution and diversity. Systems
biology and illustrative examples of applications of
Engineering in Biology.
viii Texts/References 1 Miko, I. & Lejeune, L., eds. Essentials of Genetics.
Cambridge, MA: NPG Education, 2009.O'Connor, C. M. & Adams, J. U. Essentials of Cell Biology.
Cambridge, MA: NPG Education,2010.
2. Watson JD, Baker, TA, Bell SP, Gann A, Levin M,
Losick R, Molecular Biology of the Gene, Pearson
Education, 2004.
3. Dan E. Krane, Michael L. Raymer. Fundamental
Concepts of Bioinformatics, Pearson Education India.
2003
ix Name(s) of Instructor(s) SS
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the To introduce students to modem biology with an
course emphasis on evolution of
biology as a multi-disciplinary field, to make them
aware of application of
engineering principles in biology, and engineering
2016 Batch CSE 23
robust solutions inspired by biological examples. Based on student’s feedback, Laboratory experiments are being added to the course. The addition of laboratory work will change the course structure to
3-0-1-7.
Proposed Laboratory activities:
Before Mid Semester
Biosafety Laboratory practices and biological waste disposal + Buffers in biology, buffering capacity and
pKa
Observing cell surface and intracellular contents using phase contrast microscopy
DNA isolation, PCR, and visualization
Protein isolation and Visualization
After Mid-semester
DNA cloning and transformation
Bacterial growth kinetics
BLAST, BLAT, sequence identification
Gene expression analysis
2016 Batch CSE 24
2016 Batch (SEMESTER III)
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 207 Discrete Structures
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
There are four modules in the course:
1) Proofs and structures
Introduction, propositions, predicates, examples of
theorems and proofs, types of proof techniques,
Axioms, Mathematical Induction, Well-ordering
principle, Strong Induction, Sets, Russell’s paradox,
infinite sets, functions, Countable and uncountable
sets, Cantor’s diagonalization technique, Relations,
Equivalence relations, partitions of a set.
2) Counting and Combinatorics
Permutations, combinations, binomial theorem, pigeon
vii Course Content hole principle, principles of inclusion and exclusion,
double counting. Recurrence relations, solving
recurrence relations.
3) Elements of graph theory
Graph models, representations, connectivity, Euler and
Hamiltonian paths, planar graphs, Trees and tree
traversals.
4) Introduction to abstract algebra and number
theory
Semigroups, monoids, groups, homomorphisms,
normal subgroups, congruence relations. Ceiling, floor
functions, divisibility. Modular arithmetic, prime
numbers, primality theorems.
1. Discrete Mathematics and its applications with
Combinatorics and graph theory, 7th edition, by
Kenneth H Rosen. Special Indian Edition published by
McGraw-Hill Education, 2017.
viii Texts/References 2. Introduction to Graph Theory, 2nd Edition, by
Douglas B West. Eastern Economy Edition published
by PHI Learning Pvt. Ltd, 2002.
3. Discrete Mathematics, 2nd Edition, by Norman L
2016 Batch CSE 25
Biggs. Indian Edition published by Oxford University
Press, 2003.
ix Name(s) of Instructor(s) PRB
Name(s) of other Departments/
x Academic Units to whom the course is NA
relevant
Is/Are there any course(s) in the same/
xi other academic unit(s) which is/ are
No
equivalent to this course? If so, please
give details.
Justification/ Need for introducing
This is a fundamental and core course which forms the
xii foundations for all theory courses in Computer
the course
Science.
2016 Batch CSE 26
Name of Academic Unit: Electrical Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course EE 215 Data Analysis
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be
offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s) --
vii
Course Content
The role of statistics. Graphical and numerical methods
for describing and summarising data. Probability.
Population distributions. Sampling variability and
sampling distributions. Estimation using a single
sample. Hypothesis testing a single sample. Comparing
two populations or treatments. Simple linear regression
and correlation. Case studies.
viii
Texts/References
1. Introduction to Probability and Statistics for
Engineers and Scientists by Sheldon M. Ross, Elsevier,
New Delhi, 3rd edition (Indian), 2014.
2. Probability, Random Variables and Stochastic
processes by Papoulis and Pillai, 4th Edition, Tata
McGraw Hill, 2002.
3. An Introduction to Probability Theory and Its
Applications, Vol. 1, William Feller, 3rd edition, Wiley
International, 1968.
ix Name(s) of Instructor(s) SRMP
x
Name(s) of other Departments/
Academic Units to whom the course is
relevant
CSE & ME
xi
Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii
Justification/ Need for introducing
the course
Analyzing data and interpreting results are integral part
of almost every research and it finds extensive use in
industry as well. From Machine learning to Finance, its
applications are enormous.
2016 Batch CSE 27
Name of Academic Unit: Humanities and Social Sciences
Level: B.Tech.
Programme: B.Tech.
i Title of the course HS 101 Economics
ii Credit Structure (L-T-P-C) (2-1-0-6)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester
Full
Course
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
Basic economic problems. resource constraints and
Welfare maximizations. Nature of Economics: Positive
and normative economics; Micro and macroeconomics,
Basic concepts in economics. The role of the State in
economic activity; market and government failures;
New Economic Policy in India. Theory of utility and
consumer’s choice. Theories of demand, supply and
market equilibrium. Theories of firm, production and
vii Course Content costs. Market structures. Perfect and imperfect
competition, oligopoly, monopoly. An overview of
macroeconomics, measurement and determination of
national income. Consumption, savings, and
investments. Commercial and central banking.
Relationship between money, output and prices.
Inflation - causes, consequences and remedies.
International trade, foreign exchange and balance
payments, stabilization policies : Monetary, Fiscal and
Exchange rate policies.
1. P. A. Samuelson & W. D. nordhaus, Economics,
McGraw Hill, NY, 1995.
2. A. Koutsoyiannis, Modern Microeconomics,
Macmillan, 1975. R. Pindyck and D. L. Rubinfeld,
Microeconomics, Macmillan publishing company, NY,
1989.
3. R. J. Gordon, Macroeconomics 4th edition, Little
viii Texts/References Brown and Co., Boston, 1987.
4. William F. Shughart II, The Organization of Industry,
Richard D. Irwin, Illinois, 1990.
5. R.S. Pindyck and D.L. Rubinfeld. Microeconomics
(7th
Edition), Pearson Prentice Hall, New Jersey, 2009.
6. R. Dornbusch, S. Fischer, and R. Startz.
Macroeconomics (9th Edition), McGraw-Hill Inc. New
York, 2004.
ix Name(s) of Instructor(s) --
2016 Batch CSE 28
Name(s) of other Departments/
x Academic Units to whom the course is CSE, EE & ME
relevant
Is/Are there any course(s) in the
xi same/ other academic unit(s) which is/ No
are equivalent to this course? If so,
please give details.
xii Justification/ Need for introducing This course is a basic course on economics and useful
the course for all students of B.Tech.
2016 Batch CSE 29
Name of Academic Unit: Electrical Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course EE 101: Introduction to Electrical and
Electronics Circuits
ii Credit Structure (L-T-P-C) (0-0-3-8)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the Exposure to calculus (MA 101)
students) – specify course number(s)
vii Course Content From Physics to Electrical Engineering
(a) Lumped matter discipline
(b) Batteries, resistors, current sources and basic laws
(c) I-V characteristics and modeling physical systems
Basic Circuit Analysis Methods
(a) KCL and KVL, voltage and current dividers
(b) Parallel and serial resistive circuits
(c) More complicated circuits
(d) Dependent sources, and the node method
(e) Superposition principle
(f) Thevenin and Norton method of solving linear circuits
(g) Circuits involving diode.
Analysis of Non-linear Circuits
(a) Toy example of non-linear circuit and its analysis
(b) Incremental analysis
(c) Introduction to MOSFET Amplifiers
(d) Large and small signal analysis of MOSFETs
(e) MOSFET as a switch
Introduction to the Digital World
(a) Voltage level and static discipline
(b) Boolean logic and combinational gates
(c) MOSFET devices and the S Model
(d) MOSFET as a switch; revisited
(e) The SR model of MOSFETs
(f) Non-linearities: A snapshot
Capacitors and Inductors
(a) Behavior of capacitors, inductors and its linearity
(b) Basic RC and RLC circuits
(c) Modeling MOSFET anomalies using capacitors
(d) RLC circuit and its analysis
(e) Sinusoidal steady state analysis
(f) Introduction to passive filters
Operational Amplifier Abstraction
(a) Introduction to Operational Amplifier
(b) Analysis of Operational amplifier circuits
(c) Op-Amp as active filters
2016 Batch CSE 30
Page 25 of 126
(d) Introduction to active filter design
Transformers and Motors
(a) AC Power circuit analysis
(b) Polyphase circuits
(c) Introduction to transformers
(d) Introduction to motors
viii Texts/References 1. Anant Agarwal and Jefferey H. Lang, “Foundations of
Analog and Digital Electronics Circuits,” Morgan
Kaufmann publishers, 2005
2. Wlilliam H. Hayt, Jr., Jack E. Kemmerly and Steven
M. Durbin, “Engineering Circuit Analysis,” Tata
McGraw-Hill
3. Theodore Wildi, “Electrical Machines, Drives and
Power Systems,” Pearson, 6-th edition. 4. V. Del. Toro, “Electrical Engineering Fundamentals,”
Pearson publications, 2nd
edition.
ix Name(s) of Instructor(s) BBN
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the To introduce students to basics of electrical
course engineering.
EE102 Laboratory Component
• Typical experiments covered
1. I-V characteristics of two terminal electronic components (diode, temperature sensor etc.) + introduction to operating point using non-linear devices such as diode. 2. Characteristics of MOSFET
– MOSFET as amplifiers
– MOSFET as a switch
3. Realization of basic logical circuits using MOSFET switch. 4. Transfer function of circuits involving R, L and C components + passive filters using R, L and C elements. 5. Feedback systems + operational amplifier based circuit design. 6. Active and reactive power calculations.
2016 Batch CSE 31
Name of Academic Unit: Computer Science and Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course CS 251 Software Systems Laboratory
ii Credit Structure (L-T-P-C) (1-3-0-8)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
Vim/emacs HTML, CSS
2. Report and presentation software: latex, beamer,
drawing software (e.g. inkscape, xfig, open-office)
3. IDE (e.g. eclipse, netbeans), code reading,
debugging Basic Java Java collections, interfaces
4. Java threads Java GUI Introduction to
documentation: e.g. doxygen/javadocs
5. Version management: SVN/Git
6. Unix basics: shell, file system, permissions, process
hierarchy, process monitoring, ssh, rsync
7. Unix tools: e.g. awk, sed, grep, find, head, tail, tar,
vii Course Content cut, sort
8. Bash scripting: I/O redirection, pipes
9. Python programming
10. Makefile, libraries and linking
11. Graph plotting software (e.g., gnuplot)
12. Profiling tools (e.g., gprof, prof)
13. Optional topics (may be specific to individual
students302222 projects): intro to sockets, basic SQL
for data storage,JDBC/pygresql
A project would be included which touches upon many
of the above topics, helping students see the connect
across seemingly disparate topics. The project is also
expected to be a significant load: 20-30 hours of work.
1. Online tutorials for HTML/CSS, Inkscape,
OODrawUnix Man Pages for all unix tools, Advanced
Bash Scripting Guide from the Linux Documentation
Project (www.tldp.org).
viii Texts/References 2. The Python Tutorial Online Book
(http://docs.python.org/3/tutorial/index.html).
3. The Java Tutorials
(http://docs.oracle.com/javase/tutorial/).
4. Latex - A document preparation system, 2/e, by
Leslie Lamport, Addison-Wesley, 1994.
ix Name(s) of Instructor(s) PRB, RK, SRB
Name(s) of other Departments/
x Academic Units to whom the course is NA
relevant
2016 Batch CSE 32
Is/Are there any course(s) in the same/
xi other academic unit(s) which is/ are
No
equivalent to this course? If so, please
give details.
Justification/ Need for introducing
This is a fundamental and core course which trains
xii students on different programming platforms, as well as
the course
on basic software engineering principles.
2016 Batch CSE 33
2016 Batch (SEMESTER IV)
Name of Academic Unit: Computer Science and Engineering
Level: UG Programme: B.Tech.
i Title of the course CS 310 Automata Theory
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be Spring
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the Exposure to Discrete Structures
students) – specify course
number(s)
vii Course Content Finite state machines (DFA/NFA/epsilon NFAs), regular
expressions. Properties of regular languages. My hill-
Nerode Theorem. Non-regularity. Push down automata.
Properties of context-free languages. Turing
machines:Turing hypothesis, Turing computability,
Nondeterministic, multi tape and other versions of Turing
machines. Church`s thesis, recursively enumerable sets and
Turing computability. Universal Turing machines.
Unsolvability, The halting problem, partial solvability,
Turing enumerability, acceptability and decidability,
unsolvable problems about Turing Machines. Post`s
correspondence problem.
Viii Texts/References 1. Introduction to Automata Theory, Languages and
Computation, by John. E. Hopcroft, Rajeev Motwani, J. D.
Ullman, 3rd edition. Pearson. 2013.
2. Elements of the Theory of Computation, by H.R. Lewis
and C.H.Papadimitrou, 2nd Edition. Prentice Hall Inc,
1998.
x Name(s) of Instructor(s) GN
x Name(s) of other Departments/ Nil
Academic Units to whom the
course is relevant
xi Is/Are there any course(s) in the No
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
xii Justification/ Need for Fundamental course on computability.
introducing the course
2016 Batch CSE 34
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 348 Computer Networks
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be
Spring
offered
v Whether Full or
Full
Half Semester Course
Pre-requisite(s), if any (For the
vi students) – specify course Nil
number(s)
Design of Computer Networking protocols at all layers:
transmission media, data link protocols, media access
vii Course Content* control, routing and congestion control, admission
control, traffic shaping and policing, Internet working
(IP) and transport layer protocols (TCP). Performance
analysis of networks.
1. Data and Computer Communications, 6th edition, by
W. Stallings, Prentice Hall, 2000.
2. Computer Networks, 4th edition, by A. S.
Tannenbaum, Prentice Hall, 2003.
3. Data Communications, Computer Networks and
Open Systems, 4th edition, by F. Halsall, Addison-
viii Texts/References Wesley, 1996.
4. High Performance Communication Networks, by
Walrand and Varaiya, Morgan Kaufman, 1996.
5. Internet working with TCP/IP: Principles, Protocols,
Architecture, 3rd edition, by D. E. Comer, Prentice
Hall, 1996.
6. TCP/IP Illustrated Vol. I, by W. R. Stevens, Addison
Wesley, 1994.
ix Name(s) of Instructor(s) BR
Name(s) of other Departments/ Electrical Engineering
x Academic Units to whom the
course is relevant
Is/Are there any course(s) in the
xi same/ other academic unit(s)
No
which is/ are equivalent to this
course? If so, please give details.
xii Justification/ Need for
Fundamental course on computer networks.
introducing the course
2016 Batch CSE 35
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 218 Design and Analysis of Algorithms
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to Spring
be offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the Computer Programming and Utilization, Discrete Structures, students) – specify course Data Structures and Algorithms , Data Structures and
number(s) Algorithms Laboratory
vii Course Content*
Syl Laboratory is divided roughly 8 modules; each module roughly
takes two weeks.
Module 1: Introduction Examples and motivation.
Asymptotic complexity: informal concepts, formal notation,
examples
Module 2: Searching in list: binary search, Sorting: insertion
sort, selection sort, merge sort, quicksort, stability and other
issues.
Module 3: Divide and conquer: binary search, recurrence
relations. nearest pair of points, merge sort, integer
multiplication, matrix multiplication.
Module 4: Graphs: Motivation, BFS, DFS, DFS numbering
and applications, directed acyclic graphs, directed acyclic
graphs, Shortest paths: unweighted and weighted, Single
source shortest paths: Dijkstra, Minimum cost spanning
trees: Prim’s algorithm, Kruskal’s Algorithm
Module 5: Union-Find data structure, Priority queues, heaps.
Heap sort. Dijstra/Prims revisited using heaps, Search Trees:
Introduction Traversals, insertions, deletions Balancing
Module 6: Greedy algorithms: Greedy: Interval scheduling,
Proof strategies, Huffman coding.
Module 7: Dynamic Programming: weighted interval
scheduling, memoization, edit distance, longest ascending
subsequence. matrix multiplication, shortest paths: Bellman
Ford, shortest paths: Floyd Warshall
Module 8: Intractability: NP completeness, reductions,
examples, Misc topics.
viii Texts/References 1. Algorithms, by Sanjoy Dasgupta, Christos Papadimitriou
and Umesh Vazirani, McGraw Hill Education, 2006. 2. Introduction to Algorithms, 3rd edition, by Cormen,
Leiserson, Rivest and Stein, PHI Learning Pvt. Ltd., 2010.
3. Algorithm Design, 1st edition, by Kleniberg and Tardos,
Pearson, 2014.
ix Name(s) of Instructor(s) PRB
2016 Batch CSE 36
x Name(s) of other Departments/ Nil
Academic Units to whom the
course is relevant
xi Is/Are there any course(s) in the No
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
xii Justification/ Need for Core Course for Computer Science undergraduate students.
introducing the course
2016 Batch CSE 37
Name of Academic Unit: Electrical Engineering
Level: UG
Programme: B.Tech.
i Title of the course EE 204 Digital Systems
ii Credit Structure (L-T-P-C) (2-1-0-6)
iii Type of Course Core course
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) specify course number(s)
None
vii Course Content • Introduction to Digital Systems
• Number systems and Logic: Number Systems,
Different Codes, Boolean logic, basic gates, truth tables
• Introduction to Logic families: TTL, CMOS etc.
• Boolean Algebra: Laws of Boolean Algebra, logic
minimization using K maps
• Combinational Logic Circuits: Adders, Subtractors,
Multipliers, MSI components like Comparators,
Decoders, Encoders, MUXs, DEMUXs
• Sequential circuits: Latches, Flipflops, Analysis of
clocked sequential circuits, Registers and Counters
(Synchronous and Asynchronous), State Machines
• Introduction to Hardware Description
Languages
• Array based logic elements: Memory, PLA, PLD,
FPGA
• Special Topics: Asynchronous State machines, Testing
and Verification of Digital Systems
viii Texts/References 1. J. F. Wakerly: Digital Design, Principles and
Practices,4th Edition,Pearson Education, 2005
2. M. Moris Mano; Digital Design, 4th Edition,
Pearson,2009
3. Ronald J. Tocci; Digital System, Principles and
Applications, 10th Edition, Pearson, 2009
4. H.Taub and D. Schilling; Digital Integrated
Electronics, McGraw Hill, 1977
5. Charles H Roth; Digital Systems Design using VHDL,
Thomson Learning, 1998
ix Name(s) of Instructor(s) RG
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
Computer Science Engineering
xi Is/Are there any course(s) in the
same/ other academic unit(s) which
No
2016 Batch CSE 38
is/ are equivalent to this course? If
so, please give details.
xii Justification/ Need for introducing
the course
This course introduces students to the world of Digital
Systems by introducing concept of Boolean Algebra and
Logic Functions. This course is a beginning of the spine
related to Digital Design, Microprocessor, Embedded
Systems etc,
2016 Batch CSE 39
Name of Academic Unit: Mathematics
Level: UG
Programme: B. Tech.
i Title of the course MA 214 Numerical Analysis
ii Credit Structure (L-T-P-C) ((3-1-0-8)
iii Type of Course Core course for CSE & ME
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the Calculus (MA 101), Linear Algebra (MA 102),
students) – specify course number(s) Differential Equations I (MA 104)
vii Course Content Interpolation by polynomials, divided differences,
error of the interpolating polynomial, piecewise
linear and cubic spline interpolation. Numerical
integration, composite rules, error formulae. Solution
of a system of linear equations, implementation of
Gaussian elimination and Gauss-seidel methods,
partial pivoting, row echelon form, LU factorization
Cholesky's method, ill-conditioning, norms. Solution
of a nonlinear equation, bisection andsecant methods.
Newton's method, rate of convergence, solution of a
system of nonlinear equations, numerical solution of
ordinary differential equations, Euler and Runge-
Kutta methods, multi-step methods, predictor-
corrector methods, order of convergence, nite
dierence methods, numerical solutions of elliptic,
parabolic, and hyperbolic partial differential
equations. Eigenvalue problem, power method, QR
method, Gershgorin's theorem.
viii Texts/References 1. S. D. Conte and Carl de Boor, Elementary
Numerical Analysis- An Algorithmic Approach
(3rd Edition), McGraw-Hill, (1980)
2. C. E. Froberg, Introduction to Numerical Analysis
(2nd Edition), Addison-Wesley (1981)
3. David Kincaid and Ward Cheney, Numerical
Analysis: Mathematics of Scientific Computing
(2002)
4. E. Kreyszig, Advanced engineering mathematics
(8th Edition), John Wiley (1999)
ix Name(s) of Instructor(s) AB
x Name(s) of other Departments/ CSE, ME
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
17
2016 Batch CSE 40
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the Numerical Analysis is needed for different branches
course of science and engineering for solving problems
which generally have no closed form solutions
2016 Batch CSE 41
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 212 Computer Networks Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core course
iv Semester in which normally to be
Spring
offered
v Whether Full or Half Semester
Full
Course
Pre-requisite(s), if any (For the
vi students) – specify course Nil
number(s)
Experiments to support study of the Internet protocol
stack: (a) Experimental study of application protocols
such as HTTP, FTP, SMTP, using network packet
sniffers and analyzers such as Ethereal. Small exercises
in socket programming in C/C++/Java. (b) Experiments
with packet sniffers to study the TCP protocol. Using
OS (netstat, etc) tools to understand TCP protocol FSM,
vii Course Content retransmission timer behavior, congestion control
behaviour. (c) Introduction to ns2 (network simulator) -
small simulation exercises to study TCP behavior under
different scenarios. (d) Setting up a small IP network -
configure interfaces, IP addresses and routing protocols
to set up a small IP network. Study dynamic behaviour
using packet sniffers (e) Experiments with ns2 to study
behaviour (especially performance of) link layer
protocols such as Ethernet and 802.11 wireless LAN.
viii Texts/References Nil
ix Name(s) of Instructor(s) BR
Name(s) of other Departments/
x Academic Units to whom the Electrical Engineering
course is relevant
Is/Are there any course(s) in the
xi same/ other academic unit(s)
No
which is/ are equivalent to this
course? If so, please give details.
xii Justification/ Need for
Fundamental Laboratory course on computer networks.
introducing the course
2016 Batch CSE 42
Name of Academic Unit: Electrical Engineering
Level: B. Tech
Programme: B. Tech.
i Title of the
course
EE214: Digital Circuits Laboratory
ii Credit Structure
(L-T-P-C)
(0 -0- 3- 3)
iii Type of Course Core course
iv Semester in
which normally
to be offered
Autumn
v Whether Full or
Half Semester
Course
Full
vi Pre-requisite(s),
if any (For the
students) –
specify course
number(s)
Digital Systems Theory (EE224)
Vii Course Content* This purpose of this lab is to complement the Digital Systems
Theory Course. The following is the tentative list of
experiments for this lab:
Experiments with discrete ICs
1. Introduction of digital ICs
2. Realizing Boolean expressions
3. Adder/Subtractor
4. Shift registers
5. Synchronous Counters
6. Asynchronous Counters + 7-segment display
7. Finite State Machines (2 weeks)
Experiments with CPLDs
8. Arithmetic and Logic Unit
9. LCD, Buzzer Interfacing
10. Pipelining
Viii Texts/References 1. M. Moris Mano; Digital Design, 5th Edition, Pearson,
2009
2. J.F.Wakerly: Digital Design, Principles and Practices,4th
Edition,Pearson Education, 2005
3. Ronald J. Tocci; Digital System, Principles and
Applications, 10th Edition, Pearson, 2009
Ix Name(s) of
Instructor(s) ***
RG
2016 Batch CSE 43
x Name(s) of other
Departments/
Academic Units
to whom the
course is relevant
Computer Science
xi Is/Are there any
course(s) in the
same/ other
academic unit(s)
which is/ are
equivalent to this
course? If so,
please give
details.
No
xii Justification/
Need for
introducing the
course
The lab deals with fundamental digital circuits which are
extensively used in electronic gadgets.
2016 Batch CSE 44
2016 Batch (SEMESTER V)
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 301 Computer Architecture
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
The Language of Bits, Assembly Language, Logic
Gates, Registers, and Memories, Processor Design,
Principles of Pipelining, The Memory System,
vii Course Content Multiprocessor Systems, I/O and Storage Devices.
Each concept will be first taught on the basis of the
fundamental driving principles. Following this, real
world examples (e.g., ARM processors) will be used to
emphasize the content.
1. Computer Organization and Architecture, by Smruti
Ranjan Sarangi, McGraw Higher Ed, 2017.
viii Texts/References 2. Computer Architecture A Quantitative Approach,
Sixth edition, by David Patterson and John L. Hennesy,
Morgan Kaufmann, 2017.
ix Name(s) of Instructor(s) RK
Name(s) of other Departments/
x Academic Units to whom the course is EE
relevant
Is/Are there any course(s) in the same/
xi other academic unit(s) which is/ are
No
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing This course deals with the fundamentals of how a
the course programmable computer functions.
2016 Batch CSE 45
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 303 Data Bases and Information Systems
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
Overview of data management systems. Relational
model and query languages (relational algebra and
calculus, SQL). Database design using the ER Model,
ER Diagrams, UML Class Diagrams. Relational
database design and normalization. Integrity and
Security. Design and development of Web based
information systems. Overview of storage structures
and indexing, query processing and optimization, and
vii Course Content transaction processing. Introduction to Big Data
management concepts such as: distributed and scalable
data storage, including distributed file systems, key
value stores, column stores and graph databases,
replication and consistency, and concurrent data
processing using the Map Reduce paradigm.
Introduction to decision support and data analysis, data
warehousing and data mining, and Information
Retrieval.
1. Database System Concepts, 6th edition, by Abraham
viii Texts/References Silberschatz, Henry F. Korth and S. Sudarshan,
McGraw Hill, 2010.
ix Name(s) of Instructor(s) --
Name(s) of other Departments/
x Academic Units to whom the course is NA
relevant
Is/Are there any course(s) in the same/
xi other academic unit(s) which is/ are
No
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing
Fundamental course on Databases
the course
2016 Batch CSE 46
Name of Academic Unit: Computer Science and Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course CS 305 Graph Theory and Combinatorics
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the Exposure to Discrete Structures (CS 203)
students) – specify course number(s)
vii Course Content Fundamentals of graph theory. Topics include:
connectivity, planarity, perfect graphs, coloring, matchings and extremal problems.
Basic concepts in Combinatorics. Topics include:
counting techniques, inclusion-exclusion principles,
permutations, combinations and pigeon-hole principle.
viii Texts/References 1. D. B. West, ``Introduction to Graph Theory" 2nd
edition. Prentice Hall.
2. Martin C. Golumbic, ``Algorithmic Graph Theory
and Perfect Graphs." 2nd
edition.
3. R. Diestel, ``Graph Theory", 5th
edition.
ix Name(s) of Instructor(s) --
x Name(s) of other Departments/ NA
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the Graph Theory and Combinatorics have applications in
course many areas in computer science and electrical engineering. This is considered an essential course for
those who want to explore further on theoretical
computer science.
2016 Batch CSE 47
Name of Academic Unit: Electrical Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course EE 305 Digital Signal Processing
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the --
students) – specify course number(s)
vii Course Content Discrete time signals: Sequences, representation of
signals on orthogonal basis, Sampling and reconstruction
of signals, Discrete systems: attributes, Z-Transform,
Analysis of LSI systems, Frequency analysis, Inverse
Systems, Discrete Fourier Transform (DFT), Fast Fourier
Transform algorithm, Implementation of Discrete Time
Systems. Design of FIR Digital filters: Window method,
Park-McClellan's method. Design of IIR Digital Filters:
Butterworth, Chebyshev and Elliptic Approximations,
Lowpass, Bandpass, Bandstop and High pass filters.
Effect of finite register length in FIR filter design.
Parametric and non-parametric spectral estimation.
Introduction to multirate signal processing. Application
of DSP to Speech and Radar signal processing.
Assignments and course projects based on MATLAB and
ARM based digital signal processing lab.
viii Texts/References 1. A.V. Oppenheim and Schafer, Discrete Time Signal
Processing, Prentice Hall, 1989. 2. John G. Proakis and D.G. Manolakis, Digital Signal
Processing: Principles, Algorithms and Applications,
Prentice Hall, 1997.
3. L.R. Rabiner and B. Gold, Theory and Application of
Digital Signal Processing, Prentice Hall, 1992.
4.J.R. Johnson, Introduction to Digital Signal Processing,
Prentice Hall, 1992.
5. J. DeFatta, J. G. Lucas and W. S. Hodgkiss, Digital
Signal Processing, J Wiley and Sons, Singapore, 1988.
ix Name(s) of Instructor(s) SRMP
x Name(s) of other Departments/ CSE
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
2016 Batch CSE 48
give details.
xii Justification/ Need for introducing the This is foundation course in digital signal processing and
course essential for all electrical engineers. The course can be
offered as an elective course for the computer science and
engineering students also.
2016 Batch CSE 49
Name of Academic Unit: Electrical Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course EE 307 Probability and Random Process
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core course for EE and electives for CS
iv Semester in which normally to be Autumn
offered
v Whether Full or Half Semester Full
Course
vi Pre-requisite(s), if any (For the Exposure to Calculus (MA 101)
students) – specify course number(s)
vii Course Content Introduction: Motivation for studying the course,
revision of basic math required, connection between
probability and length on subsets of real line, probability-
formaldefinition,eventsandsigma-algebra,
independence of events, and conditional probability,
sequence of events, and Borel-Cantell Lemma.
Random Variables: Definition of random variables, and
types of random variables, CDF, PDF and its properties,
examples of random variables, random vectors and
independence, brief introduction to transformation of
random variables, introduction to Gaussian random
vectors
Mathematical Expectation: Importance of averages
through examples, definition of expectation, moments
and conditional expectation, use of MGF, PGF and
characteristic functions, variance and k-th moment.
Inequalities and Notions of convergence: Markov,
Chebychev, Chernoff and Mcdiarmid inequalities,
convergence in probability, mean, and almost sure.
Random Process: Example and formal definition,
stationarity, autocorrelation, and cross correlation
function, ergodicity, KL expansion, introduction to
special random process such as Markov chains, Martinagale and Brownian motion.
Markov Chain: Communication classes and its
properties, stationary distribution and its existence,
Poisson processes, Example applications of Markov
decision process. Applications of the tools discussed in
the course in electrical engineering and computer science
2016 Batch CSE 50
viii Texts/References 1. Robert B. Ash, ``Basic Probability Theory," Reprint of
the John Wiley & Sons, Inc., New York, 1970 edition. 2. Sheldon Ross, ``A first course in probability," Pearson
Education India, 2002.
3. Bruce Hayek, ``An Exploration of Random Processes
for Engineers," Lecture notes.
ix Name(s) of Instructor(s) BBN
x Name(s) of other Departments/ CSE
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the "Randomness" is inherent to most of the systems in
course electrical engineering. Especially, in the field of
communication, the noise at the receiver brings in several challenges in designing systems that are immune to noise.
To face this challenge, it is fundamental to model and
understand the “randomness.” This course is aimed at
covering tools necessary to achieve this goal through
several example applications in electrical and computer
science engineering disciplines.
2016 Batch CSE 51
Name of Academic Unit: Mathematics
Level: B.Tech.
Programme: B.Tech.
I Title of the course MA 301 Elementary Algebra and number theory
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Offered to 5th
semester Computer Science and
Engineering
iv Semester in which normally to be Autumn
offered
V Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the Some knowledge of discrete structures, would help but
students) – specify course number(s) is not essential
vii Course Content Groups, subgroups, normal subgroups and quotient
groups; homomorphism theorems; Symmetric and
alternating groups; Group actions, Sylow theorems and
applications. Rings; subrings, ideals, factor rings,
polynomial rings, discriminents. Fields, algebraic and
transcendental extensions, Separable and normal
extensions, Statement of Galois theorem, Finite fields.
Congruence relations in integers; Chinese reminder
theorem; quadratic reciprocity law, cyclotomic
polynomials
viii Texts/References 1. D.S. Dummit and R.S. Foote, Abstract Algebra, John
Wiley (Asian reprint 2003)
2. M.Artin, Algebra, Prentice Hall (2011), paperback
Indian edition is available.
3. N.Jacobson, Basic Algebra vol I, W.H. Freeman and
Co (1985) paperback Indian edition is available.
4. J.H.Siverman, A friendly introduction to number
theory, Second edition,Prentice (2005)
5. K.Ireland and M.Rosen, A classical introduction to
modern number theory, Second edition, Springer (Indian
edition available).
ix Name(s) of Instructor(s) NSNS
x Name(s) of other Departments/ Nil
Academic Units to whom the course is
relevant
xi Is/Are there any course(s) in the same/ No
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the Knowledge of this course is required in many areas of
course Computer Science and Engineering
2016 Batch CSE 52
Name of Academic Unit: Humanities and Social Sciences
Level: B. Tech.
Programme: B.Tech.
i Title of the course HS 301: Philosophy
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Core – Humanities
iv Semester in which normally to be
offered
1
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
None
vii Course Content 1. What is Philosophy? (Philosophy in India and
West)
2. Main Branches of Philosophy
3. Three Laws of Thought
4. Epistemology and Logic (Indian and Western)
5. Metaphysics (Universal and Particular, Substance
and Attributes, Causality, Space, Time, Soul, God,
Freedom)
6. Three Great Greek Philosophers: Socrates, Plato
and Aristotle
7. Modern Philosophy: Rationalism and Empiricism
(Descartes, Locke, Berkeley and Hume)
8. Ethics (Utilitarianism, Categorical Imperative of
Kant, Ethical Relativism, Bio-Medical Ethics,
Ethical Issues)
9. Indian Philosophy Component (Nishkama-karma
of Gita, Virtue Ethics of Buddhism, Advaita
Vedanta).
10. Meaning of Life.
viii Texts/References 1. Ganeri, Jonardon, Philosophy in Classical India:
An Introduction and Analysis (London: Routledge,
2001).
2. Maritain, Jacques, An Introduction of Philosophy
(New York and Oxford: Rowman & Littlefield,
2005).
3. Mohanty, J. N. Classical Indian Philosophy: An
Introductory Text (New York and Oxford: Rowman
& Littlefield, 2000).
4. Nagel, Thomas, What Does It All Mean? A Short
Introduction to Philosophy (Oxford: Oxford
University Press, 2004).
5. Russel, Bertrand, The Problems of Philosophy
(Oxford: Oxford University Press, Reprint by Kalpaz
Publication, 2017).
6. Sharma, Chandradhar, A Critical Survey of Indian
Philosophy (Delhi: Motilal Banarsidass, 2016).
2016 Batch CSE 53
7. Thilly, Frank, A History of Philosophy (New Delhi:
SBW Publishers, 2018).
8. Williams, Bernard, Morality: An Introduction to
Ethics (Cambridge: Cambridge University Press,
2012).
ix Name(s) of Instructor(s) C. D. Sebastian
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
All
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
HS 301 is a unique course that aims to provide the
BTech students an understanding of philosophy and
history of ideas. Through this course they are
expected to develop philosophical analysis and
critical thinking which will enhance their engineering
imagination as a skill and profession with the training
in epistemology, logic, philosophical speculation and
creativity. The ethics-module of the course will help
them to think and act ethically in their profession with
relation to the societal expectations of their fellow
humans in India.
2016 Batch CSE 54
Name of Academic Unit: Humanities and Social Sciences
Level: B.Tech.
Programme: B.Tech.
i Title of the course HS 303 Introduction to Literature
ii Credit Structure (L-T-P-C) (3-1-0-6)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester
Full
Course
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
vii Course Content
What is Literature, Genres of Literature, Literary Texts
and Contexts, Major Themes in Literature
viii Texts/ References
Glossary of Literary Terms by MH Abrams, The Norton
Anthology of Poetry edited by Margaret Ferguson,
Animal Farm by George Orwell, The Penguin Book of
Modern Indian Short Stories- Stephen Alter, Oxford
Book of English Short Stories Reissue Edition (English,
Paperback, A. S. BYATT), Three Theban Plays:
Antigone; Oedipus the King; Oedipus at Colonus
(English, Paperback, Sophocles)
ix Name(s) of Instructor(s) Prof. Ridhima Tewari
xii Justification/ Need for introducing the
course
The course is aimed at introducing students to literature-
its reading and appreciation, and its relation to
contemporary world, knowledge systems and contexts.
2016 Batch CSE 55
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 311 Computer Architecture Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester
Full
Course
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
The lab will closely follow the theory course. The idea is
to have the students develop a software model of a simple
vii Course Content processor, capturing both functionality and timing
aspects. They will implement modules as the concepts are
taught in class.
viii Texts/References Nil
ix Name(s) of Instructor(s) RK
Name(s) of other Departments/
x Academic Units to whom the course EE
is relevant
Is/Are there any course(s) in the
xi same/ other academic unit(s) which
No
is/ are equivalent to this course? If
so, please give details.
xii Justification/ Need for introducing
Fundamental lab course on computer architecture.
the course
2016 Batch CSE 56
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course CS 313 Data Bases and Information Systems Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core course
iv Semester in which normally to be
Autumn
offered
v Whether Full or Half Semester
Full
Course
vi Pre-requisite(s), if any (For the
--
students) – specify course number(s)
Use of database systems supporting interactive SQL.
Two-tier client-server applications using JDBC or ODBC,
Three-tier web applications using Java servlets/JDBC or
vii Course Content equivalent. Design of applications and user interfaces
using these systems. Data analysis tools. Laboratory
project involving building data backed applications with
Web or mobile app frontends.
1. Abraham Silberschatz, Henry F. Korth and S.
viii Texts/References Sudarshan, Database System Concepts 6th Ed, McGraw
Hill, 2010.
ix Name(s) of Instructor(s) --
Name(s) of other Departments/
x Academic Units to whom the course NA
is relevant
Is/Are there any course(s) in the
xi same/ other academic unit(s) which
No
is/ are equivalent to this course? If so,
please give details.
xii Justification/ Need for introducing
Fundamental lab course on Databases
the course
2016 Batch CSE 57
2016 Batch (SEMESTER VI)
SEMESTER VI – Computer Science
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 302 Artificial Intelligence
ii Credit Structure (L-T-P-C) (3-0-0- 6)
iii Type of Course Core
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
vii Course Content Search: Problem representation; State Space Search; A*
Algorithm and its Properties; AO* search, Minimax and
alpha-beta pruning, AI in games. Logic: Formal Systems;
Notion of Proof, Decidability, Soundness, Consistency and
Completeness; Predicate Calculus (PC), Resolution
Refutation, Herbrand Interpretation, Prolog. Knowledge
Representation: PC based Knowledge Representation,
Intelligent Question Answering, Semantic Net, Frames,
Script, Conceptual Dependency, Ontologies, Basics of
Semantic Web. Leaning: Learning from Examples, Decision
Trees, Neural Nets, Hidden Markov Models, Reinforcement
Learning, Learnability Theory. Uncertainty: Formal and
Empirical approaches including Bayesian Theory, Fuzzy
Logic, Non-monotonic Logic, Default Reasoning. Planning:
Blocks World, STRIPS, Constraint Satisfaction, Basics of
Probabilistic Planning. Advanced Topics: Introduction to
topics like Computer Vision, Expert Systems, Natural
Language Processing, Big data, Neuro Computing, Robotics,
Web Search.
viii Texts/References Main Text:
1. Stuart J. Russel, Peter Norvig, Artificial Intelligence: A
Modern Approach (3rd ed.). Upper Saddle River: Prentice
Hall, 2010.
Other references:
1. N.J. Nilsson, Principles of Artificial Intelligence, Morgan
Kaufmann, 1985.
2. Malik Ghallab, Dana Nau, Paolo Traverso, Automated
Planning: Theory & Practice, The Morgan Kaufmann Series
in Artificial Intelligence, 2004.
3. Christopher Bishop, Pattern Recognition and Machine
Learning, Springer, 2006.
4. Mark Stefik, Introduction to Knowledge Systems, Morgan
Kaufmann, 1995. E. Rich and K. Knight, Artificial
Intelligence, Tata McGraw Hill, 1992.
ix Name(s) of Instructor(s) -
2016 Batch CSE 58
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
No
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
x Justification AI is taught traditionally as it is driving force behind many
concepts in computer science and it is also precursor to
advanced courses like machine learning.
2016 Batch CSE 59
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 304 Operating Systems
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core
iv Semester in which normally to
be offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
Exposure to Computer Architecture
vii Course Content Process Management, Memory Management, Storage
Management, Protection and Security, Virtual Machines,
Distributed Systems
viii Texts/References 1. Avi Silberschatz, Peter Baer Galvin, Greg Gagne,
“Operating Systems Concepts" 9th edition. Wiley.
2. Andrew S. Tanenbaum, Herbert Bos, ``Modern Operating
Systems”, 4th edition. Pearson.
ix Name(s) of Instructor(s) -
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
Electrical Engineering
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
xii Justification/ Need for
introducing the course
Fundamental course in Computer Science and Engineering.
2016 Batch CSE 60
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 305 Software Engineering
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
vii Course Content Introduction
What is Software Engineering.
Software Development Life-cycle
Requirements analysis, software design, coding, testing,
maintenance, etc.
Software life-cycle models
Waterfall model, prototyping, interactive enhancement,
spiral model. Role of Management in software development.
Role of metrics and measurement.
Software Requirement Specification
Problem analysis, requirement specification, validation,
metrics, monitoring and control.
System Design
Problem partitioning, abstraction, top-down and bottom-up
design, Structured approach. Functional versus object-
oriented approach, design specification and verification
metrics, monitoring and control. Software Architecture
Coding
Top-down and bottom-up, structured programming,
information hiding, programming style, and internal
documentation. Verification, Metrics, monitoring and
control.
Testing
Levels of testing functional testing, structural testing, test
plane, test cases specification, reliability assessment.
Software Project Management
Cost estimation, Project scheduling, Staffing, Software
configuration management, Quality assurance, Project
Monitoring, Risk management, etc. including tools for
software development to release, supporting the whole life
cycle.
viii Texts/References 1. Software Engineering: A Practioner’s approach, R.S.
Pressman, McGraw Hill, 8th edition
2. Introduction to Software Engineering, Pankaj Jalote,
Narosha Publishing
3. The Unified Software Development Process, I. Jacobson,
G. Booch, J. Rumbaugh, Pearson Education
4. Software Architecture in Practice, L. Bass, P. Clements, R.
2016 Batch CSE 61
Kazmann, 3rd ed., Addison Wesley
ix Name(s) of Instructor(s) NLS
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
No
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
xii Justification/ Need for
introducing the course
To teach students the engineering approach to software
development starting from understanding and documenting
user requirements to the design, development, testing and
release management where we all take into account non-
functional requirements and engineer them explicitly. The
course brings out various lifecycle activities in the
conventional as well as agile methodologies. It emphasizes
modern practices and tools for a successful engineering of a
usable and maintainable product.
2016 Batch CSE 62
Name of Academic Unit: Chemistry
Level: UG
Programme: B. Tech.
i Title of the course CH 301 Environmental studies
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course core
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content Module A: Natural Resources, Ecosystems,
Biodiversity and its conservation: Natural resources
and ecosystems, Forest, grassland, desert and aquatic
ecosystems, biodiversity at global, national and local
levels, conservation of biodiversity
Module B: Air Pollution
Introduction to understanding air quality
management, fundamental processes of meteorology,
Air Pollutants – Gaseous and particulate, Criteria for
pollutants, ambient and source standards, Aerosols:
Characterisation of aerosols, size distributions,
measurement methods; Transport behaviour:
diffusion, sedimentation, inertia; Visibility;
principles of particulate control systems.
Module C: Water Treatment
Discussion of water quality constituents and
introduction to the design and operation of water and
wastewater treatment processes.
Module D: Solid Waste Management and Climate
Change
Different aspects of solid and hazardous waste
management. Climate change and greenhouse gas
emissions, technologies would reduce the greenhouse
gas emissions. Climate change and its possible
causes.
Module E: Sociology/Environmentalism
Description: Environmentalism in sociological
tradition, Sustainability, North-South divide, Political
economy approaches in environmental studies,
Debates over environmental issues
Module F: Economics
Energy economics and financial markets, Market
dynamics, Energy derivatives, Energy Efficiency;
Sustainable Development: Concept, Measurement &
Strategies, Interaction between Economic
Development and the Environment
Module G: Philosophy
2016 Batch CSE 63
Environmental ethics, Deep ecology, Practical
ecology, Religion and attitude towards environmental
ethics, Ecofeminism and its evolution.
Module H: Field work and project: visit to a local area
to document environmental assets, case studies of a
simple ecosystem and group discussions on current
environmental issues.
viii Texts/References 1) Cunningham W.P. and Cunningham M.A. (2002),
Principles of Environmental Science, Tata McGraw-
Hill Publishing Company, New Delhi.
2) Dasgupta, P. and Maler, G. (eds.), (1997), The
Environment and Emerging Development Issues,
Vol. I, Oxford University Press, New Delhi.
3) Jackson, A.R.W. and Jackson, J.M. (1996),
Environmental Sciences: The Environment and
Human Impact, Longman Publishers.
4) Nathanson, J.A., (2002), Basic Environmental
Technology, Prentice Hall of India, New Delhi.
5) Redclift, M. and Woodgate, G. (eds.), (1997),
International Handbook of Environmental Sociology.
6)Srivastava, K.P. (2002), An Introduction to
Environmental Study, Kalyani Publishers, Ludhiana.
7) Review articles from literature
ix Name(s) of Instructor(s) BLT
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Common for all branches
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
2016 Batch CSE 64
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 312 Artificial Intelligence Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
vii Course Content* The lab will closely follow and aim to elucidate the lessons
covered in the theory course CS344. Implementation and study
of A*, Usage of Prolog Inferencing, Expert System Shells,
Neural Net Platforms, Prediction and Sequence Labeling using
HMMs, Simulation of Robot Navigation and such exercises
are strongly recommended.
viii Texts/References Main Text:
1. Stuart J. Russel, Peter Norvig, Artificial Intelligence: A
Modern Approach (3rd ed.). Upper Saddle River: Prentice
Hall, 2010.
Other references:
1. N.J. Nilsson, Principles of Artificial Intelligence, Morgan
Kaufmann, 1985.
2. Malik Ghallab, Dana Nau, Paolo Traverso, Automated
Planning: Theory & Practice, The Morgan Kaufmann Series in
Artificial Intelligence, 2004.
3. Christopher Bishop, Pattern Recognition and Machine
Learning, Springer, 2006.
4. Mark Stefik, Introduction to Knowledge Systems, Morgan
Kaufmann, 1995. E. Rich and K. Knight, Artificial
Intelligence, Tata McGraw Hill, 1992.
ix Name(s) of Instructor(s) -
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
No
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
x Justification AI is taught traditionally as it is driving force behind many
concepts in computer science and it is also precursor to
advanced courses like machine learning.
2016 Batch CSE 65
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course CS 314 Operating Systems Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
Exposure to Computer Architecture
vii Course Content Laboratory Assignments related to the topics covered in the
theory course: Process Management, Memory
Management, Storage Management, Protection and
Security, Virtual Machines, Distributed Systems
viii Texts/References 1. Avi Silberschatz, Peter Baer Galvin, Greg Gagne,
“Operating Systems Concepts" 9th edition. Wiley.
2. Andrew S. Tanenbaum, Herbert Bos, “Modern Operating
Systems”, 4th edition. Pearson.
ix Name(s) of Instructor(s) -
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
Electrical Engineering
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
xii Justification/ Need for
introducing the course
Fundamental course in Computer Science and Engineering.
2016 Batch CSE 66
Name of Academic Unit: Electrical Engineering.
Level: UG
Programme: B.Tech.
i Title of the course EE 314 Digital Signal Processing Laboratory
ii Credit Structure (L-T-P-C) (0-0-3-3)
iii Type of Course Core course
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) specify course
number(s)
Digital Signal Processing
vii Course Content Using Matlab (offline):
• Generation of elementary digital signals
• Concept of digital frequency
• Sampling theorem
• Convolution and correlation
• DFT and FFT
• Design of IIR filters
• Design of FIR filters
• Applications of signals processing Using DSP Kits
(Real time):
• Generation of elementary digital signals
• Convolution and correlation
• DFT and FFT
• Application of IIR filters
• Application of FIR filters
• Some speech processing experiments
• Some audio processing experiments
• Some biomedical signal processing experiments
viii Texts/References 1. Chassaing and D. Reay, Digital Signal Processing
and Applications with the TMS320C6713 and
TMS320C6416 DSK, 2nd ed., Wiley, Hoboken, NJ,2008.
2. D. R. Brown III, 2009 Workshop on Digital Signal
Processing and Applications with the TMS320C6713
DSK, Parts 1 & 2, available online from:
(a) http://spinlab.wpi.edu/courses/
dspworkshop/dspworkshop_part1_2009.pdf
(b) http://spinlab.wpi.edu/courses/
dspworkshop/dspworkshop_part2_2009.pdf
3. N. Dahnoun, ”DSP Implementation Using the
TMS320C6711 Processors,” contained in the Texas
Instruments ”C6000 Teaching Materials”
ix Name(s) of Instructor(s) SRMP
2016 Batch CSE 67
x Name(s) of other Departments /
Academic Units to whom the
course is relevant
None
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
xii Justification / Need for
introducing the course
This lab course complements the learning's in the Digital
Signal processing theory course.
2016 Batch CSE 68
ELECTIVES
Name of Academic Unit: Electrical Engineering
Level: UG
Programme: B.Tech.
i Title of the course EE 304 Robotics
ii Credit Structure (L-T-P-C) (2-0-2-6)
iii Type of Course Elective course
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) specify course
number(s)
Undergraduate Control Systems or Engineering
Mechanics
vii Course Content • Introduction
• Actuators and Drives: DC motors, dynamics of
single axis drive systems, Power Electronics basics
etc.
• Sensors and control components: Robot control
using PWM amplifiers, microcontrollers etc.
• Robot Mechanisms: Robot linkages and joints
• Planar Kinematics: Planar kinematics of serial link
mechanisms, Kinematics of Parallel Link
Mechanisms etc.
• Differential motion: Properties of Jacobians
• Mechanics of Robots: Statics, Duality of differential
kinematics and statics, robot dynamics, non-
holonomic systems
• Inverse kinematics and trajectory generation
• Concepts of Control: PID control, Hybrid position-
force control, compliance control, torque control
etc.
• Advanced topics and case studies
• Demonstrations and assignments using MATLAB
and ARM based experimental set-ups
viii Texts/References 1. Asada, H., and J. J. Slotine. Robot Analysis and
Control. New York, NY: Wiley, 1986.
2. John J. Craig Introduction to Robotics: Mechanics
andControl, Addison-Wesley Publishing Company,
3rd Edition, 2003.
3. M. Spong, M. Vidyasagar, S. Hutchinson, Robot
Modeling and Control, Wiley & Sons, 2005.
4. R. M. Murray, Z. Li, S. Sastry, A Mathematical
Introduction to Robotic Manipulation, CRC press,
1994.
ix Name(s) of Instructor(s) AM
2016 Batch CSE 69
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
Mechanical Engineering
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
xii Justification/ Need for
introducing the course
Robotics are being used in the industries for more than
two decades now. With decreasing cost of Electronics,
computational resources, now a day's robots are being
used, now a day, by not only in industries, but also in
the fields of medicine, prosthesis, home assistance,
agriculture and so on. Even after the wide-spread use,
the challenges in the field of Robotics are far from over
and a wide range of problems demanding research in
this field are still open. Due to the blend of immediate
applications as well as scope of research, a course on
Robotics is useful for students who will join the
industries as well as those who wish to pursue research
in this field.
2016 Batch CSE 70
Name of Academic Unit: Mathematics
Level: UG
Programme: B. Tech
i Title of the course MA 302 Algebraic codes and Combinatorics
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
--
vii Course Content Syllabus: Algebraic codes: Definition and
motivation, parameters, parity check matrix of an
algebraic code, basic inequalities, Macwilliams'
identity, Perfect codes, Hamming codes, Golay
codes, cyclic codes, relation to factorisation of
X^{n}-1; MDS codes
Combinatorics: t-designs, Fischers inequality, Finite
projective planes, Bruck-Ryser theorem, extensions
of Witt designs, ovals in projective planes
Eigen value techniques in graph theory, expander
graphs, Ramanujan graphs
viii Texts/References 1) J.H. Van Lint, Introduction to coding theory, 3rd
edition, Graduate texts in Maths, 86, Springer
2) J.H. Van Lint and R.M. Wilson, A course in
Combinatorics, Cambridge Univ. Press, 2001
3) P. J. Cameron and J.H. Van Lint, Graphs, Codes and
designs (Revised edition og Graph theory, Coding theory
and block designs)London Math Society 43, CUP 19890
ix Name(s) of Instructor(s) NSNS
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Common for all
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
--
2016 Batch CSE 71
Name of Academic Unit: Physics
Level: UG
Programme: B. Tech.
i Title of the course PH 301 Astrophysics for Engineers
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content 1. a. An inventory of the Universe,
b. Celestial sphere, Coordinates
c. Units, sizes, masses and distance scale
2. Electromagnetic spectrum
a. Radio, Microwave, Infrared, Optical, X-ray and
Gamma Ray
b. Telescopes and Detectors
3. Stars
A. General
a. Sun, Planets, (Earth)
b. Mass, Radius, Luminosity, Temperature,
Chemistry, Age and Types of stars
c. Hertzsprung-Russell Diagram
d. Birth and Evolution of stars
c. Limits on Mass - Quantum mechanism at large
scale: Brown Dwarf
B: Structure of a star:
a. Virial Theorem (qualitative)
b. Nuclear Energy, Pressure, Interaction with
radiation.
c. Basic Equations of Stellar Structure
d. Thermal Equilibrium, Radiation and Convection
- Schwarzchild Criterion
e. Helioseismology
4. Galactic and Extragalactic Astronomy
a. The Milky Way and Andromeda
b. Rotation Curve - Dark Matter
c. Structures within 500 mega light years
d. Clusters of Galaxies, Superclusters, Filaments
and Voids
5. Special Topics:
a. White Dwarf - Quantum Mechanics and
Gravitation: Chandrasekhar limit
b. Supernova, Neutron Stars, (Pulsar astronomy),
c. Black Holes, Gravitational Wave Astronomy
d. Gamma Ray Burst
e. Quasars and Active Galactic Nuclei
6. Topics in Cosmology
2016 Batch CSE 72
a. Hubble Expansion - Cosmic Distance Scale - Age
of the Universe
b. Standard Model of Cosmology
c. Cosmic Microwave Background
d. Supernova Cosmology Project and Dark Energy
e. Gravitational Lens
7. Major Astronomical facilities where India is
involved:
GMRT, SKA, Thirty Metre Telescope, LIGO,
ASTROSAT
8. Open questions in Astrophysics and Cosmology
viii Texts/References 1. The New Cosmos (A. Unsold, B. Baschek)
2. An Introduction to Modern Astrophysics (B.W. Carroll,
D.A. Ostlie)
3. Elements of Cosmology (J.V. Narlikar)
ix Name(s) of Instructor(s) DN
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
All
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
Astrophysics and Cosmology have a few fundamental
unsolved problems. This course is an attempt to
convey to the students that there are upcoming
powerful astronomical facilities capable of solving
some of them. But both at hardware and software
level, it is Technology that drives what observations
are feasible. India is one of the main contributors for
development of some of the technologies.
2016 Batch CSE 73
Name of Academic Unit: Physics
Level: B. Tech.
Programme: B. Tech.
i Title of the course Quantum Computation
ii Credit Structure (L-T-P-C) (2-1-0-6)
iii Type of Course Elective
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Exposure to PH101 – Quantum Mechanics and
Applications
MA102 - Linear Algebra
vii Course Content Introduction to Classical Computation: The Turing
Machine –The Church-Turing thesis, Universal
Turing Machine, Probabilistic Turing machine;
Circuit model of computation – Binary arithmetics,
Elementary logic gates, Universal classical
computation; Computational complexity –
Complexity classes, Chernoff bound; Energy and
information – Maxwell’s demon, Landauer’s
principle, Extracting work from information;
Reversible computation – Toffoli and Fredkin gates,
billiard ball computer.
Framework of Quantum Mechanics: The Dirac
notation and Hilbert Space, Dual Vectors, Operators,
Spectral Theorem, Functions of operators, Tensor
Products, Schmidt Decomposition theorem; The state
of quantum system, time-evolution of a closed
system; composite systems, measurement, mixed
states and general quantum operations.
Quantum Computation: The quantum circuit model,
Quantum Gates – 1-qubit gates, Controlled-U gates;
Universal Sets of Quantum Gates, Implementing
measurements with quantum circuits.
Quantum communications: Super dense coding,
Quantum Teleportation.
Quantum Algorithms: Probabilistic versus quantum
algorithms, Phase Kick-Back, Deutsch algorithm,
Deutsch-Jozsa Algorithm, Simon’s Algorithm,
Grover’s quantum search Algorithm.
Quantum computational Complexity Theory and
lower bounds: computational complexity, Black-Box
Model, General Black-box lower Bounds, Polynomial
Methods, Block Sensitivity.
Quantum Error Corrections: Classical error
corrections – The error model, encoding, error
recovery, Fault tolerance, Quantum error correction,
2016 Batch CSE 74
Three- and nine-qubit quantum codes, Fault tolerant
quantum computation.
Quantum Computation with physics systems
viii Texts/References 1. Quantum Computation and Quantum
Information, M. A. Nielsen & I. L. Chuang, 10th
Edition, Cambridge University Press, NY, USA
(2011).
2. An introduction to Quantum Computing, P.
Kaye, R. Laflamme and M. Mosca, Oxford University
Press, (2010).
3. Preskill's lecture notes on Quantum
Information and Quantum Computation,
http://www.theory.caltech.edu/people/preskill/ph229/
4. Principles of Quantum Computation and
Information (Vol.-1), G. Benenti, G. Casati, and G.
Strini, World Scientific, 2004.
5. Classical and Quantum Computation, A. Yu.
Kitaev, A. H. Shen, and M. N. Vyalyi, Americal
Mathematical Society, 2002
6. Quantum Coputation and Quantum
Communication-Theory and Experiments, M.
Pavicic, Springer, 2006.
7. Quantum Computer Science, N. D. Mermin,
Cambridge, 2007.
8. Lectures on Quantum Information, Edited by
D. Bruss and G. Leuchs, Wiley-VCH Verlag, 2007.
ix Name(s) of Instructor(s) RP
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Elective for CSE, EE
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
The course introduces to the topics like Quantum
states, Qubits, Quantum Algorithms, quantum
complexity problems, quantum error corrections, etc.
the topics which are required to understand the
science behind working of quantum computers.
2016 Batch CSE 75
Name of Academic Unit: Mathematics
Level: UG
Programme: B. Tech.
i Title of the course MA 303 Fourier series and Fourier transforms.
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be
offered
Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Exposure to Calculus (MA 101), Linear Algebra (MA
102)
vii Course Content Notion of Fourier series: definition and examples,
trignometric polynomials, various notion of
convergence. Convolution: Dirichlet kernel and
approximation identities, Fejer's summation,
Plancherel and Parseval's theorems, $L^2$
convergence, orthonomal basis.
Application of fourier series: isoperimetric inequality
and Weyl's equidistribution theorem.Fourier
transform: definition and examples, character theory,
Schwartz functions, fourier inversion formula,
Plancherel theorem, fourier tranform on euclidean
spaces, introduction to the theory of distributions,
poisson summation formula, zeta and theta
functions.Applications of fourier transform: analytic
properties of Riemann zeta function, poisson kernel
and heat equations, partial differential equations,
Heiseinberg's uncertainity principle.equations, partial
differential equations, Heiseinberg's uncertainity
principle.
vii
i Texts/References 1. Princeton lectures in Analysis-I, Fourier analysis-
an introduction by E. M. Stein and R. Shakarchi,
Princeton university press, 2003
2. Analysis II Differential and Integral Calculus,
Fourier Series, Holomorphic Functions, by Roger
Godement, Springer 2005 edition.
3. Fourier Analysis and Its Applications (Pure and
Applied Undergraduate Texts), by Gerald B. Folland,
American Mathematical Society, 2009.
ix Name(s) of Instructor(s) KK
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
EE and ME
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
This is a mathematics course which is useful for any
branch of engineering
2016 Batch CSE 76
Name of Academic Unit: All
Level: UG
Programme: B.Tech.
i Title of the course CH 302 Sustainable energy and energy materials
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
First year undergraduate chemistry course (CH101)
vii Course Content Fuel cells, catalysis for fuel cells and sustainable
chemical processes • Batteries • Solar photovoltaics
Wind power: practical aspects • Tidal power •
Inorganic, Organic and functional biomaterials as
energy materials
viii Texts/References
ix Name(s) of Instructor(s) RRM/SSR
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Course is relevant for students across all the
departments
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
Developing sustainable/renewable energy methods
are critical to meet the ever increasing global energy
demands. This course will shed light on various
methods which are currently under practice towards
generating sustainable energy and their detailed
mechanisms.
2016 Batch CSE 77
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course MA 304 Graph Theory and its applications
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be
offered
Autumn
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
Exposure to Discrete Structures
vii Course Content Fundamentals of graph theory. Topics include: connectivity,
planarity, perfect graphs, coloring, matchings and extremal
problems.
Basic concepts in Combinatorics. Topics include: counting
techniques, inclusion-exclusion principles, permutations,
combinations and pigeon-hole principle.
viii Texts/References 1. D. B. West, ``Introduction to Graph Theory" 2nd edition.
Prentice Hall.
2. Martin C. Golumbic, ``Algorithmic Graph Theory and
Perfect Graphs." 2nd edition.
3. R. Diestel, ``Graph Theory", 5th edition.
ix Name(s) of Instructor(s) NSNS
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
Electrical Engineering
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
xii Justification/ Need for introducing
the course
Graph Theory and Combinatorics have applications in many
areas in computer science and electrical engineering. This is
considered an essential course for those who want to explore
further on theoretical computer science.
2016 Batch CSE 78
Name of Academic Unit: Electrical engineering
Level: UG
Programme: B. Tech.
i Title of the course Deep Learning
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
Exposure to Calculus, Linear Algebra, Probability,
Random Processes, Ability to code in Python
vii Course Content Introductory Concepts of DNN (a) Linear regression, logistic regression – penultimate layers
of a neural network
(b) Dealing with nonlinearity – Kernal Trick
(c) Data-driven kernel learning using NNs
DNN Training (a) Issues in training practical deep networks,
Vanishing/Exploding gradients
(b) Regularization for Deep Learning – Early stopping,
weight regularization, activity regularization, dropout
(c) Optimization methods for training deep networks –
Stochastic gradient descent, rmsprop, adam
(d) Convolutional Neural networks
Sequence Modeling (a) Recurrent neural networks
(b) LSTMs ans BLSTMs
Unsupervised Learning (a) Autoendcoders
(b) Variational autoencoders
(c) Generative adversial networks (GANs)
(d) Representation learning and feature extraction
Vi
ii Texts/References 1. Ian Goodfellow and Yoshua Bengio and
Aaron Courville, “Deep Learning,” MIT
Press
2. Bishop, C. M. Neural Networks for
Pattern Recognition. Oxford University
Press. 1995
3. B Yegnanarayana, “Artificial Neural Networks,” PHI.
ix Name(s) of Instructor(s)
SRMP
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
CSE
xi Is/Are there any course(s) in the No
2016 Batch CSE 79
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
xii Justification/ Need for
introducing the course
2016 Batch CSE 80
Name of Academic Unit: Computer Science & Engineering
Level: UG
Programme: B. Tech.
i Title of the course CS 306 Introduction to Artificial Neural Networks &
Deep Learning
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content Background to ANN and PDP models; Basics of
ANN including terminology, topology and learning
laws; (4 lectures)
Analysis of Feedforward neural networks (FFNN)
including linear associative networks, perceptron
network, multilayer perceptron, gradient descent
methods and backpropagation learning; (8 lectures)
Analysis of Feedback neural networks (FBNN)
including Hopfield model, state transition diagram,
stochastic networks, Boltzmann learning law; (8
lectures)
Evolution of ANN architectures - from learning to
deep learning: (1 lecture)
viii Texts/References 1. B Yegnanarayana, Artificial Neural Networks,
Prentice Hall of India, New Delhi, 1999.
2. David E Rumelhart, James L McClelland, and the
PDP Research group, Eds, Parallel and Distributed
Processing: Explorations in Microstructure of
Cognition, Vol.1, Cambridge MA: MIT Press, 1986a
3. James L McClelland, David E Rumelhart and the
PDP Research group, Eds, Parallel and Distributed
Processing: Explorations in Microstructure of
Cognition, Vol.2, Cambridge MA: MIT Press, 1986b
4. James L McClelland, David E Rumelhart and the
PDP group, Eds, Explorations in Parallel and
Distributed Processing: A Handbook of Models,
Cambridge MA: MIT Press, 1989
5. Simon Haykin, Neural Networks and Learning
Machines, Pearson Education, 2011
6. Ian Goodfellow, Yoshua Bengio and Aaron
Courville, Deep learning, MIT Press, 2017
ix Name(s) of Instructor(s) SRMP
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
EE
xi Is/Are there any course(s) in the same/ Nil
2016 Batch CSE 81
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the
course
--
2016 Batch CSE 82
Name of Academic Unit: Computer Science and Engineering
Level: UG
Programme: B.Tech.
i Title of the course Topics in Design and Analysis of Algorithms
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
Discrete Mathematics, Design and Analysis of algorithms,
Data structures and Algorithms.
vii Course Content Module 1: Iterated Improvement Paradigms-
Computational and Algorithmic Thinking, Matching
Algorithms, Flow Algorithms (16 hours).
Module 2: Approximation Algorithms- Greedy
Approximation, Local Search, Linear Programming,
Duality Techniques (16 hours)
Module 3: Randomized Algorithms- Monte Carlo and Las
Ve-gas types, Randomized Attrition, Randomized In-
cremental Design, Sampling, Chernoff type bounds and
High Confidence Analysis, Abundance of witness for
Monte Carlo algorithms, Number theoretic Algorithms (16
hours).
Vi
ii Texts/References 1. [OA] James B. Orlin, Ravindra K. Ahuja, and Thomas L.
Magnanti, “Network Flows”, Prentice Hall, 1993.
2. [WS] David P. Williamson and David B. Shmoys, “The
Design of Approximation Algorithms”,
CambridgeUniversity Press, 2011.
3. [MR] Rajeev Motwani and Prabhakar Raghavan, “Ran-
domized Algorithms”, Cambridge University Press,
1995.
ix Name(s) of Instructor(s) C. Pandu Rangan (IIT Madras)
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
Nil
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
No
xii Justification/ Need for
introducing the course
The objective of this course is to get excied about some
advanced algorithm design techniques. We need to learn
many more beyond the basic paradigms such as divide and
conquer, greedy and dynamic programming. We focus on
algorithmic thinking inspired by three fundamental and key
2016 Batch CSE 83
approaches- Iterated improvements, Approximations and
Randomization.
2016 Batch CSE 84
Name of Academic Unit: Mechanical Engineering
Level: UG
Programme: B.Tech.
i Title of the course ME 305 Synthesis of Mechanisms
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be
offered
VI
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
None
vii Course Content Planar mechanisms and geometry of motion:
Definition, Basic concepts, classification of links and
pairs, Mechanisms, Machine and Inversions,
Grashof’s Law, Transmission of torque and force in
mechanisms, Mobility, Degree of freedom (DOF),
Grubler criterion, DOF permitted by turning and
sliding, Equivalent mechanisms, Unique
mechanisms.
Number synthesis: DOF and effect of odd and even
number of links, Minimum number of binary links in
a mechanism Possibility of minimum number of
turning pairs in a mechanism, Enumeration of
kinematic chain, DOF of spatial mechanisms.
Synthesis of linkages: Type, number and
dimensional synthesis, Precision points, structural
error, Chebyshev spacing. Poles and relative poles.
Graphical method for synthesis – Motion
generation, Path generation, Function generation,
Overlay method.
Analytical method for synthesis – Freudenstein’s
equation, Loop closure technique, Bloch’s method of
synthesis, Order synthesis.
Coupler curves: Equation of coupler curves,
Synthesis for path generation, Robert-Chebyshev
theorem (cognate linkages).
viii Texts/References TEXTBOOKS
1. Ghosh and Mallik, Theory of Mechanisms and
Machines, East West Press Pvt. Ltd.
REFERENCES
2016 Batch CSE 85
1. George N. Sandor and Arthur G. Erdman,
Mechanism Design: Analysis and Synthesis Volume
I, Third Edition, Prentice Hall, 1996.
2. George N. Sandor and Arthur G. Erdman, Advanced
Mechanism Design: Analysis and Synthesis Volume
II, First Edition, Pearson, 1984.
ix Name(s) of Instructor(s) SV
x Name(s) of other Departments/
Academic Units to whom the course
is relevant
All
xi Is/Are there any course(s) in the
same/ other academic unit(s) which
is/ are equivalent to this course? If so,
please give details.
No
xii Justification/ Need for introducing
the course
The science of mechanism kinematics is roughly divided
in two divergent topics: analysis and synthesis. Analysis
(Theory of Machines) typically involves a defined
mechanism and predicting how either the coupler or the
follower will react to specific motions of the driver. A
fundamentally different problem is that of kinematic
synthesis. By kinematic synthesis, it means the design or
creation of a mechanism to attain specific motion
characteristics. In this sense, synthesis is the inverse of
analysis. Synthesis is the very essence of design because
it represents the creation of new hardware to meet
particular requirements of motion: displacement,
velocity, acceleration; individually or in combination.
2016 Batch CSE 86
Name of Academic Unit: Mechanical Engineering
Level: UG
Programme: B.Tech.
i Title of the course ME 306 Theory of Elasticity
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
Mechanics of Materials
vii Course Content Analysis of Stress: Stress tensors. Cauchy's stress
principle, direction cosines, stress components on an
arbitrary plane with stress transformation. Principal
stresses in three dimensions, stress invariants, Equilibrium
equations, Octahedral stresses, Mohr's stress circle:
Construction of Mohr Circle for two and three
dimensional stress systems, Equilibrium equations in polar
coordinates for two-dimensional state of stresses. General
state of stress in 3D in cylindrical coordinate System.
Analysis of Strain: types of strain, strain tensors, strain
transformation. Principal strains, strain invariants,
octahedral strains, Mohr's Circle for Strain, Equations of
Compatibility for Strain, Navier’s
Stress-strain relations: Stress-strain relations,
Generalized Hooke's law, Lame’s displacement equations
of equilibrium, transformation of compatibility condition
from Strain components to stress components (Beltrami-
Michell compatibility relation). Strain energy in an elastic
body, General theorems: St. Venant's principle,
Superposition Principle, Uniqueness theorem, Reciprocal
theorem.
2D problems in Cartesian coordinate system: plane
stress and plane strain problems. Stress function, Solution
of two-dimensional problems with different loading
conditions by the use of polynomials. Solution of two-
dimensional problems with different loading conditions by
the use of Fourier method.
2D problems in Polar coordinate system: Strain-
displacement relations, compatibility equation, stress-
strain relations, stress function and Biharmonic equation.
2016 Batch CSE 87
General solution in Polar coordinates (Michell solution),
Polar coordinate solutions: Stress concentration, effect of
circular holes on stress distribution in plates, Half-space
problems - Flamant solution, Hertz disk solution, Wedge
problems. Axisymmetric problems, thick-walled
cylinders, rotating disks of uniform and variable thickness
Torsion of prismatic bars: General solution of the torsion
problem – St. Venant’s semi-inverse approach, Prandtl’s
stress function, torsion of circular, elliptic, equilateral
triangle cross sections. Solution by Fourier method:
Rectangular section, Prandtl's membrane analogy, torsion
of thin walled and multiple cell closed sections.
Thermal Stresses: Thermoelastic Stress–Strain
Relations, Equations of Equilibrium, Strain–Displacement
Relations, Thin Circular Disk: Temperature Symmetrical
about Centre, Long Circular Cylinder
Introduction to 3D problems: Papkovich–Neuber
potential representations for 3D Solutions for Isotropic
Solids, Demonstration that Papkovich–Neuber solution
satisfies the governing equations, Point Force in an Infinite
Solid, Stretching of bar under its weight
viii Texts/References Texts
1. Martin H. Sadd, Elasticity: Theory, Applications, And
Numerics, 3rd Edition, Academic Press, 2014.
2. L. S. Srinath, Advanced Mechanics of So lids, 2nd
Edition, TMH Publishing Co. Ltd., New Delhi, 2003
3. C.T. Wang, "Applied Elasticity", McGraw-Hill Book
Company, New York, 1953
References
1. S. P. Timoshenko, J. N. Goodier, Theory of Elasticity, ,
3rd Edition, McGraw Hill Publishing Co. 1970.
2. I. S. Sokolnikoff, The Mathematical theory of elasticity,
McGraw Hill, New York, 1946
3. J. R. Barber, Elasticity, 3rd edition, Springer, 2009.
4. A. P. Boresi, Ken Chong, James D. Lee, Elasticity in
Engineering Mechanics, , 2010, Wiley.
5. Allan F. Bower, Applied Mechanics of Solids, CRC
Press, 2009.
6. R. W. Soutas-Little, Elasticity, Dover Publication Inc,
New York, 1973
7. A. S. Saada, “Elasticity Theory and Applications”,
Cengage Learning, New Delhi, 2014.
ix Name(s) of Instructor(s) TPG
x Name(s) of other Departments/
Academic Units to whom the
course is relevant
All
xi Is/Are there any course(s) in the No
2016 Batch CSE 88
same/ other academic unit(s)
which is/ are equivalent to this
course? If so, please give details.
xii Justification/ Need for
introducing the course
Theory of elasticity (TOE) is a course which investigates
effect of external loads on deformable bodies. Unlike
mechanics of materials, TOE is more rigorous as it relaxes
many assumptions of mechanics of materials. Thus, it paves
way to analyse solids beyond structural elements like beams,
trusses and shafts. This approach for generalization invokes
more rigor mathematically. In this course, we linearize
strains and stress-strain relation to attempt problems from
mechanics of materials in the new perspective i.e. from TOE
approach but not limited to it. Thus, it aims to appreciate the
need for experimental mechanics techniques like
Photoelasticity, Thermoelastic stress analysis, DIC and the
need for computational tools like FEM.
2016 Batch CSE 89
Name of Academic Unit: Mechanical Engineering
Level: UG
Programme: B.Tech.
i Title of the course ME 307 Introduction to Turbulence and its Modelling
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
ME203 Fluid Mechanics
vii Course Content Introduction to Turbulence: Nature of turbulence,
origin of turbulence, laminar and turbulent boundary
layers, diffusion of turbulence, concept of eddy
viscosity
Statistics of Turbulence: Statistical aspects of
turbulence, scales in turbulence, spectrum of
turbulence, energy cascade in isotropic turbulence,
Kolmogorov hypotheses
Mathematical Theory of Turbulence: The Reynolds
equation, Reynolds decomposition, equations for the
mean flow, Reynolds stress, mixing length model,
turbulent heat transfer, limitations of mixing length
theory
Dynamics of Turbulence: Dynamics of turbulence,
Taylor microscale, Reynolds stress and vorticity, the
vorticity equation
Boundary-free and Wall-bounded Turbulence:
Turbulent wakes, turbulent jets and mixing layers,
turbulent flows in pipes and channels, experimental
techniques for turbulence characteristics
Introduction to Turbulence Modelling: Turbulence
modelling and closure problem, algebraic models,
modern variants of the mixing length model, one
equation models, k- and k- models, Spalart–
Allmaras turbulence model
Introduction to Numerical Techniques for
Turbulence: Direct numerical simulations (DNS),
large eddy simulations (LES) and Reynolds averaged
Navier-Stokes (RANS) modelling techniques,
spectral methods and particle based methods for
turbulence
2016 Batch CSE 90
viii Texts/References TEXTBOOKS
1. Tennekes H. and Lumley J., A first course in turbulence,
M.I.T. Press.
2. Tritton D.J., Physical Fluid Dynamics, Oxford
University Press.
3. Davidson P.A., Turbulence: An Introduction for
Scientists and Engineers, Oxford Uni Press.
4. Townsend A.A., The structure of turbulent shear flow,
Cambridge University Press., 1980.
5. Wilcox D.C., Turbulence modeling for CFD, DCW
Industries, Incorporated, 1994.
ix Name(s) of Instructor(s) DVP
x Name(s) of other Departments/
Academic Units to whom the course
is relevant
All
xi Is/Are there any course(s) in the
same/ other academic unit(s) which
is/ are equivalent to this course? If so,
please give details.
No
xii Justification/ Need for introducing
the course
The important topic in fluid mechanics and thermal
sciences is the investigation of turbulent fluid flows. The
topic is important to understand transport in a highly
disordered flows and for other topics, e.g. turbulent
mixing and combustion. This course rightly blends theory
of turbulence with the advanced modelling aspects of it.
The course is useful for research scholars and advanced
learners of fluid mechanics.
2016 Batch CSE 91
Name of Academic Unit: Humanities and Social Sciences
Level: UG
Programme: B. Tech.
i Title of the course HS 302 Modernism and the ‘Hero’
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full Semester
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content Fiction/Non-Fiction of Franz Kafka, Albert Camus,
Saadat Hasan Manto, Samuel Beckett, among others.
viii Texts/References --
ix Name(s) of Instructor(s) RT
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
--
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
None
xii Justification/ Need for introducing the
course
This course would focus on the Modernist period in
literature of the 20th century, analysing texts from
different cultures and continents. Aiming to unpack
‘Modernism’ and its complex socio-political
backdrop, the course would ask critical questions
such as Who is the Modern ‘Hero’? What are the
markers of this ‘hero’? What are the connections
between this ‘hero’ and the ‘Anti-Hero? How has the
figure of the Hero evolved?
2016 Batch CSE 92
Name of Academic Unit: Humanities and Social Sciences
Level: UG
Programme: B. Tech.
i Title of the course HS 305 Intellectual Property Management
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be
offered
Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content Historical Development of Intellectual Property in
Industrialised Society, Patent Basics, Patent Systems
around the world, Application of patents in different
technology areas including Software and Business
Methods, How to read a Patent, Introduction to Patent
Databases and Analysis Tools, Patent Searching and
Analysis, Use of Patent Information for Research and
Business Planning, Introduction to TRIZ , Evaluation
of Patents, IPR Beyond Patents ( Copyright, Trade
Marks, Designs and other forms of IP rights), IP
Management including IP Strategy for Start-ups and
Corporates , IP Licensing, IP Acquisition and
Enforcement, Case studies and Tutorial.
viii Texts/References Reading material will be provided
ix Name(s) of Instructor(s) Prof. R. R. Hirwani
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
All the departments
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
Intellectual Property plays an important role in
technological innovations, creation and growth of
technology start-ups. The existing patent databases
are repositories of global technical knowledge and
can be used for problem identification, cross
fertilisation of ideas, generation of alternate solutions,
technology monitoring, and competitive intelligence.
It is felt necessary to sensitise the students to current
IP regime and prepare them for the career in
technology ventures.
2016 Batch CSE 93
2016 Batch (SEMESTER VII) ELETIVES
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech./MS
Programme: B.Tech./MS
i Title of the course Power Aware Computing
ii Credit Structure (L-T-P-C) 3-0-2-8
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students)
– specify course number(s)
Exposure to Computer Architecture,
Operating Systems
vii Course Content Introduction to Power and Energy, Power
consumption modeling and estimation,
Dynamic power management and DVFS,
Leakage reduction techniques, circuit-level
and Micro-architecture techniques, Power
states and ACPI support, Memory/cache
power optimizations. Software level
techniques, GPU power modeling and
optimizations
viii Texts/References 1. S. Kaxiras, M. Martonosi, Computer
Architecture Techniques for Power-
Efficiency, Synthesis Lectures on Computer
Architecture. Morgan &C laypool publishers
2. Siva G. Narendra, Anantha Chandrakasan
P. Leakage in Nanometer CMOS
Technologies, Series on Integrated Circuits
and Systems
3. Rakesh Chadha, J Bhasker an ASIC Low
Power Primer: Analysis, Techniques and
Specification
ix Name(s) of Instructor(s) Dr. Gayathri Ananthanarayanan
x Name(s) of other Departments/ Academic
Units to whom the course is relevant
Electrical Engineering
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
Power/energy consumption is a first-class
problem for computer systems. It plays a
major role in design of all kinds of systems
(from smart phones and handhelds to data
centres). This course aims to discuss, assess
and compare the behaviour and performance
of various power saving techniques found in
modern computing systems.
2016 Batch CSE 94
Name of Academic Unit: Level: B. Tech.
Programme: B.Tech.
i Title of the course Distributed Systems
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be
offered
VII
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Operating Systems, Data Structures and Algorithms,
Programming in C++
vii Course Content Introduction to distributed systems, Message
Passing, Leader Election, Distributed Models,
Causality and Logical Time
Logical Time, Global State & Snapshot and
Distributed Mutual Exclusion-Non-Token and
Quorum based approaches
Distributed Mutual Exclusion-Token based
approaches, Consensus & Agreement,
Checkpointing & Rollback Recovery
Deadlock Detection, DSM and Distributed MST
Termination Detection, Message Ordering &
Group Communication, Fault Tolerance and
Self-Stabilization, Gossip Style communication,
chord, pastry
Concurrency and Replication Control, RPCs,
Transactions
Distributed Randomized Algorithms, DHT and
P2P Computing
Case Studies: GFS, HDFS, Map Reduce and
Spark
viii Texts/References 1. Distributed Computing: Principles, Algorithms,
and Systems- Ajay D. Kshemkalyani and
Mukesh Singhal
2. Distributed Computing: Fundamentals,
Simulations and Advanced Topics-Hagit Attiya
and Jennifer Welch
3. Distributed Algorithms-Nancy Lynch
4. Elements of Distributed Computing-Vijay K.
Garg
5. Advanced Concepts in Operating Systems-
Mukesh Singhal, Niranjan G. Shivaratri
ix Name(s) of Instructor(s) Dr. Kedar Khandeparkar
x Name(s) of other Departments/
Academic Units to whom the course is
2016 Batch CSE 95
relevant
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
Technologies such as Hadoop, Cassandra, Spark, etc., that
have emerged in the recent times are mainly based on the
principles of distributed systems. This course aims to
develop an in-depth understanding of the various
distributed algorithms and discuss some use cases.
2016 Batch CSE 96
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech./MS
Programme: B.Tech./MS
i Title of the course Compilers
ii Credit Structure (L-T-P-C) 3-0-2-8
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students)
– specify course number(s)
Exposure to Data Structures and Algorithms,
Computer Architecture, Automata Theory
vii Course Content The compiled and interpreted execution
models. Lexical analysis and parsing using lex
and yacc. Scope and visibility analysis. The
role of types. Type analysis of a language with
basic types, derived types, parametric
polymorphism and subtypes. Binding times.
Data layout and lifetime management of data.
Stack and heap as storage structures.
Implementation of function calls. Activation
records structures. Dynamic memory
allocation and Garbage collection.
Implementation of higher order functions -
closures. Implementation of control
structures, exception handling.
Implementation of object oriented concepts --
objects, inheritance and dynamic dispatch.
Implementation of a naive code generator for
a virtual machine. Security checking of virtual
machine code.
viii Texts/References 1. Alfred V. Aho, Monica S. Lam, Ravi Sethi
and Jeffrey D.Ullman: Compilers: Principles,
Techniques, and Tools, 2/E, AddisonWesley
2007.
2. Andrew Appel: Modern Compiler
Implementation in C/ML/Java, Cambridge
University Press, 2004
3. Dick Grune, Henri E. Bal, Cerial J.H.
Jacobs and Koen G. Langendoen: Modern
Compiler Design, John Wiley & Sons, Inc.
2000.
4. Michael L. Scott: Programming Language
Pragmatics, Morgan Kaufman Publishers,
2006.
ix Name(s) of Instructor(s)
x Name(s) of other Departments/ Academic
Units to whom the course is relevant
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
2016 Batch CSE 97
xii Justification/ Need for introducing the
course
The knowledge on compilers helps to
understand how programs written in a high-
level language is converted to machine codes.
This helps programmers to write better
programs.
2016 Batch CSE 98
Name of Academic Unit: Computer Science and Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course CS 304 Graph Theory and Combinatorics
ii Credit Structure (L-T-P-C) (3 0 0 6)
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students)
– specify course number(s)
Exposure to Discrete Structures
vii Course Content Combinatorics: Counting, the pigeon-hole
principle, Principle of inclusion exclusion,
Derangements, Recurrence relations, Ramsey
theory
Graph theory: Fundamentals, Trees, Matching,
Connectivity, Planar graphs, Coloring
viii Texts/References 1. D. B. West, ``Introduction to Graph
Theory" 2nd edition. Prentice Hall.
2. Van Lint, Jacobus Hendricus, and Richard
Michael Wilson, A course in combinatorics.
Cambridge university press, 2001.
3. Harary. Graph Theory. Reading, MA:
Perseus Books, 1999.
4. R. Diestel, ``Graph Theory", 5th edition.
Springer
ix Name(s) of Instructor(s) -
x Name(s) of other Departments/ Academic
Units to whom the course is relevant
Electrical Engineering
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
Graph Theory and Combinatorics have
applications in many areas in computer science
and electrical engineering. This is considered
an essential course for those who want to
explore further on theoretical computer
science.
2016 Batch CSE 99
Name of Academic Unit: Computer Science and Engineering
Level: B.Tech./ MS
Programme: B.Tech./ MS
i Title of the course Advanced Algorithms
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students)
– specify course number(s)
Exposure to Discrete Mathematics, Design
and Analysis of algorithms, Data structures
and Algorithms.
vii Course Content Module 1: Iterated Improvement Paradigms-
Computational and Algorithmic Thinking,
Matching Algorithms, Flow Algorithms (16
hours).
Module 2: Approximation Algorithms-
Greedy Approximation, Local Search, Linear
Programming, Duality Techniques (16 hours)
Module 3: Randomized Algorithms- Monte
Carlo and Las Vegas types, Randomized
Attrition, Randomized Incremental Design,
Sampling, Chernoff type bounds
and High Confidence Analysis, Abundance
of witness for Monte Carlo algorithms,
Number theoretic Algorithms (16 hours).
viii Texts/References 1. [OA] James B. Orlin, Ravindra K. Ahuja,
and Thomas L. Magnanti, “Network Flows”,
Prentice Hall, 1993.
2. [WS] David P. Williamson and David B.
Shmoys, “The Design of Approximation
Algorithms”, Cambridge University Press,
2011.
3. [MR] Rajeev Motwani and Prabhakar
Raghavan, “Randomized Algorithms”,
Cambridge University Press, 1995.
ix Name(s) of Instructor(s) C. Pandu Rangan (IIT Madras)
x Name(s) of other Departments/ Academic
Units to whom the course is relevant
Nil
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
The objective of this course is to get excited about
some advanced algorithm design techniques. We
need to learn many more beyond the basic
paradigms such as divide and conquer, greedy and
dynamic programming. We focus on algorithmic
thinking inspired by three fundamental and key
approaches- Iterated improvements,
Approximations and Randomization.
2016 Batch CSE 100
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech./MS
Programme: B.Tech./MS
i Title of the course Computer Graphics
ii Credit Structure (L-T-P-C) 3-0-2-8
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Exposure to C/C++ Programming is desirable,
Data Structures and Algorithms, Basic Linear
Algebra.
vii Course Content Introduction to the course, Rasterization
Basics, Drawing in OpenGL, Clipping
2D Transformations, 3D Transformations,
Viewing Transformations,
The Modeling-Viewing Pipeline, Visibility,
Hierarchical Modelling, Shading, Texture
Cubic Splines, Bezier Splines, B-Splines
Principles of Animation, Interpolation for
Animation, Modelling Surfaces
viii Texts/References 1. Fundamentals of Computer Graphics
(Third Edition), Peter Shirley, Steve
Marschner and others, A K Peters/CRC
Press (2009)
2. Interactive Computer Graphics - A Top-
Down Approach Using OpenGL (6/e),
Edward Angel
3. Computer Graphics using OpenGL (3/e), F.
S. Hill Jr. and S. M. Kelley
4. Computer Graphics with OpenGL (3/e), D.
D. Hearn and M. P. Baker
ix Name(s) of Instructor(s)
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Nil
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
Computer Graphics has applications in visual
communication, computer games, and any
automation which involves processing of
visual data.
2016 Batch CSE 101
Name of Academic Unit: Dept of Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course Introduction to Logic
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be
offered
Even
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Discrete Mathematics
vii Course Content 1 Propositional logic: Natural deduction, Semantics
of propositional logic, Soundness of propositional
logic, Completeness of propositional logic
Horn clauses and satisfiability. 2 Predicate logic : Natural deduction rules,
decidability of predicate logic, Expressiveness of
predicate logic 3 Program correctness : Hoare triples, Partial and total
correctness, Proof calculus for partial correctness,
Proof calculus for total correctness 4 Other Applications such as Logic in databases,
Logic programming, Puzzle solving 5 Practice with Verification tools
viii Texts/References (1) Logic in Computer Science. Huth and Ryan.
Cambridge University Press, 2004
(2) A Mathematical Introduction to Logic. Herbert
D Enderton. Harcourt Academic Press.
(3) First-Order Logic and Automated Theorem
Proving by Melvin Fitting.
ix Name(s) of Instructor(s)
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Mathematics
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
2016 Batch CSE 102
xii Justification/ Need for introducing the
course
This is introductory course for logic, with an aim to
applications in Computer Science, like program
correctness and verification
2016 Batch CSE 103
Name of Academic Unit: Dept. of Computer Science and Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course Principles of Programming Languages
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be
offered
Odd
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Discrete Mathematics, CS 101
vii Course Content Principles of Language Design,
Specification of Language Syntax,
Survey of Procedural and OO Languages,
Intro. to Functional Programming,
Intro. to Logic Programming,
Programming Language Semantics: Values, Bindings,
Types,
Programming Language Constructs, Expressions,
Statements,
Procedures and Environments, Parameter Passing
Type systems, type inferences, unification.
viii Texts/References
(1) Programming Language Pragmatics by
Michael Scott. Fourth Edition, Morgan Kaufmann
Publishers
(2) Programming Languages: Application and
Interpretation by Krishamurthi, Shriram.
(3) Essentials of Programming Languages by
Friedman, Wand, and Haynes. MIT Press, 2001.
ix Name(s) of Instructor(s)
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
NO
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
NO
xii Justification/ Need for introducing the
course
The languages that programmers use are constantly
changing, and the
popular languages of today will surely be replaced by
new ones. The
2016 Batch CSE 104
objective of this course is to provide students with a
working
knowledge of the basic principles underlying the
design of all
computer programming languages. Students
completing this course should
be able to quickly learn to effectively use new
computer programming
languages. In particluar, after taking this course
students should be
able to do the following:
Evaluate programming language features and
designs.
Solve problems using the functional, object-oriented,
and declarative
paradigms.
Describe the strengths and limitations of the
imperative, functional
and object-oriented paradigms for solving different
kinds of problems
(or in different application domains), especially in
relation to each
other.
Explain and answer questions about specific
languages that illustrate
different paradigms, including questions about
relevant concepts and
major features.
Design, define, and evaluate parts of programming
languages or similar
systems and justify your design decisions.
2016 Batch CSE 105
Academic Unit: Electrical Engineering
Level: UG
Programme: BTech
i Title of the course Machine Learning and Pattern
Recognition
ii Credit Structure (L-T-P-C) 3 0 0 6
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students) –
specify course number(s)
Exposure to Calculus or equivalent.
vii Course Content Recap
(a) Probability Theory, Linear
Algebra, Convex Optimization
Introduction to statistical decision
theory
(a) Hypothesis testing
(b) Regression, Classification, Bias
Variance trade-off
Regression and PCA
(a) Linear Regression, Multivariate
Regression,
(b) Subset Selection, Shrinkage
Methods,
(c) Principal Component Regression,
Partial Least squares
(d) Linear Classification, Logistic
Regression, Linear Discriminant
Analysis
Neural Networks
(a) Models of Neural Networks,
Learning laws, Perceptron
(b) Neural Networks - Introduction,
Early Models, Perceptron Learning,
activation and synaptic dynamics,
feed-forward neural network etc.
(c) Backpropagation, Initialization,
Training and Validation, Parameter
Estimation - MLE, MAP, Bayesian
Estimation
Graphical Models
(a) Undirected Graphical Models,
HMM, Variable Elimination, Belief
Propagation
(b) Bootstrapping and Cross
Validation, Class Evaluation
Measures, ROC curve, MDL
(c) Gaussian Mixture Models,
Expectation Maximization
Clustering
2016 Batch CSE 106
(a) Partitional Clustering, Hierarchical
Clustering, Birch Algorithm CURE
Algorithm, Density-based Clustering
viii Texts/References 1. Trevor Hastie, Robert Tibshirani,
Jerome H. Friedman “The Elements of
Statistical Learning,” Springer text in
statistics.
2. C. Bishop, “Pattern Recognition
and Machine Learning,” Springer text
in information science and statistics.
3. B. Yegnanarayana, “Artificial
Neural Networks,” Prentice Hall
Publications, 2005.
ix Name(s) of Instructor(s) S. R. M. Prasanna (Flip mode)
x Name(s) of other Departments/ Academic
Units to whom the course is relevant
EE, CSE, ME
xi Is/Are there any course(s) in the same/ other
academic unit(s) which is/ are equivalent to
this course? If so, please give details.
No
2016 Batch CSE 107
Name of Academic Unit: Electrical Engineering Level: B. Tech. / MS(R) / PhD
Programme: B.Tech. / MS(R) / PhD
i Title of the course Speech Processing
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be
offered
Autumn (July – Nov)
v Whether Full or Half Semester Course Full Semester Course
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content Introduction: speech production and perception,
nature of speech; Short-term processing: need,
approach, time, frequency and time-frequency
analysis.
Short-term Fourier transform (STFT): overview of
Fourier representation, non-stationary signals,
development of STFT, transform and filter-bank
views of STFT.
Cesptrum analysis: Basis and development, delta,
delta-delta and mel-cepstrum, homomorphic signal
processing, real and complex cepstrum.
Linear Prediction (LP) analysis: Basis and
development, Levinson-Durbin’s method,
normalized error, LP spectrum, LP cepstrum, LP
residual.
Sinusoidal analysis: Basis and development, phase
unwrapping, sinusoidal analysis and synthesis of
speech.
Applications: Speech recognition, speaker
recognition, speech synthesis, language and dialect
identification and speech coding.
viii Texts/References 1. L.R. Rabiner and R.W. Schafer, Digital Processing
of Speech Signals Pearson Education, Delhi, India,
2004
2. J. R. Deller, Jr., J. H. L. Hansen and J. G. Proakis
Discrete-Time Processing of Speech Signals, Wiley-
IEEE Press, NY, USA, 1999.
3. D. O’Shaughnessy, Speech Communications:
Human and Machine, Second Edition,University
Press, 2005.
4. T. F. Quatieri, “Discrete time processing of speech
signals”, Pearson Education, 2005.
5. L. R. Rabiner, B. H. Jhuang and B. Yegnanarayana,
“Fundamentals of speech recognition”, Pearson
Education, 2009.
2016 Batch CSE 108
ix Name(s) of Instructor(s) B. Yegnanarayana and S. R. M. Prasanna
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Computer Science and Engineering, Electrical
Engineering
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
This course aims at providing an overview to the
speech processing area. Speech processing being an
application area of signal processing and pattern
recognition, the same will be suitable for both
electrical engineering and computer science and
engineering students. The course contents include
introduction to speech processing, speech signal
processing methods like short term Fourier transform,
cepstral analysis, linear prediction analysis,
sinusoidal analysis. Some of the applications like
speech recognition and speech synthesis will also be
taught.
2016 Batch CSE 109
Name of Academic Unit: Electrical Engineering Level: B. Tech. / MS(R) / PhD
Programme: B.Tech. / MS(R) / PhD
i Title of the course Power System Dynamics and Control
ii Credit Structure (L-T-P-C) 2-0-1
iii Type of Course Elective
iv Semester in which normally to be
offered
Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Power System, Electrical Machines
vii Course Content Modelling of Synchronous Machines, Modelling of
Exciters, Small Signal Stability Analysis, Modelling
of Turbine and Governors, Simulation of Power
System Dynamic Response, Improvement of
Stability, Sub-synchronous Oscillations.
viii Texts/References 1. Power System Dynamics and Stability: With
Synchrophasor Measurement and Power System
Toolbox, 2nd Edition
2. Power System Stability and Control : Prabha
Kundur Mc GrawHill
3. Power System Dynamics and Stability, J
Machowski; J Bialek, J Bumby, John Wiley &
Sons
ix Name(s) of Instructor(s) Pratyasa Bhui
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
None
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
xii Justification/ Need for introducing the
course
This is an elective course for Power Systems Spine
2016 Batch CSE 110
Name of Academic Unit: Electrical Engineering Level: B. Tech. / MS(R) / PhD
Programme: B.Tech. / MS(R) / PhD
i Title of the course Wireless Communication
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Core
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Signals and Systems, Probability (UG level),
Principles/Fundamentals of Communications
vii Course Content Review of fundamentals in probability theory,
random processes, spectral analysis of deterministic
and random signals; review of digital modulation
schemes, optimal receiver design under additive
white Gaussian noise (AWGN) and error rate
performance; orthogonal frequency division
multiplexing (OFDM); channel modeling, capacity
and diversity techniques in wireless communication;
multi-input multi-output (MIMO) systems and space
time block codes (STBC); cellular communication
systems, multiple-access and interference
management.
viii Texts/References 1) David Tse and Pramod Viswanath,
“Fundamentals Of Wireless Communication,”
Cambridge University Press, 2005.
2) Andrea Goldsmith, “Wireless Communications,”
Cambridge University Press, 2005.
ix Name(s) of Instructor(s) Naveen M B
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Engineering Physics
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
None
xii Justification/ Need for introducing the
course
This is an elective course for Communications spine.
2016 Batch CSE 111
Name of Academic Unit: Computer Science & Engineering
Level: UG
Programme: B. Tech.
i Title of the course Artificial Neural Networks & Deep Learning
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content Background to ANN and PDP models; Basics of
ANN including terminology, topology and learning
laws; (4 lectures)
Analysis of Feedforward neural networks (FFNN)
including linear associative networks, perceptron
network, multilayer perceptron, gradient descent
methods and backpropagation learning; (8 lectures)
Analysis of Feedback neural networks (FBNN)
including Hopfield model, state transition diagram,
stochastic networks, Boltzmann learning law; (8
lectures)
Evolution of ANN architectures - from learning to
deep learning: (1 lecture)
viii Texts/References 1. B Yegnanarayana, Artificial Neural Networks,
Prentice Hall of India, New Delhi, 1999.
2. David E Rumelhart, James L McClelland, and the
PDP Research group, Eds, Parallel and Distributed
Processing: Explorations in Microstructure of
Cognition, Vol.1, Cambridge MA: MIT Press, 1986a
3. James L McClelland, David E Rumelhart and the
PDP Research group, Eds, Parallel and Distributed
Processing: Explorations in Microstructure of
Cognition, Vol.2, Cambridge MA: MIT Press, 1986b
4. James L McClelland, David E Rumelhart and the
PDP group, Eds, Explorations in Parallel and
Distributed Processing: A Handbook of Models,
Cambridge MA: MIT Press, 1989
5. Simon Haykin, Neural Networks and Learning
Machines, Pearson Education, 2011
6. Ian Goodfellow, Yoshua Bengio and Aaron
Courville, Deep learning, MIT Press, 2017
ix Name(s) of Instructor(s) SRMP
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
EE
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
Nil
2016 Batch CSE 112
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the
course
--
2016 Batch CSE 113
Name of Academic Unit: Mechanical Engineering
Level: B. Tech./Masters/PhD
Programme: B. Tech./Masters/PhD
i Title of the course Introduction to Combustion
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students)
– specify course number(s)
Exposure to Fluid Mechanics,
Thermodynamics, Heat transfer
vii Course Content Combustion thermodynamics: Stoichiometry,
Enthalpy of reaction, Adiabatic flame
temperature, Chemical equilibria
thermodynamics.
Chemical Kinetics: Arrhenius theory of
chemical reaction, Theories of reaction rate,
Equilibrium with kinetic approach,
Molecularity and order, Analysis of simple
reactions.
Transport processes in Combustion:
Momentum transport, heat transport, Mass
diffusion, conservation equations.
Premixed combustion: Explosion, detonation,
deflagration, 1-D combustion wave analysis,
Laminar premixed flames and burning
velocity, Introduction to turbulent premixed
flames.
Non-premixed combustion: Laminar jet
diffusion flames, Analysis of 2D diffusion
flames
viii Texts/References 1. Kuo, Kenneth K, Principles of
Combustion, 2nd Ed, Wiley Publication
2. Stephen R Turns, An Introduction to
Combustion: Concepts and Applications, 2nd
Ed, Mc Graw Hill Publication
3. Warren C Strahle, An Introduction to
Combustion, Combustion Science and
Technology Book Series, Gordon and Breach
Science Publishers
4. Law, C. K, Combustion physics, 2006,
Cambridge University press
5. Williams F. A, Combustion theory, 2nd Ed,
CRC Press
ix Name(s) of Instructor(s) R Santhosh
x Name(s) of other Departments/ Academic
Units to whom the course is relevant
-
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
No
2016 Batch CSE 114
Name of Academic Unit: Mechanical Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course Introduction to Computational Fluid Dynamics
ii Credit Structure (L-T-P-
C)
3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any
– specify course
number(s)
ME 203 Fluid Mechanics; Numerical Analysis; Computer
Programming
vii Course Content 1. Review of Governing Equations: General conservation
equation; specific mass, momentum, energy conservation
equations.
2. Fundamentals of Numerical Methods: Direct and iterative
solvers for linear equations; PDE, Classification, Basics of
finite-difference, finite-volume finite-volume methods;
Notion of accuracy, consistency, stability, convergence;
Verification and validation.
3. Diffusion Equation: 1-D steady conduction; Source terms
and non-linearity; 2-D steady conduction; Unsteady
conduction; Non-trivial boundary conditions.
4. Advection-Diffusion Equation: Steady 1-D advection-
diffusion equation; Upwinding, numerical diffusion, higher-
order schemes; 2-D advection-diffusion equation
5. Incompressible Navier-Stokes equations, Incompressibility
and pressure-velocity coupling; Staggered vs collocated
grids; SIMPLE and PISO algorithms.
6. Special Topics: Non-Cartesian coordinate systems;
Curvilinear grids; Unstructured grids; Advanced linear
solution methods such as multigrid methods,
preconditioning; Use of numerical libraries; Introduction to
parallel programming for CFD.
7. Mesoscopic approaches to discrete simulation of fluid
dynamics
8. Tutorial on a commercial CFD code & an open-source code
(e.g. OpenFOAM).
2016 Batch CSE 115
viii Texts/References 1. “An Introduction to Computational Fluid Dynamics”, by H. W.
Versteeg and W. Malalasekera; 2nd edition, Pearson Education Ltd.,
2007. (ISBN: 9780131274983)
2. “Introduction to Computational Fluid Dynamics: Development,
Application and Analysis”, by Atul Sharma; Wiley, 2016. (ISBN:
9781119002994)
ix Name(s) of Instructor(s) Dhiraj V Patil
x Name(s) of other Departments/ Academic Units to
whom the course is relevant
Departments of Mathematics,
Chemical, Civil, Physics
xi Is/Are there any course(s) in the same/ other
academic unit(s) which is/ are equivalent to this
course? If so, please give details.
NA
xii Justification/ Need for
introducing the course
CFD is an integral part of the design process in mechanical,
aerospace, and chemical industries, as well as a topic of active
research. Training at the undergraduate and early-postgraduate
level will enable students to take advantage of opportunities in
these areas.
The course aims to provide an introduction to discretization and
solution of the equations of fluid dynamics and heat transfer.
Students will gain an appreciation of the principles of the finite-
volume method, experience in writing and debugging scientific
codes, and solving and analysing a problem using a
commercial/open-source package. Students should expect to
devote significant time to learning via coding assignments and
project.
2016 Batch CSE 116
Name of Academic Unit : Mechanical Engineering
Level : B.Tech.
Programme : B.Tech.
i Title of the course FINITE ELEMENT ANALYSIS
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to
be offered
VII
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any (For the students) – specify course number(s) Mechanics of Materials
vi
i
Course
Content
*
Approximate solution of differential equations -- Weighted residual techniques. Collocation,
Least Squares and Galerkin methods. Piecewise approximations. Basis of Finite Element
Method. Formulation of the matrix method -- "stiffness matrix"; transformation and assembly
concepts. Example problems in one dimensional structural analysis, heat transfer and fluid
flow.
Elements of Variational calculus. Minimisation of a functional. Principle of minimum total
potential. Piecewise Rayleigh - Ritz method and FEM. Comparison with weighted residual
method.
Two dimensional finite element formulation. Isoparametry and numerical integration.
Algorithms for solution of equations. Convergence criteria, patch test and errors in finite
element analysis.
Finite element formulation of dynamics. Applications to free vibration problems. Lumped
and consistent mass matrices. Algorithms for solution of eigenvalue problems.
Vi
ii
Texts/Referen
ces REFERENCES
Bathe, K. J., Finite element procedures in Engineering Analysis, Prentice Hall of
India, 1990.
Cook, R.D., D. S. Malkus and M. E. Plesha, Concepts and Applications ofFinite
element analysis, John Wiley, 1989.
Reddy, J. N., An Introduction to the Finite Element Method, 2nd ed., McGraw
Hill, 1993.
Seshu, P. Finite Element Method, Prentice Hall of India, New Delhi, 2003.
Zienkiewicz, O. C., and K. Morgan, Finite elements and approximation, John
Wiley, 1983.
Zienkiewicz, O. C., and R. L. Taylor, The finite element method, vol.1&2, Tata
McGraw Hill.
ix Name(s) of Instructor(s) Prof. Seshu
x Name(s) of other Departments/ Academic Units to whom the course
is relevant
All
xi Is/Are there any course(s) in the same/ other academic unit(s) which
is/ are equivalent to this course? If so, please give details.
No
xi
i
Justification/ Need for
introducing the course
FEM is a numerical method to solve PDEs. The course introduces the
basic concepts and principles involved in FE formulation of PDEs.
Applications to domains spanning structural mechanics , fluid
mechanics and heat transfer are taken to illustrate the concepts
2016 Batch CSE 117
Name of Academic Unit : Mechanical Engineering
Level : B.Tech.
Programme : B.Tech.
i Title of the course Fatigue and Fracture Mechanics
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to
be offered
VII
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any (For the students) – specify course number(s) Mechanics of Materials and
TOE
vi
i
Course
Content
*
Module 1 (10 hours): Introduction and historical overview, Types of fatigue – low cycle
fatigue, high cycle fatigue, very high cycle (giga cycle) fatigue, Fatigue test methods and
equipment, Total life approaches based on cyclic stress and cyclic strain, Cyclic hardening and
softening in single crystals and polycrystals
Module 2 (10 hours): Crack initiation and propagation, Mechanisms, Macro-structural and
microstructural aspects, Use of fracture mechanics in fatigue
Module 3 (10 hours): Local strain approach, effect of different factors on fatigue – Stress
concentration, Size, Surface, Temperature, Frequency, Environment, Microstructure, Residual
stresses, Fretting, Creep-fatigue interaction, Multiaxial stresses, Thermomechanical loading,
Variable amplitude loading, Load sequence, Crack closure
Module 4 (10 hours): Fatigue behaviour of different materials – Metallic materials and
weldments, Ceramics, Polymers, Composites, Metallic glasses, Shape memory alloys,
Ultrafine grained materials, Nanocrystalline materials, Biomaterials, Metallic foams, Case
studies on fatigue failures, Design considerations, Methods for fatigue life improvement
Vi
ii
Texts/Referen
ces Suggested books:
Fatigue of Materials, Suresh, Cambridge India, 2015
Fracture Mechanics, Fundamentals and Applications, T.L. Anderson, CRC
Press 2017
ix Name(s) of Instructor(s) Prof. Nagesh R. Iyer
x Name(s) of other Departments/ Academic Units to whom the course
is relevant
All
xi Is/Are there any course(s) in the same/ other academic unit(s) which
is/ are equivalent to this course? If so, please give details.
No
xi
i
Justification/ Need for
introducing the course
The present course introduces to the behaviour of materials under
fatigue and fracture. Extending the design criteria based on strength and
stiffness, the course discusses life prediction of engineering materials
under fatigue and damage to present design criterion based on
toughness.
2016 Batch CSE 118
Name of Academic Unit: Mechanical Engineering
Level: B.Tech.
Programme: B.Tech.
i Title of the course Vibrations of Linear Systems
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be
offered
VII
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
None
vii Course Content Concepts of Vibrations: Harmonic motion and definitions
and terminology, Harmonic analysis, Fourier series
expansion, Importance of vibration, Basic concepts of
vibration, Classification of Vibration, Vibration analysis
procedure.
Characteristics of Discrete System Components, Equivalent
Springs, Dampers and Masses, Modeling of Mechanical
Systems, System Differential Equations of Motion, Nature of
Excitations, System and Response Characteristics –
Superposition Principle, Vibration about Equilibrium Point.
One DOF systems: Free Vibrations – Undamped and
damped vibrations, Harmonic Oscillator, Types of damping,
Viscously Damped Single DOF Systems, Measurement of
Damping, Coulomb Damping – Dry Friction.
Forced Vibrations – Response of Single DOF System to
Harmonic Excitations, Frequency Response Plots, Systems
with Rotating Unbalanced Masses, Whirling of Rotating
Shafts, Harmonic Motion of the Base, Vibration Isolation,
Vibration Measuring Instruments – Accelerometers,
Seismometers, Energy Dissipation, Structural Damping,
Response to Periodic Excitations, Fourier Series.
Response of Single DOF systems to Nonperiodic
Excitations, The Unit Impulse - Impulse Response, The Unit
Step Function - Step Response, The Unit Ramp Function -
Ramp Response, Response to Arbitrary Excitations - The
Convolution Integral, Shock Spectrum, System Response by
the Laplace Transformation Method -Transfer Function,
General System Response.
Two DOF Systems: System Configuration, Equations of
Motion-2 DOF Systems, Free Vibration of Undamped
2016 Batch CSE 119
Systems, Natural Modes, Response to Initial Excitations,
Coordinate Transformations – Coupling, Orthogonality of
Modes - Natural Coordinates, Beat Phenomenon, Response
of Two-Degree-of-Freedom Systems to Harmonic
Excitations, Undamped Vibration Absorbers.
Vibrations of Continuous Systems: Vibrating String,
Longitudinal vibrations of Bar, Torsional vibrations of Rod.
Lateral vibrations of Beam.
viii Texts/References TEXTBOOKS
1. S S Rao, Mechanical Vibrations, Pearson Education, 5th
Edition, 2004.
REFERENCES
1. W T Thomson, M D Dahleh and C Padmanabha, Theory
of Vibration with applications, Pearson Education, 2008. 2. Leonard Meirovitch, Fundamentals of Vibrations,
McGraw-Hill, 2000.
3. Den Hartog, Mechanical Vibrations, Dover Publications.
ix Name(s) of Instructor(s) Dr. Shrikanth V.
x Name(s) of other Departments/
Academic Units to whom the course
is relevant
Nil
xi Is/Are there any course(s) in the
same/ other academic unit(s) which
is/ are equivalent to this course? If so,
please give details.
No
xii Justification/ Need for introducing
the course
This course deals with the study of vibration in mechanical
systems which is concerned with the oscillatory motions of
bodies and the forces associated with them. This course aims to
provide you with an understanding of the nature and behaviour
of dynamic engineering systems and the capability of applying
the knowledge of mathematics, science, and engineering to
solve engineering vibration problems.
2016 Batch CSE 120
Name of Academic Unit: Mechanical Engineering
Level: B. Tech.
Programme: B. Tech.
i Title of the course ‘Composite Materials: Manufacturing, Properties &
Applications’
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content • Introduction: Definition and classification,
Importance of composites over other materials.
Revision of some mechanical properties.
• Reinforcements: Functions of reinforcements and
their forms,
Glass fibers: Production, composition and properties,
Production and properties of carbon and aramid
fibers, Ceramic particulate and whisker
reinforcements.
• Micromechanics: Estimation of modulus and tensile
strength. Prediction of thermal and electrical
properties
• Role of matrix and characteristics of different matrix
materials.
• Reinforcement-matrix Interfaces: wettability,
interactions at the interfaces. Mechanical, physical
and chemical bonding.
• Polymer matrix composites (PMC): Important
polymeric matrices,
Manufacturing methods: Unit operations, hand lay-
up, spray-up, pressure bag molding, vacuum bagging,
prepags, compression molding, autoclaving, RTM,
filament winding and pultrusion.
• Metal matrix composites (MMC): Property
advantages, comparison between MMCs & PMCs.
Manufacturing of MMCs: Solid state processes:
Diffusion bonding and P/M routes, Liquid state
processes: Melt-infiltration, stir casting, in-situ
processing, spray deposition and electrodeposition.
• Properties and applications of selected PMCs and
MMCs in industry.
• Ceramic matrix composites (CMC): Types of
CMCs, main processing methods, and important
applications.
• Introduction to Nanocomposites.
viii Texts/References Text Books:
2016 Batch CSE 121
(1) K.K. Chawla, ‘Composite Materials: Science and
Engineering’, 3rd Ed. Springer-Verlag, N.Y. (2012).
(2) F.L. Matthews and R.D. Rawlings, ’Composite
Materials: Engineering and Science’, CRC,
Woodhead Pub. Ltd., Cambridge, England (2008).
References:
(1) N. Chawla and K. K. Chawla, ’Metal Metrix
Composites’ 2nd Ed, Springer, N.Y. (2013).
(2) ASM Handbook Vol.21: Composites, Eds. D.B.
Miracle and S. L. Donaldson ,
ASM International, Ohio (USA) (2001).
ix Name(s) of Instructor(s) ANT
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
Nil
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
The objectives of the course are to provide the
students with -
• An understanding of basics of reinforcements,
matrices and composite materials.
• Structure, processing and properties of
reinforcements and matrix materials.
• Basic understanding of composite micromechanics
and interfacial bonding.
• Manufacturing methods and engineering
applications of Polymer-, metal- and ceramic- matrix
composites (PMC, MMC, &CMC).
• Introduction to nanocomposites and their
application.
2016 Batch CSE 122
Name of Academic Unit: Department of Physics
Level: UG
Programme: B.Tech
i Title of the Course Quantum Mechanics
ii Credit Structure (2-1-0-6)
iii Type of Course Core course
iv Semester in which
normally to be
offered
Autumn
v Whether Full or
Half Semester
Course Full
vi Pre-requisite(s), if
any (For the
students) – specify
course number(s)
PH101: Quantum Physics and Application I
MA106: Linear Algebra.
vii Course Content
Recap on Wave Particle duality, Heisenberg Uncertainty Relation,
Schrodinger Equation, Harmonic Oscillator.
Hydrogen atom
Dirac notations
Spin and Angular momentum algebra
Stern-Gerlach experiment
Wentzel–Kramers–Brillouin approximation
Time independent perturbation theory
Zeeman and Stark effect
Variational method
Density matrix representation
Pure and Mixed states
Superposition principle
Quantum measurement
C-bits and Qubits
Entanglement
Decoherence
Quantum logic gates
Introduction to quantum computation and quantum communications
viii Texts/References
(separate sheet
may be used, if
necessary)
Ajoy Ghatak and S. Lokanathan, Quantum Mechanics: Theory and
Applications, Trinity Press, New Delhi, 5th Edition, 2015.
R. Shankar, Principles of Quantum Mechanics, Springer; 2nd ed. 1994.
E. Merzbacher, Quantum Mechanics, Wiley, 1970 .
P.M. Mathews and K. Venkatesan, A text book of Quantum
Mechnanics, Tata McGraw Hill, 1976.
A. Messiah, Quantum Mechanics, North Holland, 2014.
Richard P. Feynman, Robert B. Leighton, and Matthew Sands, The
Feynman Lectures on Physics - Vol.3, Pearson Education, 1964.
L. Landau and E. Liftshitz, Quantum Mechanics, Pergamon 1965.
Leonard Susskind, Quantum Mechanics: The Theoretical Minimum,
Penguin, 2015.
Michael A. Nielsen and Isaac L. Chuang, Quantum Computation and
Quantum Information, Cambridge University Press, 2010.
ix Name(s) of
Instructor(s) R. Prabhu, Department of Physics
2016 Batch CSE 123
x Name(s) of other
Departments/
Academic Units to
whom the course is
relevant
NA
xi Is/Are there any
course(s) in the
same/ other
academic unit(s)
which is/ are
equivalent to this
course? If so,
please give details.
No
viii Justification/ Need
for introducing the
course
This course develops the necessary knowledge about Quantum Mechanics. It is
necessary for any students to undertake this course, this course will allow them
to know, how the first principles of quantum mechanics that they learnt in PH101
course, could be used to uncover many counter intuitive behaviour of Nature at
atomic scale and to understand several phenomena existing which are not
amenable to classical sense. The course will also try to introduce to the field of
quantum information which will forerun the technological developments in the
21st century.
2016 Batch CSE 124
Name of Academic Unit: Physics
Level: UG
Programme: B. Tech.
i Title of the course Astrophysics for Engineers
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be offered Spring
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content 1. a. An inventory of the Universe,
b. Celestial sphere, Coordinates
c. Units, sizes, masses and distance scale
2. Electromagnetic spectrum
a. Radio, Microwave, Infrared, Optical, X-ray and
Gamma Ray
b. Telescopes and Detectors
3. Stars
A. General
a. Sun, Planets, (Earth)
b. Mass, Radius, Luminosity, Temperature,
Chemistry, Age and Types of stars
c. Hertzsprung-Russell Diagram
d. Birth and Evolution of stars
c. Limits on Mass - Quantum mechanism at large
scale: Brown Dwarf
B: Structure of a star:
a. Virial Theorem (qualitative)
b. Nuclear Energy, Pressure, Interaction with
radiation.
c. Basic Equations of Stellar Structure
d. Thermal Equilibrium, Radiation and Convection
- Schwarzchild Criterion
e. Helioseismology
4. Galactic and Extragalactic Astronomy
a. The Milky Way and Andromeda
b. Rotation Curve - Dark Matter
c. Structures within 500 mega light years
d. Clusters of Galaxies, Superclusters, Filaments
and Voids
5. Special Topics:
a. White Dwarf - Quantum Mechanics and
Gravitation: Chandrasekhar limit
b. Supernova, Neutron Stars, (Pulsar astronomy),
c. Black Holes, Gravitational Wave Astronomy
d. Gamma Ray Burst
e. Quasars and Active Galactic Nuclei
6. Topics in Cosmology
2016 Batch CSE 125
a. Hubble Expansion - Cosmic Distance Scale - Age
of the Universe
b. Standard Model of Cosmology
c. Cosmic Microwave Background
d. Supernova Cosmology Project and Dark Energy
e. Gravitational Lens
7. Major Astronomical facilities where India is
involved:
GMRT, SKA, Thirty Metre Telescope, LIGO,
ASTROSAT
8. Open questions in Astrophysics and Cosmology
viii Texts/References 1. The New Cosmos (A. Unsold, B. Baschek)
2. An Introduction to Modern Astrophysics (B.W. Carroll,
D.A. Ostlie)
3. Elements of Cosmology (J.V. Narlikar)
ix Name(s) of Instructor(s) DN
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
All
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
Astrophysics and Cosmology have a few fundamental
unsolved problems. This course is an attempt to
convey to the students that there are upcoming
powerful astronomical facilities capable of solving
some of them. But both at hardware and software
level, it is Technology that drives what observations
are feasible. India is one of the main contributors for
development of some of the technologies.
2016 Batch CSE 126
Name of Academic Unit: Department of Physics
Level: UG
Programme: B. Tech
i Title of the Course Classical Electrodynamics
ii Credit Structure (2-1-0-6)
iii Type of Course Core Course
iv Semester in which
normally to be
offered
Autumn
v Whether Full or
Half Semester
Course
Full
vi Pre-requisite(s), if
any (For the
students) – specify
course number(s)
PH102 Electricity and Magnetism
MA 105 Calculus
vii Course Content
A review of Maxwell's equations, its scope and limitations. Microscopic,
Macroscopic fields and fields in materials.
Conservation laws, gauge transformations, Green's functions
Plane Electromagnetic Waves and Wave propagation
Waveguides, Resonant Cavities and Optical Fibres
Electromagneitc Radiation, multipoles, Antennae
Diffraction, Scattering, Dispersion, Reflection
Dynamics of Relativistic particles
Radiation from accelerated charges
viii Texts/References
(separate sheet
may be used, if
necessary)
J.D. Jackson: Claasical Elctrodynamics (Wiley student edition)
W K H Panofsky and M Philips: Classical Electricity and Magnetism
W Greiner: Classical Electrodynamics (Springer)
ix Name(s) of
Instructor(s) D Narasimha
x Name(s) of other
Departments/
Academic Units to
whom the course is
relevant
NA
xi Is/Are there any
course(s) in the
same/ other
academic unit(s)
which is/ are
equivalent to this
course? If so,
please give details.
No
viii Justification/ Need
for introducing the
course
This course is essential for the students who would opt for higher studies in
Physics and also useful for Electrical Engineering students opting for MS and
PhD . It will be provide formal background for Electrical Engineering students
studying topics such as wireless communications, optical fibres and so on.
2016 Batch CSE 127
Name of Academic Unit: Department of Physics
Level: B.Tech
Programme: B.Tech
i Title of the Course Quantum Field Theory
ii Credit Structure L T P C
2 1 0 6
iii Type of Course Elective
iv Semester in which
normally to be
offered
Autumn/Summer
v Whether Full or
Half Semester
Course
Full
vi Pre-requisite(s), if
any (For the
students) – specify
course number(s)
Successfully finishing first 3 Years of BTech Course
vii Course Content
Introduction:
Review of Classical field Theories and the need for Quantum
Field Theory
Bosonic Fields:
Second quantization of bosons; non-relativistic quantum
fields and the Landau Ginzburg theory; relativistic free
particles and the Klein-Gordon field; causality and the
Klein-Gordon propagator; quantum electromagnetic fields
and photons.
Fermionic Fields:
Second quantization of fermions; particle-hole formalism;
Dirac equation and its non-relativistic limit; quantum
Dirac field; spin-statistics theorem; Dirac matrix
techniques; Lorentz and discrete symmetries.
Interacting Fields and Feynman Rules:
Perturbation theory; correlation functions; Feynman
diagrams; S-matrix and cross-sections; Feynman rules for
fermions; Feynman rules for QED.
Functional Methods:
Path integrals in quantum mechanics; "path" integrals for
classical fields and functional quantization; functional
quantization of QED; QFT and statistical mechanics;
symmetries and conservation laws.
Quantum Electrodynamics:
Some elementary processes; radiative corrections;
infrared and ultraviolet divergencies; renormalization of
fields and of the electric charge; Ward identity.
Renormalization Theory:
2016 Batch CSE 128
Systematics of renormalization; `integration out' and the
Wilsonian renormalization; `running' of the coupling
constants and the renormalization group.
Non-Abelian Gauge Theories:
Non-abelian gauge symmetries; Yang-Mills theory;
interactions of gauge bosons and Feynman rules;
Fadde'ev-Popov ghosts and BRST; renormalization of the
YM theories and the asymptotic freedom; the Standard
Model.
viii Texts/References
(separate sheet
may be used, if
necessary)
“An Introduction to Quantum Field Theory”, Michael
Peskin and Daniel Schroeder (Addison Wesley)
“Introduction to Quantum Field Theory”, A. Zee
“Quantum Field Theory”, Lewis H. Ryder
“Quantum Field Theory and Critical Phenomena”, by Jean
Zinn-Justin.
“Quantum field Theory for the Gifted Amateur”, T.
Lancaster and Stephen J. Blundell
NPTEL lectures in Quantum Field Theory
(https://nptel.ac.in/courses/115106065/)
ix Name(s) of
Instructor(s) B L Tembe
x Name(s) of other
Departments/
Academic Units to
whom the course is
relevant
NA
xi Is/Are there any
course(s) in the
same/ other
academic unit(s)
which is/ are
equivalent to this
course? If so,
please give details.
No
viii Justification/ Need
for introducing the
course
Quantum Field Theory is one of the basic theories in physics which has met with
great success in explaining a large number of natural phenomena. This could be
of interest to most students with a desire to learn physics and mathematics and
who have a basic background in science in engineering of up to the third year of
IIT B.Tech courses.
2016 Batch CSE 129
Name of Academic Unit: Electrical Engineering Level: B. Tech. / MS(R) / PhD
Programme: B.Tech. / MS(R) / PhD
i Title of the course VLSI Design
ii Credit Structure (L-T-P-
C)
(3 0 0 6)
iii Type of Course Elective
iv Semester in which
normally to be offered
Autumn
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any
(For the students) –
specify course
number(s)
Digital systems
vii Course Content* Review of MOS transistor models, Technology scaling, CMOS
logic families including static, dynamic and dual rail logic.
Integrated circuit layout; design rules, parasitics. low power design,
high performance design, logical effort, Interconnect aware design,
clocking techniques.
VLSI design: data and control path design, floor planning, Design
Technology: introduction to hardware description
languages(VHDL), logic, circuit and layout verification.
Viii Texts/References 1. N. Weste and D. M. Harris, “CMOS VLSI Design, A
circuits and systems perspective” Pearson, 2010
2. S. Kang and Y. Leblebici, “CMOS Digital Integrated
circuits”, Tata McGraw Hill edition, 2003
3. Jan M. Rabaey, A. Chandrakasan and B. Nikolic,
“Digital Integrated circuits” Pearson , 2016
ix Name(s) of
Instructor(s) ***
NK
x Name(s) of other
Departments/ Academic
Units to whom the
course is relevant
xi Is/Are there any
course(s) in the same/
other academic unit(s)
which is/ are equivalent
to this course? If so,
please give details.
No
2016 Batch CSE 130
xii Justification/ Need for
introducing the course
Digital integrated circuits have revolutionized computers and the
way we control and design electronic systems. This is a advanced
course on CMOS digital integrated circuits, which gives exposure to
high performance VLSI design in CMOS technologies.
2016 Batch CSE 131
Name of Academic Unit: Electrical Engineering Level: B. Tech. / MS(R) / PhD
Programme: B.Tech. / MS(R) / PhD
i Title of the course Advanced Power Electronics &Drives
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Circuits, semiconductor devices and Electric
Machines &power electronics
vii Course Content Basics of semiconductor devices, gate drives for BJT,
MOSFET and IGBT, heat sink selection, snubber
circuits, non-isolated converters like buck, boost and
buck-boost converters, isolated converters like
forward, push pull, half bridge, full bridge and fly
back, design of magnetics for inductors and
transformers, inverters, PWM generation - SPWM,
space vector PWM, dq axis theory for 2 and 3 phase
applications. Introduction to electric drives, and speed
control of electric machines.
Design examples like, EV Battery chargers, and grid
connected PV inverter.
viii Texts/References 1. L. Umanand, Power electronics and applications, Wiley India Pvt. Limited, 2009.
2. Chryssis, G.C., High frequency switching power supplies, Second Edn, McGraw Hill, 1989.
3. R. W. Erickson, Dragan Maksimovic, Fundamentals of Power Electronics, Springer, 2001.
4. N.Mohan, Power Electronics: Converter, Applications & Design, John Wiley & Sons, 1989.
5. Ranganathan V T, Electric Drives, Course Notes, IISc, 2005-06.
6. Leonhard W., Control of Electrical Drives, 3rd Edition, Springer.
ix Name(s) of Instructor(s) Satish Naik
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
None
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
None
xii Justification/ Need for introducing the
course
This is an elective course for Power Systems Spine
2016 Batch CSE 132
Name of Academic Unit: Level: B. Tech./MS
Programme: B.Tech./MS
i Title of the course Basics of Accounting and Financial
Management
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be
offered
Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
None
vii Course Content Basics of financial accounting like accounting
principles, understanding balance sheet, profit
and loss account, cash flow statements, analysis
of financial performance. Basics of Managerial
Accounting cover introduction to managerial
accounting, cost classifications, C-V-P Analysis,
use of cost information for decision making;
Evolution of finance as an independent
subject;operating environment of finance
manager, fundamental concepts of finance: Risk
& Return and Time value of money: Capital
budgeting techniques: the concept of working
capital and working capital policy: management
of current assets and current liabilities
viii Texts/References 1. James Jiambalvo, Managerial Accounting,
Wiley India Edition
2. R Narayanaswamy, Financial Accounting-A
Managerial Perspective, PHI Learning
3. Prasanna Chandra, Fundamentals of
Financial Management, Tata McGraw Hill
Education Pvt Ltd Principles of Corporate
Finance-Richard A Brealey &Steward C
Myers (McGraw Hill Pubs)
4. James C Van Horne , Financial Management
and Policy, PHI Pubs
5. Ross, Westerfield & Jaffe , Corporate
Finance,Tata McGraw Hill
6. Aswath Damodaran, Corporate Finance-
Theory and Practice, John Wiley & Sons
7. Brigham & Houston, Fundamentals of
Financial Management, Thomson,
ix Name(s) of Instructor(s) Prof S N Rao
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
All departments as it is part of minor in
Management
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
No
2016 Batch CSE 133
give details.
xii Justification/ Need for introducing the
course
Accounting is the language of business. The
basic function of language is to serve as a means
of communication. Accounting also serves this
function. It communicates the results of business
operations to various parties who have some
stake in the business viz., the proprietor,
creditors, investors, Government and other
agencies. Finance covers any decision made by
firms which have financial implications. Thus,
there is finance aspect to almost every action
taken by a firm, no matter which functional area
claims responsibility for it.
Knowledge of management, particularly
accounting and finance, is an important value
addition to engineering graduates .It enhances
their placement opportunities.
2016 Batch CSE 134
Name of Academic Unit: Department of Physics
Level: B.Tech
Programme: B.Tech
i Title of the Course Statistical Mechanics
ii Credit Structure L T P C
2 1 0 6
iii Type of Course Elective
iv Semester in which
normally to be
offered
Autumn/Summer
v Whether Full or
Half Semester
Course
Full
vi Pre-requisite(s), if
any (For the
students) – specify
course number(s)
Successfully finishing first 3 Years of B. Tech Course
vii Course Content
0. Introduction: Review of Classical Mechanics
and Quantum Mechanics
1. Thermodynamics:
Thermal equilibrium, the laws of thermodynamics;
temperature, energy, entropy, and other functions of state.
2. Probability Theory: Probability densities, cumulants and
correlations; central limit theorem; laws of large numbers.
3. Kinetic Theory: Phase space densities; Liouville's
theorem, BBGKY hierarchy, the Boltzmann equation;
transport phenomena.
4. Classical Statistical Mechanics: Postulates;
microcanonical, canonical and grand canonical ensembles;
non-interacting examples.
5. Interacting Systems: Virial and cluster expansions; van
der Waals theory; liquid-vapor condensation.
6. Quantum Statistical Mechanics: Quantization effects in
molecular gases; phonons, photons; density matrix
formulation.
7. Identical Particles: Degenerate quantum gases; Fermi
liquids; Bose condensation; superfluidity.
8. Molecular Partition Functions: Translational, rotational
and vibrational partition functions, equilibrium constants
of chemical reactions in terms of partition functions.
9. Liquid state theories: Classical theories of spatial and
time correlation functions. Thermodynamic and kinetic
parameters in terms of spatial and time correlation
functions. Brownian motion and the Langevin equation.
2016 Batch CSE 135
10. Lattice Models and the Renormalization Group: Lattice
Models and their exact solutions. Introduction to the
renormalization group.
11. Computer Simulations: Classical molecular dynamics
and Monte Carlo Simulations.
viii Texts/References
(separate sheet
may be used, if
necessary)
Huang, Kerson. Statistical Mechanics. 2nd ed. Wiley1987
Pathria, R. K. Statistical Mechanics. Pergamon Press, 1972.
Landau, L. D., and E. M. Lifshitz. Statistical Physics, Part 1.
3rd ed. Pergamon Press, 1980
Reif, Frederick, ed. Fundamentals of Statistical and Thermal
Physics. McGraw-Hill, 1965.
Feynman, Richard Phillips. Statistical Mechanics: A Set of
Lectures. Westview Press, 1998.
McQuarrie D. A., Statistical Mechanics
Hansen J. P. and McDonald I. R., Theory of Simple Liquids,
4th Edition, Academic Press
Allen M. P. and Tildesley D. J., Computer Simulation of
Liquids, Oxford, 2nd Edition
ix Name(s) of
Instructor(s) B L Tembe
x Name(s) of other
Departments/
Academic Units to
whom the course is
relevant
Chemistry/Physics and Biology
xi Is/Are there any
course(s) in the
same/ other
academic unit(s)
which is/ are
equivalent to this
course? If so,
please give details.
No
viii Justification/ Need
for introducing the
course
Statistical Mechanics attempts to understand macroscopic phenomena based on
a small number of postulates and models of the interactions between particles. It
provides a good basis for thermodynamics as well. This could be of interest to
most students with a desire to learn physics, chemistry and theoretical biology
2016 Batch CSE 136
and who have a basic background in science in engineering of up to the third
year of IIT B.Tech courses.