Courses
Dual Degree (CSE)
Course Structure of Dual Degree (CSE)
Semester  Course Code  Course name  LTPCredit  Offering Department  
Semester I  CE111  Engineering Drawing  1035  Civil  
EE101  Electrical Sciences  3108  Electrical  
HS103  Communicative English for Engineers  20.516  Humanities and Social Science  
MA101  Mathematics I  3108  Mathematics  
ME110  WorkshopI  0033  Mechanical  
PH103  Physics –I  3108  Physics  
PH 110  Physics Laboratory  0033  Physics  
Total credits: 41  
Semester II  CB102&CE102  Biology and Environmental Studies  3006  CB & CE  
CH103  Introductory Chemistry  3108  Chemistry  
CH110  Chemistry Laboratory  0033  Chemistry  
CS102  Programming and Data Structures  3006  CS  
CS112  Programming and Data Structures Laboratory  0033  CS  
EE103  Basic Electronics Laboratory  0033  EE  
MA102  Mathematics –II  3108  Mathematics  
ME102  Engineering Mechanics  3108  ME  
Total credits: 45  
Semester III  MA2XX  Mathematics III  3006  Mathematics  
HS2XX  HSS Elective – I  3006  Humanities and Social Science  
CS204  Algorithms  3006  CS  
CS224  Algorithms Laboratory  0033  CS  
CS203  Discrete Mathematics  3006  CS  
CS227  Digital Systems  2026  CS  
MAXXX  Optimization techniques  3006  Mathematics  
CS230  Software Lab/Tools  0033  CS  
Total credits: 42  
Semester IV  HS2XX  HSS Elective – II  3006  Humanities and Social Science  
XX2XX  Open Elective I (Prob. Theory and Random Processes)  3006  Mathematics  
CS321  Computer Architecture  3006  CS  
CS322  Computer Architecture Lab  0033  CS  
CS2XX  Theory of computation  3006  CS  
CS354  Database  3006  CS  
CS355  Database Lab  0033  CS  
Total credits: 36  
Semester V  XX3XX  Open ElectiveII  3006  Science/Egg.  
CS3XX  Computer Network  3006  CS  
CS3XX  Computer Network Lab  0033  CS  
CS3XX  Operating Systems  3006  CS  
CS3XX  Operating Systems Lab  0033  CS  
CS3XX  AlgorithmII  3006  CS  
CS3XX  Innovative Design Lab  0033  CS  
Total credits: 33  
Semester VI  HS3XX  HSS Elective–III  3006  Humanities and Social Science  
CS3XX  CS ElectiveI  3006  CS  
CS3XX  PPL + Compiler  3006  CS  
CS3XX  PPL + Compiler Lab  0033  CS  
CS3XX  Artificial Intelligence  3006  CS  
CS3XX  Artificial Intelligence Lab  0033  CS  
CSXXX  Machine Learning & DS  3006  CS  
CS3XX  Capstone Project  0033  CS  
Total credits: 39  
Semester VII 
CS4XX/CS5XX  Open Elective – III  3006  
CS4XX/CS5XX  CS ElectiveII  3006  CS  
CS4XX/CS5XX  CS ElectiveIII  3006  CS  
CS4XX/CS5XX  CS Elective – IV  3006  CS  
CS4XX/CS5XX  CS Elective – V  3006  CS  
CS4XX/CS5XX  ProjectI  0088  CS  
Total credits: 38  
Semester VIII  CS4XX/CS5XX  CS ElectiveVI  3006  CS  
CS4XX/CS5XX  CS ElectiveVII  3006  CS  
CS4XX/CS5XX  CS Elective VIII  3006  CS  
CS4XX/CS5XX  CS Elective IX  3006  CS  
CS4XX/CS5XX  ProjectII  001212  CS  
Total credits: 36  
Semester IX  CS5XX/CS7XX  CS ElectiveX  3006  CS  
CS5XX/CS7XX  CS Elective XI  3006  CS  
CS5XX/CS7XX  CS Elective XII  3006  CS  
CS5XX/CS7XX  ProjectIII  001818  CS  
Total credits: 36  
Semester X  CS5XX/CS7XX  CS ElectiveXIII  3006  CS  
CS5XX/CS7XX  CS Elective XIV  3006  CS  
CS5XX/CS7XX  ProjectIV  002222  CS  
Total credits: 34  
Total credits for Dual Degree CS: 380 
DETAILED SYLLABUS
Semester I
Geometrical construction of simple plane figure: Bisecting the line, draw perpendicular, parallel line, bisect angle, trisect angle, construct equatorial triangle, square, polygon, inscribed circle. Free hand sketching: prerequisites for freehand sketching, sketching of regular and irregular figures. Drawing scales: Engineering scale, graphical scale, plane scale, diagonal scale, comparative scale, scale of chord. Orthographic projection: Principle of projection, method of projection, orthographic projection, plane of projection, first angle of projection, third angle of projection, reference line. Projection of points, lines and plane: A point is situated in the first quadrant, point is situated in the second quadrant, point is situated in the third quadrant, point is situated in the fourth quadrant, projection of line parallel to both the plane, line contained by one or both the plane, line perpendicular to one of the plane, line inclined to one plane and parallel to other, line inclined to both the plane, true length of line. Missing views: Drawing of missing front view of a solid, missing top view of solids, missing side view of solids, Orthographic projection of simple solid: Introduction, types of solid, projection of solid when axis perpendicular to HP, axis perpendicular to VP, axis parallel to both HP and VP, axis inclined to both HP and VP. Orthographic projection of simple solid: Introduction, types of solid, projection of solid when axis perpendicular to HP, axis perpendicular to VP, axis parallel to both HP and VP, axis inclined to both HP and VP. Text and Reference Books:

Circuit Analysis Techniques, Circuit elements, Simple RL and RC Circuits, Kirchhoff’s law, Nodal Analysis, Mesh Analysis, Linearity and Superposition, Source Transformations, Thevnin's and Norton's Theorems, Time Domain Response of RC, RL and RLC circuits, Sinusoidal Forcing Function, Phasor Relationship for R, L and C, Impedance and Admittance. Semiconductor Diode, Zener Diode, Rectifier Circuits, Clipper, Clamper, Bipolar Junction Transistors, Transistor Biasing, Transistor Small Signal Analysis, Transistor Amplifier, Operational Amplifiers, Opamp Equivalent Circuit, Practical Opamp Circuits, DC Offset, Constant Gain Multiplier, Voltage Summing, Voltage Buffer, Controlled Sources, Instrumentation Circuits, Active Filters and Oscillators. Number Systems, Logic Gates, Boolean Theorem, Algebraic Simplification, Kmap, Combinatorial Circuits, Encoder, Decoder, Combinatorial Circuit Design, Introduction to Sequential Circuits. Magnetic Circuits, Mutually Coupled Circuits, Transformers, Equivalent Circuit and Performance, Analysis of ThreePhase Circuits, Electromechanical Energy Conversion, Introduction to Rotating Machines. Text and Reference Books:

In today’s ‘global village’, there are many who believe that ‘Communication is like breathing and life would cease to continue without it’. This particular course on communication skills imbibes the same and therefore, it aims to equip the students with getting the basics right of communication and presentation skills for academic and professional purposes. It is designed to help the second language learners acquire fluency in both spoken and written English to communicate information with clarity, precision and confidence especially in the professional sphere. It will introduce learners not only to the basic concepts in communication but also focus on providing them a handson experience of the same. It is hoped that after commanding the skills required in spoken and written English, learners will be able to express themselves more effectively. The course will have ten units and shall focus on the following topics: Unit 1: Language and Communication What is Communication Nature, Style and Process of Communication Communication Barriers Objectives and Importance of Communication Formal and Informal Communication Verbal and Non Verbal Communication Unit 2: English Language Remedial Skills Construction of Sentences SubjectVerb Agreement Tenses Active and Passive Voice Direct and Indirect Speech Common Errors Unit 3: Oral Skills Public Speaking Dealing with lack of confidence Making an Effective Presentation Telephone Etiquette Understanding GD Why conduct a GD? How to gear up for a GD? Different Phases of GD Unit 4: Listening Skills Meaning of Listening Different Types of Listening Barriers to Listening and Methods to overcome them Various strategies to develop effective Listening Semantic Markers Unit 5: Reading Skills What is Reading? Types of Reading Reading Comprehension Unit 6: Writing Skills Business Correspondence Element and Style of Writing Report Writing Notice, Agenda and Minutes Unit 7: Interview Techniques How to prepare for an Interview An Interview Text and Reference Books:

Properties of real numbers. Sequences of real numbers, monotone sequences, Cauchy sequences, divergent sequences. Series of real numbers, Cauchy’s criterion, tests for convergence. Limits of functions, continuous functions, uniform continuity, monotone and inverse functions. Differentiable functions, Rolle's theorem, mean value theorems and Taylor's theorem, power series. Riemann integration, fundamental theorem of integral calculus, improper integrals. Application to length, area, volume, surface area of revolution. Vector functions of one variable and their derivatives. Functions of several variables, partial derivatives, chain rule, gradient and directional derivative. Tangent planes and normals. Maxima, minima, saddle points, Lagrange multipliers, exact differentials. Repeated and multiple integrals with application to volume, surface area, moments of inertia. Change of variables. Vector fields, line and surface integrals. Green’s, Gauss’ and Stokes’ theorems and their applications. Text Books:
Reference Books:

Sheet Metal Working: Sheet material: GI sheets, aluminum, tin plate, copper, brass etc.; Tools: steel rule, vernier calipers, micrometer, sheet metal gauge, scriber, divider, punches, chisels, hammers, snips, pliers, stakes etc.; operations: scribing, bending, shearing, punching etc.; Product development: hexagonal box with cap, funnel etc. Pattern Making and Foundry Practice: Pattern material: wood, cast iron, brass, aluminum, waxes etc.; Types of patterns: split, single piece, match plate etc.; Tools: cope, drag, core, core prints, shovel, riddle, rammer, trowel, slick, lifter, sprue pin, bellow, mallet, vent rod, furnace etc. Moldings sands: green sand, dry sand, loam sand, facing sand etc., Sand casting: Sand preparation, mould making, melting, pouring, and cleaning. Joining: Classifications of joining processes; Introduction to Arc welding processes; power source; electrodes; edge preparation by using tools bench vice, chisels, flat file, square file, half round file, round file, knife edge file, scrapers, hacksaws, try squares; cleaning of job, Job: lap and butt joints using manual arc welding. Machining centre: Introduction to different machine tools; Working principle of lathe, milling, drilling etc.; Setting and preparation of job using lathe and milling; Performing different operations namely, straight turning, taper turning, knurling, thread cutting etc.; Introduction to dividing head, indexing, performing operation in milling using indexing mechanism. CNC centre: Introduction to CNC machines; Fundamentals of CNC programming using G and M code; setting and operations of job using CNC lathe and milling, tool reference, work reference, tool offset, tool radius compensation. Text and Reference Books:

Orthogonal coordinate systems and frames of reference, conservative and nonconservative forces, workenergy theorem, potential energy and concept of equilibrium; Rotation about fixed axis, translationalrotational motion, vector nature of angular velocity, rigid body rotation and its applications, Euler's equations; Gyroscopic motion and its application; Accelerated frame of reference, centrifugal and Coriolis forces. Harmonic oscillator damped and forced oscillations, resonance, coupled oscillations, small oscillation, normal modes, longitudinal and transverse waves, wave equation, plane waves, phase velocity, superposition wave packets and group velocity, two and three dimensional waves. Failure of classical concepts, Black body radiation, photoelectric effect, Compton effect, Davison and Germer's experiment, FrankHertz experiment, Bohr's theory, Sommerfeld's model, correspondence principle, Planck hypothesis, De Broglie's hypothesis, Hilbert space, observables, Dirac notation, principle of superposition, wave packets, phase and group velocities, probability & continuity equation, eigenvalues and eigen functions, orthonormality, expectation values, uncertainty principle, postulates of Quantum Mechanics, Schrodinger equation & its applications to 1D potentials, field quantization, periodic potential wells: Kronig Penny model and origin of band gap. Textbooks:

Ex 1 Decay of Current in A Capacitive Circuit Ex 2 QFactor of an LCR Circuit Ex 3 Study of Hall Effect Ex 4 Speed of Sound in Air Ex 5 ‘g’ by A Compound Pendulum Ex 6 Speed of Light in Glass Ex 7 Determination of e/m Ex 8 Interference of Light: Newton’s Ring Ex 9 Surface Tension of Water by Method of Capillary Ascent Ex 10 Determination of Plank’s constant by Photoelectric Effect 
Semester II
Module 1  Biology: 1. Cell – Structure and logic of optimization; 2. Blood – The following tissue – Basis and rationale; 3. Organs – Structure, function, interactions, failure; 4. Molecular basis of disorders – example: Diabetes; 5. Modern techniques of evaluations and corrections; 6. Open discussions – Feedback from students Module 2 – Environmental Science / Studies: 1.Ecology and Sustainable Development – Ecosystems, Natural cycles, Biodiversity, Man and environment; 2. Water Resources – Hydrologic cycle and its components, Groundwater and surface water, Water quality; 3. Environmental Sanitation: Conventional and ecological sanitation; 4. Environmental Pollution and Control – Air, Water, Soil, Noise Pollution, Solid and Hazardous Waste, Biomedical Waste, Ewaste: Sources, effect, treatment and control; 5. Environmental Legislations and Standards; 6.Current Environmental Issues: Greenhouse gases and global warming, Acid rain, Ozone layer depletion, Climate change Text Books:

PHYSICAL CHMEISTRY Thermodynamics: The fundamental definition and concept, the zeroth and first law. Work, heat, energy and enthalpies. Second law: entropy, free energy and chemical potential. Change of Phase. Third law. Chemical equilibrium, Chemical kinetics: The rate of reaction, elementary reaction and chain reaction. Electrochemistry: Conductance of solutions, equivalent and molar conductivities and its variation with concentration. Kohlrausch’s lawionic mobilities, Transference number of ions. activities, application of DebyeHuckel theory. The Walden’s rule. DebyeHuckelOnsager treatment. Electrochemical cells, Nernst equation. Application of EMF measurements. Liquid junction potential, commercial cells – the primary and secondary cells. Fuel cells. INORGANIC CHEMISTRY Coordination chemistry: ligand, nomenclature, isomerism, stereochemistry, valence bond, crystal field and molecular orbital theories. Bioinorganic chemistry: Trace elements in biology, heme and nonheme oxygen carriers, hemoglobin and myoglobin; organometallic chemistry. ORGANIC CHEMISTRY Stereo and regiochemistry of organic compounds, conformers. Bioorganic chemistry: amino acids, peptides, proteins, enzymes, carbohydrates, nucleic acids and lipids. Modern techniques in structural elucidation of compounds (UV – Vis, IR, NMR). Solid phase synthesis and combinatorial chemistry. Green chemical processes. Textbooks: P. W. Atkins, Physical Chemistry, ELBS, 5th Ed, 1994. J. O'M. Bockris and A. K. N. Reddy, Modern Electrochemistry, Vol. 1 and 2, Kluwer Academic, 2000. K. L. Kapoor, A Textbook of Physical Chemistry, Macmillan India, 2nd Ed, 1986. F. A. Cotton and G. Wilkinson, Advanced Inorganic Chemistry, Wiley Eastern Ltd, New Delhi, 3rd Ed, 1972 (reprint in 1998). D. J. Shriver, P. W. Atkins and C. H. Langford, Inorganic Chemistry, ELBS, 2nd Ed, 1994. S. H. Pine, Organic Chemistry, McGraw Hill, 5th Ed, 1987 Reference Books: Levine, Physical Chemistry, McGraw Hill, 4th Ed, 1995. J. E. Huheey, E. A. Keiter and R. L. Keiter, Inorganic Chemistry: Principle, structure and reactivity, Harper Collins, 4th Ed, 1993. L. G. Wade Jr., Organic Chemistry, Prentice Hall, 1987 
Estimation of metal ion: Determination of total hardness of water by EDTA titration. Experiments based on chromatography: Identification of a mixture containing two organic compounds by TLC. Experiments based on pH metry.: Determination of dissociation constant of weak acids by pH meter. Experiments based on conductivity measurement: Determination of amount of HCl by conductometric titration with NaOH. Synthesis and characterization of inorganic complexes: e.g. Mn(acac)3, Fe(acac)3, cisbis(glycinato)copper(II) monohydrate and their characterization by m. p. IR etc. Synthesis and characterization of organic compounds: e.g. Dibenzylideneacetone. Kinetics: Acid catalyzed hydrolysis of methylacetate. Verification of BeerLamberts law and determination of amount of iron present in a supplied solution. Experiments based on electrogravimetry and electroplating. Experiments based on magnetometry. 
Introduction to digital computers; introduction to programming  variables, assignments; expressions; input/output; conditionals and branching; iteration; functions; recursion; arrays; introduction to pointers; structures; introduction to dataprocedure encapsulation; dynamic allocation; linked structures; introduction to data structures stacks, queues and trees; time and space requirements. References: 1. B. W. Kernighan and D. Ritchie, The C Programming Language, Prentice Hall of India (2nd Edition). 2. A. Kelley and I. Pohl, A Book on C, Pearson Education (4th Edition). 3. P.J. Deitel and H.M. Deitel , C How To Program, Pearson Education (7th Edition). 
Introduction to Unix Commands; Introduction to Program development tools  vi editor, GNU compiler, testing and debugging, etc.; Implementation of programs in C language. 
Experiments using diodes and bipolar junction transistor (BJT): design and analysis of half wave and fullwave rectifiers, clipping circuits and Zener regulators, BJT characteristics and BJT amplifiers; experiments using operational amplifiers (opamps): summing amplifier, comparator, precision rectifier, a stable and mono stable multivibrators and oscillators; experiments using logic gates: combinational circuits such as staircase switch, majority detector, equality detector, multiplexer and demultiplexer; experiments using flipflops: sequential circuits such as non overlapping pulse generator, ripple counter, synchronous counter, pulse counter and numerical display. Reference Books:
India, 2002.


Linear Algebra: Vector spaces (over the field of real and complex numbers). Systems of linear equations and their solutions. Matrices, determinants, rank and inverse. Linear transformations. Range space and rank, null space and nullity. Eigenvalues and eigenvectors. Similarity transformations. Diagonalization of Hermitian matrices. Bilinear and quadratic forms. Ordinary Differential Equations: First order ordinary differential equations, exactness and integrating factors. Variation of parameters. Picard's iteration. Ordinary linear differential equations of nth order, solutions of homogeneous and nonhomogeneous equations. Operator method. Method of undetermined coefficients and variation of parameters. Power series methods for solutions of ordinary differential equations. Legendre equation and Legendre polynomials, Bessel equation and Bessel functions of first and second kind. Systems of ordinary differential equations, phase plane, critical point stability. Textbooks:
Reference Books:


Semester III
Complex Analysis: Complex numbers, geometric representation, powers and roots of complex numbers. Functions of a complex variable: Limit, Continuity, Differentiability, Analytic functions, CauchyRiemann equations, Laplace equation, Harmonic functions, Harmonic conjugates. Elementary Analytic functions (polynomials, exponential function, trigonometric functions), Complex logarithm function, Branches and Branch cuts of multiple valued functions. Complex integration, Cauchy's integral theorem, Cauchy's integral formula. Liouville’s Theorem and MaximumModulus theorem, Power series and convergence, Taylor series and Laurent series. Zeros, Singularities and its classifications, Residues, Rouches theorem (without proof), Argument principle (without proof), Residue theorem and its applications to evaluating real integrals and improper integrals. Conformal mappings, Mobius transformation, SchwarzChristoffel transformation. Fourier series: Fourier Integral, Fourier series of 2p periodic functions, Fourier series of odd and even functions, Halfrange series, Convergence of Fourier series, Gibb’s phenomenon, Differentiation and Integration of Fourier series, Complex form of Fourier series. Fourier Transformation: Fourier Integral Theorem, Fourier Transforms, Properties of Fourier Transform, Convolution and its physical interpretation, Statement of Fubini’s theorem, Convolution theorems, Inversion theorem Partial Differential Equations: Introduction to PDEs, basic concepts, Linear and quasilinear first order PDE, Second order PDE and classification of second order semilinear PDE, Canonical form. Cauchy problems. D’ Alembert’s formula and Duhamel’s principle for one dimensional wave equation, Laplace and Poisson equations, Maximum principle with application, Fourier method for IBV problem for wave and heat equation, rectangular region. Fourier method for Laplace equation in three dimensions. Text Books: 1. R. V. Churchill and J. W. Brown, Complex Variables and Applications, 5th Edition, McGrawHill, 1990. 2. K. Sankara Rao, Introduction to Partial Differential Equations, 2nd Edition, 2005. Reference Books: 3. J. H. Mathews and R. W. Howell, Complex Analysis for Mathematics and Engineering, 3rd Edition, Narosa, 1998. 4. I. N. Sneddon, Elements of Partial Differential Equations, McGrawHill, 1957. E. Kreyszig, Advanced Engineering Mathematics, 9th Edition, Wiley, 2005. 
Asymptotic notations, introduction to complexity (time/space) analysis of algorithms. Basic introduction to algorithmic paradigms like divide and conquer, recursion, greedy, dynamic programming, etc. Searching: binary search trees, balanced binary search trees, AVL trees and redblack trees, Btrees, hashing. Priority queues, heaps, Interval trees. Sorting: quick sort, heap sort, merge sort, radix sort, bucket sort, counting sort, etc and their analysis. Graph Algorithms: BFS, DFS, connected components, topological sort, minimum spanning trees, shortest paths, network flow. Reducibility between problems and NPcompleteness: discussion of different NPcomplete problems. Books M. A. Weiss, Data Structures and Problem Solving Using Java, 2nd Ed, AddisonWesley, 2002. T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, Introduction to Algorithms, MIT Press, 2001. B. W. Kernighan and D. Ritchie, The C Programming Language, 2nd Ed, Prentice Hall of India, 1988. A. Aho, J. E. Hopcroft and J. D. Ullman, The Design and Analysis of Computer Algorithms, AddisonWesley, 1974. S. Sahni, Data Structures, Algorithms and Applications in C++, McGrawHill, 2001. M. T. Goodrich and R. Tamassia, Algorithm Design: Foundations, Analysis and Internet Examples, John Wiley & Sons, 2001. 
The laboratory component will emphasize two areas: Implementation of algorithms covered in class: This will involve running the algorithms under varying input sets and measuring running times, use of different data structures for the same algorithm (wherever applicable) to see its effect on time and space, comparison of different algorithms for the same problem etc. Design of Algorithms: This will involve design and implementation of algorithms for problems not covered in class but related to topics covered in class. The exact set of algorithms to design and implement is to be decided by the instructor. In addition, there will be at least one significantly large design project involving some real world application. An efficient design of the project should require the use of multiple data structures and a combination of different algorithms/techniques. The lab work can be carried out using any programming language. 
Propositional logic: Syntax, semantics, valid, satisfiable and unsatisfiable formulas, encoding and examining the validity of some logical arguments; Recurrences, summations, generating functions, asymptotic; Sets, relations and functions: Operations on sets, relations and functions, binary relations, partial ordering relations, equivalence relations, principles of mathematical induction, Finite and infinite sets, countable and uncountable sets, Cantor’s diagonal argument and the power set theorem; Introduction to counting: Basic counting techniques  inclusion and exclusion, pigeonhole principle, permutation, combination, generating function; Algebraic structures and morphisms: semigroups, groups, subgroups, homomorphism, rings, integral domains, fields; Introduction to graphs: paths, connectivity, subgraphs, isomorphic and homeomorphic graphs, trees, complete graphs, bipartite graphs, matchings, colourability, planarity, digraphs; Text Books: 1. J. P. Tremblay and R. P. Manohar, Discrete Mathematics with Applications to Computer Science, Tata McGrawHill, 1999. 2. C. L. Liu, Elements of Discrete Mathematics, 2nd Ed, Tata McGrawHill, 2000. 3. R. L. Graham, D. E. Knuth, and O. Patashnik, Concrete Mathematics, 2nd Ed, AddisonWesley, 1994. 4. N. Deo, Graph Theory with Applications to Engineering and Computer Science, Prentice Hall of India, 1974. 5. S. Lipschutz and M. L. Lipson, Schaums Outline of Theory and Problems of Discrete Mathematics, 2ndEd, Tata McGrawHill, 1999 
Number Systems, Boolean algebra, logic gates, minimization of completely and incompletely specified switching functions, Karnaugh map and QuineMcCluskey method, multiple output minimization, twolevel and multilevel logic circuit synthesis. Clocks, flipflops, latches, counters and shift registers, finite state machine model, synthesis of synchronous sequential circuits, minimization and state assignment, Programmable logic devices: memory design. Data path control path partitionbased design. Experiments: Combinational logic circuits: Design and implementation of combinational circuits such as ALU and 7segment LED display driver; Sequential Circuits: Design of sequence generators and detectors, counters, design of ASMs such as, traffic light controllers, lift controllers, etc. Digital design project: The students design and implement a final digital project of their choice.
References: 
Linear programming: Introduction and Problem formulation, Concept from Geometry, Geometrical aspects of LPP, Graphical solutions, Linear programming in standard form, Simplex, Big M and Two Phase Methods, Revised simplex method, Special cases of LPP. Duality theory: Dual simplex method, Sensitivity analysis of LP problem, Transportation, Assignment and travelling salesman problem. Integer programming problems: Branch and bound method, Gomory cutting plane method for all integers and for mixed integer LPP. Theory of games: saddle point, linear programming formulation of matrix games, twoperson zerosum games with and without saddlepoints, pure and mixed strategies, graphical method of solution of a game, solution of an game by simplex method. Computational complexity of the Simplex algorithm, Karmarkar's algorithm for LPP. Acquaintance to softwares like TORA and MATLAB. Text Books: 1. Hamdy A. Taha, Operations Research: An Introduction, Eighth edition, PHI, New Delhi (2007). 2. S.Chandra, Jayadeva, AparnaMehra, Numerical Optimization with Applications, Narosa Publishing House (2009). 3. A. Ravindran, D.T. Phillips, J.J. Solberg, Operation Research, John Wiley and Sons, New York (2005). 4. M. S. Bazaraa, J. J. Jarvis and H. D. Sherali, Linear Programming and Network Flows, 3rd Edition, Wiley (2004). Reference Books: 1. D. G. Luenberger, Linear and Nonlinear Programming, 2nd Edition, Kluwer, (2003). 2. S. A. Zenios (editor), Financial Optimization, Cambridge University Press (2002). 3. F. S. Hiller, G. J. Lieberman, Introduction to Operations Research, Eighth edition, McGraw Hill (2006). 
Bash shell programming – basic concepts, expressions, decision making selections, repetition, special parameters  positional parameters, shift, argument validation, script examples. Android Basics: Getting started with Android development, project folder structure, simple programming, running project, generating build/APK of the app from Android Studio First application: Creating Android Project, Android Virtual Device Creation, set up debugging environment, Workspace set up for development, launching emulator, debugging on mobile devices. Basic UI design: Basics about Views, Layouts, Drawable Resources, input controls, Input Events etc. understand the app idea and design user interface/wireframes of mobile app Set up the mobile app development environment 
Semester IV
Algebra of sets, probability spaces, random variables, cumulative distribution functions, mathematical expectations, conditional probability and expectation, moments and inequalities, special discrete and continuous probability distributions, function of a random variable, random vectors and their distributions, convolutions, joint, marginal and conditional distributions, product moments, independence of random variables, bivariate distributions and properties, order statistics and their distributions, sampling distributions, Central Limit Theorem, strong law of large numbers, sequence of random variables, modes of convergence, distributions of the sample mean and the sample variance for a normal population, chisquare, t and F distributions, method of moments and maximum likelihood estimation, concepts of unbiasedness, criteria for choosing estimators, consistency and efficiency of estimates, confidence intervals, pivotal quantities, confidence intervals for proportions, simple and composite hypothesis, null and alternative hypotheses, types of error, level and size of tests, the most powerful test and Neyman  Pearson Fundamental Lemma, tests for one and twosample problems for normal populations, tests for proportions, likelihood ratio tests, chisquare test for goodness of fit. discrete and continuous stochastic processes, markov chains, transition probability matrix, state spaces, classification of states, stationary distributions, ergodicity, Poisson process, birth and death process. Introduction to reliability analysis: Application of Bayes theorem in real life problem; Reliability analysis of simple system. Serial, parallel and combined systems; First order uncertainty and reliability analysis (FORM), First order second mom (FOSM) and Advanced FOSM methods; Applications of risk and reliability analysis in engineering systems. Text / Reference Books: Scheaffer, R. L., Mulekar, M. S. and McClave, J. T., (2011): Probability and statistics for Engineers, Fifth Edition, Broo Cole, Cengage Learning. Ang, A. HS., and Tang, W. H., (2006): Probability Concepts in Engineering, Volumes 1. John Wiley and Sons. Halder, A and Mahadevan, S., (2000): Probability, Reliability and Statistical Methods in Engineering Design, John Wiley Sons. Rao, S.S., (1992): ReliabilityBased Design, McGraw Hill, Inc. Harr, M.E., (1987): ReliabilityBased Design in Civil Engineering. McGraw Hill, Inc. Ang, A. HS, and Tang, W. H., (1975): Probability Concepts in Engineering Planning and Design, Volumes 2. John Wiley Sons Benjamin, J., and Cornell. A., (1963): Probability, Statistics, and Decision for Civil Engineers. McGraw Hill. 
CPU  registers, instruction execution cycle, RTL interpretation of instructions, addressing modes, instruction set. Case study  instruction sets of some common CPUs; Assembly language programming for some processor; Data representation: signed number representation, fixed and floating point representations, character representation. Computer arithmetic  integer addition and subtraction, ripple carry adder, carry lookahead adder, etc. multiplication – shiftandadd, Booth multiplier, carry save multiplier, etc. Division  nonrestoring and restoring techniques, floating point arithmetic; CPU control unit design: hardwired and microprogrammed design approaches, Case study  design of a simple hypothetical CPU; Pipelining: Basic concepts of pipelining, throughput and speedup, pipeline hazards; Memory organization: Memory interleaving, concept of hierarchical memory organization, cache memory, cache size vs block size, mapping functions, replacement algorithms, write policy; Peripheral devices and their characteristics: Inputoutput subsystems, I/O transfers  program controlled, interrupt driven and DMA, privileged and nonprivileged instructions, software interrupts and exceptions. Programs and processes  role of interrupts in process state transitions. 
Familiarization with assembly language programming; Synthesis/design of simple data paths and controllers, processor design using HDL like verilog/vhdl; Interfacing  DAC, ADC, keyboarddisplay modules, etc. Development kits as well as Microprocessors/PCs may be used for the laboratory, along with design/simulation tools as and when necessary. 
Regular Languages: Finite AutomataDeterministic and Nondeterministic, regular operations, Regular Expressions, Equivalence of DFA, NFA and Res, Nonregular Languages and pumping lemma ContextFree Languages: ContextFree Grammars, Chomsky Normal Form, Pushdown Automata, Non ContextFree Languages and pumping lemma, Deterministic ContextFree Languages Turing Machines: Definition of TM and its variants, Decidability, Reducibility. Complexity Theory: Time complexity and Space Complexity. Text Books: 1.Introduction to the Theory of Computation, by Michael Sipser 2. Computational Complexity, by Christos H. Papadimitriou, AddisonWesley publishers. 3. Computational Complexity: A Modern Approach, by Sanjeev Arora and Boaz Barak. 
Database system architecture: Data Abstraction, Data Independence, Data Definition and Data Manipulation Languages; Data models: Entityrelationship, network, relational and object oriented data models, integrity constraints and data manipulation operations; Relational query languages: Relational algebra, tuple and domain relational calculus, SQL and QBE; Relational database design: Domain and data dependency, Armstrong’s axioms, normal forms, dependency preservation, lossless design; Query processing and optimization: Evaluation of relational algebra expressions, query equivalence, join strategies, query optimization algorithms; Storage strategies: Indices, Btrees, hashing; Transaction processing: Recovery and concurrency control, locking and timestamp based schedulers, multiversion and optimistic Concurrency Control schemes; Recent Trends: XML Data, XML Schema, JSON and “NoSQL Systems, etc. Books: Abraham Silberschatz, Henry Korth, and S. Sudarshan, Database System Concepts, McGrawHill. Raghu Ramakrishnan, Database Management Systems, WCB/McGrawHill. Bipin Desai, An Introduction to Database Systems, Galgotia. J. D. Ullman, Principles of Database Systems, Galgotia. R. Elmasri and S. Navathe, Fundamentals of Database Systems, AddisonWesley. Serge Abiteboul, Richard Hull and Victor Vianu, Foundations of Databases. AddisonWesley 
Database schema design, database creation, SQL programming and report generation using a commercial RDBMS like ORACLE/SYBASE/DB2/SQLServer/INFORMIX. Students are to be exposed to front end development tools, ODBC and CORBA calls from application Programs, internet based access to databases and database administration. 
Semester V
Evolution of computer networks; Physical Layer: Theoretical basis for data communication, transmission media and impairments, switching systems Medium Access Control Sublayer: Channel allocation Problem, multiple access protocols, Ethernet Data link layer: Framing, HDLC, PPP, sliding window protocols, error detection and correction Network Layer: Internet addressing, IP, ARP, ICMP, CIDR, routing algorithms (RIP, OSPF, BGP); Transport Layer: UDP, TCP, flow control, congestion control; Introduction to quality of service; Application Layer: DNS, Web, email, authentication, encryption. Books: Peterson & Davie, Computer Networks, A Systems Approach: 5th Edition William Stallings Data and Computer Communication, Prentice Hall of India. Behrouz A. Forouzan, Data Communication and Networking, McGrawHill. Andrew S. Tanenbaum, Computer Networks, Prentice Hall. Douglas Comer, Internetworking with TCP/IP, Volume 1, Prentice Hall of India. W. Richard Stevens, TCP/IP Illustrated, Volume 1, AddisonWesley. 
Simulation experiments for protocol performance, configuring, testing and measuring network devices and parameters/policies; network management experiments; Exercises in network programming. 
Process Management: process; thread; scheduling. Concurrency: mutual exclusion; synchronization; semaphores; monitors; Deadlocks: characterization; prevention; avoidance; detection. Memory Management: allocation; hardware sup port; paging; segmentation. Virtual Memory: demand paging; replacement; allocation; thrashing. File Systems and Implementation. Secondary Storage: disk structure; disk scheduling; disk management. (Linux will be used as a running example, while examples will draw also from Windows NT/7/8.); Advanced Topics: Distributed Systems. Security. RealTime Systems. Books: A. Silberschatz, P. B. Galvin and G. Gagne, Operating System Concepts, 8th Ed, John Wiley & Sons, 2010. A. S. Tenenbaum, Modern Operating Systems, 2nd Ed, Prentice Hall of India, 2001. H. M. Deitel, P. J. Deitel and D. R. Choffness, Operating Systems, 3rd Ed, Prentice Hall, 2004. W. Stallings, Operating Systems: Internal and Design Principles, 5th Ed, Prentice Hall, 2005. M. J. Bach, The Design of the UNIX Operating System, Prentice Hall of India, 1994. M. K. McKusick et al, The Design and Implementation of the 4.4 BSD Operating System, Addison Wesley, 1996. 
Programming assignments to build different parts of an OS kernel. 
Models of computation: RAM model and its logarithmic cost. Formal introduction to algorithmic paradigms: divide and conquer, recursion, dynamic programming, greedy, branch and bound, etc. Special topics: Geometric algorithms (range searching, convex hulls, segment intersections, etc.) 
The objective of this lab would be to encourage and provide support to students for some innovative work. The work may focus on inventing a practical solution for a pure Computer Science or multidisciplinary problems. Depending on the nature of the work, it may be carried out in a group or individual mode. 
Semester VI
Introduction: History of Programming Languages; Evolution of the Major Programming Languages; Art of Programming Language Design; Properties and Success of Programming Languages. Programming LanguageParadigms: Imperative (e.g. C, Pascal, Fortran); Functional (e.g. LISP, HASKELL, OCaml); Object Oriented (e.g. JAVA, C++, Scala); Logicbased (e.g. Prolog); Multiparadigm programming languages (e.g. Python). Programming Language Concepts: Values and Data Types; Block Structure; Scope, Binding and Lifetime of Variables; Static vs. Dynamic Typing; Static vs. Dynamic Scoping; Memory Management; Procedural Abstraction; Data Abstraction; Concurrency; etc. Programming Language Syntax and Semantics: Syntax vs. Semantics; Brief Overview of Regular and Context Free Languages, Formal Semantics: denotational, operational, axiomatic semantics. Language Translation: Compiler vs. Interpreter; Various Phases of Compilers; Overview of Parsing Techniques; Syntax vs. Semantic Analysis; Intermediate Code Generation, Code Optimization Techniques; A Closer Look at Implementation  Building a Runnable Program. Text Books: 1. Michael L. Scott, “Programming Language Pragmatics”, Morgan Kaufmann, 3rd Edition. 2. Harold Abelson, Gerald Jay Sussman, Julie Sussman, “Structure and Interpretation of Computer Programs”, MIT Press, 2nd Edition. 3. Aho A., Sethi R., Ullman J.D., Compilers : Principles, Techniques and Tools, Addison Wesley, 1995 References: 1. Ravi Sethi, K.V. Vishwanatha, “Programming Languages: Concepts and Constructs”, 2/e, Pearson Education, 2007. 2. T.W. Pratt and M.V. Zelkowitz, “Programming Languages – Design and Implementation”, PrenticeHall. 3. Robert W. Sebesta, “Concepts of Programming Languages”, AddisonWesley. 4. D. A. Watt, “Programming Language Design Concepts”, John Wiley & Sons. 5. Kenneth C. Louden and Kennath A. Lambert, “Programming Languages: Principles and Practice”, Cengage Learning. 6. Recent Research Papers relevant to the course. 

1. Handson experience with various parsers, such as ANTLR, Lark, Lex, Yacc, etc.; 2. Design your own programming language, write its grammar, and implement its parser; 3. Programming assignments to build a compiler for a subset of a Clike programming language; 4. Class assignments on functional and logic programming languages, such as LISP, Prolog. 
1. Introduction, Motivation of the course 2. Problem Solving: Uninformed search, Informed search, Local Search, 3. Game Playing: Minmax, AlphaBeta Pruning, Constraint Satisfaction Problems: Factor Graphs, Backtracking Search, Dynamic Ordering, Arc consistency 4. Knowledge, Reasoning and Planning: Propositional and Predicate Calculus, Semantic Nets; Automated Planning 5. Machine Learning: Learning from examples and analogy 6. Association rule mining 7. Application Topics: Introduction to NLP, Introduction to Fuzzy Sets and Logic References:
Journals and Conference Proceedings: Artificial Intelligence, Machine Learning, ACL Anthology, ICML, ECML etc. 
Small projects based on the concepts and tools taught in AI class. 
The objective of this project would be to encourage and provide support to students for some innovative work. The work may focus on inventing a practical solution for a CS or multidisciplinary problems. Depending on the nature of the work, it may be carried out in a group or individual mode. 
Proposed Electives 

1  Advanced topics on Database 
2  CAD for VLSI 
3  Computer and Network Security 
4  Distributed Systems 
5  Formal methods for analysis and verification 
6  Natural Language Processing 
7  Pattern Recognition 
8  Software Testing 
9  Wireless Networks 
10  Introduction to Network Science 
11  A Mathematical Introduction to Robotics 
12  Advanced Machine Learning 
13  Advanced Network Science, 
14  Advanced Operating Systems 
15  Advanced Signal Processing for AI and DS 
16  AI in Healthcare 
17  Applications of artificial intelligence in Chemistry 
18  Applied Time Series Analysis 
19  Big Data Computing 
20  Blockchain tech: A Software Engg. Perspective 
21  Cloud Computing 
22  Computational Geometry 
23  Conversational AI 
24  Conversational Artificial Intelligence, 
25  Cryptography 
26  Data Visualization 
27  Database & Data Mining 
28  Deep Learning for NLP 
29  Design and Analysis of Algorithms 
30  Discrete Differential Geometry 
31  Distributed Machine Learning 
32  Edge AI 
33  Estimation and Detection 
34  Estimation and Detection 
35  Foundation of Computer Security 
36  Foundations of Computer Systems 
37  Foundations of Machine Learning 
38  Foundations of Theoretical Computer Science 
39  Geometric and Topological Modelling for Scientists and Engineers 
40  Graph Representation Learning 
41  High Performance Computing 
42  Information Retrieval and Mining, 
43  information theory and coding 
44  Intro. Blockchain and Cryptocurreny 
45  Introduction to Computational Topology 
46  Introduction to Deep Learning 
47  Introduction to Network Science 
48  Machine Translation, 
49  Mobile Robotics 
50  Planning Algorithms 
51  Sentiment and Emotion Analysis 
52  Social Text Mining, 
53  Statistical signal processing 
54  Statistical signal processing 
55  Topological Data Analysis 
B. Tech. AI & DS
Course structure of B. Tech. AI & DS IIT Patna
Semester  Course Code  Course name  LTPCredit  Offering Department 

Semester I  CE111  Engineering Drawing  1035  Civil 
EE101  Electrical Sciences  3108  Electrical  
HS103  Communicative English for Engineers  20.516  Humanities and Social Science  
MA101  Mathematics I  3108  Mathematics  
ME110  WorkshopI  0033  Mechanical  
PH103  Physics –I  3108  Physics  
PH 110  Physics Laboratory  0033  Physics  
Total credits: 41  
Semester II  CB102 & CE102  Biology and Environmental Studies  3006  CB & CE 
CH103  Introductory Chemistry  3108  Chemistry  
CH110  Chemistry Laboratory  0033  Chemistry  
CS102  Programming and Data Structures  3006  CS  
CS112  Programming and Data Structures Laboratory  0033  CS  
EE103  Basic Electronics Laboratory  0033  EE  
MA102  Mathematics –II  3108  Mathematics  
ME102  Engineering Mechanics  3108  ME  
Total credits: 45  
Semester III  MA2XX  Mathematical III  3108  Mathematics 
HS2XX  HSS Elective – I  3006  Humanities and Social Science  
CS204  Algorithms  3006  CS  
CS224  Algorithms Laboratory  0033  CS  
CS203  Discrete Mathematics  3006  CS  
CS227  Digital Systems  2026  CS  
CS271  Optimization techniques  3006  CS  
CS230  Software Lab/Tools  0033  CS  
Total credits: 44  
Semester IV  HS2XX  HSS Elective – II  3006  Humanities and Social Science 
MA2XX  Open Elective I (Prob. Theory and Random Processes)  3006  Mathematics  
CS2XX  Computer Architecture  3006  CS  
CS2XX  Computer Architecture Lab  0033  CS  
CS2XX  Theory of computation  3006  CS  
CS2XX  Database  3006  CS  
CS2XX  Database Lab  0033  CS  
Total credits: 36  
Semester V  XX3XX  Open Elective  3006  Science/Engg. 
CS341  Operating Systems  3006  CS  
CS342  Operating Systems Lab  0033  CS  
CS3XX  Computer Network  3006  CS  
CS3XX  Computer Network Lab  0033  CS  
CS3XX  Deep Learning  3006  CS  
CS2XX  Innovative Design Lab  0033  CS  
CS3XX  Artificial IntelligenceII  3006  CS  
Total credits: 39  
Semester VI  HS3XX  HSS Elective – III  3006  Humanities and Social Science 
CS3XX  Advance Machine Learning  3006  CS  
CS3XX  Bayesian Data Analysis  3006  CS  
CS3XX  Programming for AI/ML  0033  CS  
CS3XX  Computer Vision  3006  CS  
CS3XX  Capstone ProjectI  0033  CS  
Total credits: 30  
Semester VII  XX4XX  Open Elective  3006  
CS4XX  Natural Language Processing  3006  CS  
CS4XX  Bigdata Analytics  2026  CS  
CS4XX  Elective – I  3006  CS  
CS4xx  Elective – II  3006  CS  
CS4XX  Capstone ProjectII  0033  CS  
Total credits: 33  
Semester VIII  CS4XX  Bigdata Security  2026  CS 
xx4XX  Elective III  3006  
xx4XX  ElectiveIV  3006  
CS4XX  individual Project  3006  CS  
Total credits: 24 
Proposed Electives Database & Data Mining Introduction to Computational Topology Geometric and Topological Modelling for Scientists and Engineers Mobile Robotics Cloud Computing Statistical signal processing Estimation and Detection information theory and coding Introduction to Network Science Cryptography High Performance Computing Social Text Mining, AI in Healthcare Conversational AI Discrete Differential Geometry Computational Geometry Topological Data Analysis Planning Algorithms, A Mathematical Introduction to Robotics Advanced Signal Processing for AI and DS Edge AI Statistical signal processing, Estimation and Detection, Applications of artificial intelligence in Chemistry Graph Representation Learning, Advanced Network Science, Distributed Machine Learning Deep Learning for NLP Conversational Artificial Intelligence, Machine Translation, Information Retrieval and Mining, Sentiment and Emotion Analysis Advanced Operating Systems Signal Processing and Machine Learning for Data Science Applied Time Series Analysis Probability and Random Process Applied Time Series Analysis Reinforcement Learning 
Total credits: 299
Semester I
CE111  Engineering Drawing  1035  Civil 

Geometrical construction of simple plane figure: Bisecting the line, draw perpendicular, parallel line, bisect angle, trisect angle, construct equatorial triangle, square, polygon, inscribed circle.
Free hand sketching: prerequisites for freehand sketching, sketching of regular and irregular figures.
Drawing scales: Engineering scale, graphical scale, plane scale, diagonal scale, comparative scale, scale of chord.
Orthographic projection: Principle of projection, method of projection, orthographic projection, plane of projection, first angle of projection, third angle of projection, reference line.
Projection of points, lines and plane: A point is situated in the first quadrant, point is situated in the second quadrant, point is situated in the third quadrant, point is situated in the fourth quadrant, projection of line parallel to both the plane, line contained by one or both the plane, line perpendicular to one of the plane, line inclined to one plane and parallel to other, line inclined to both the plane, true length of line.
Missing views: Drawing of missing front view of a solid, missing top view of solids, missing side view of solids, Orthographic projection of simple solid: Introduction, types of solid, projection of solid when axis perpendicular to HP, axis perpendicular to VP, axis parallel to both HP and VP, axis inclined to both HP and VP.
Orthographic projection of simple solid: Introduction, types of solid, projection of solid when axis perpendicular to HP, axis perpendicular to VP, axis parallel to both HP and VP, axis inclined to both HP and VP.
Text and Reference Books:
 B. Agrawal and CM Agrawal, Engineering Drawing, Tata McGrawHill Publishing Company Limited, 2008.
 D. A. Jolhe, Engineering Drawing, Tata McGrawHill Publishing Company Limited, 2006.
 K. Venugopal, Engineering Drawing and Graphics, 2nd ed., New Age International, 1994.
EE101  Electrical Sciences  3108  Electrical 

Circuit Analysis Techniques, Circuit elements, Simple RL and RC Circuits, Kirchhoff’s law, Nodal Analysis, Mesh Analysis, Linearity and Superposition, Source Transformations, Thevnin's and Norton's Theorems, Time Domain Response of RC, RL and RLC circuits, Sinusoidal Forcing Function, Phasor Relationship for R, L and C, Impedance and Admittance.
Semiconductor Diode, Zener Diode, Rectifier Circuits, Clipper, Clamper, Bipolar Junction Transistors, Transistor Biasing, Transistor Small Signal Analysis, Transistor Amplifier, Operational Amplifiers, Opamp Equivalent Circuit, Practical Opamp Circuits, DC Offset, Constant Gain Multiplier, Voltage Summing, Voltage Buffer, Controlled Sources, Instrumentation Circuits, Active Filters and Oscillators.
Number Systems, Logic Gates, Boolean Theorem, Algebraic Simplification, Kmap, Combinatorial Circuits, Encoder, Decoder, Combinatorial Circuit Design, Introduction to Sequential Circuits.
Magnetic Circuits, Mutually Coupled Circuits, Transformers, Equivalent Circuit and Performance, Analysis of ThreePhase Circuits, Electromechanical Energy Conversion, Introduction to Rotating Machines.
 C. K. Alexander and M. N. O. Sadiku, Fundamentals of Electric Circuits, 3rd Edition, McGrawHill, 2008.
 W. H. Hayt and J. E. Kemmerly, Engineering Circuit Analysis, McGrawHill, 1993.
 Donald A Neamen, Electronic Circuits; analysis and Design, 3rd Edition, Tata McGrawHill Publishing Company Limited.
 Adel S. Sedra, Kenneth C. Smith, Microelectronic Circuits, 5th Edition, Oxford University Press, 2004.
 R. L. Boylestad and L. Nashelsky, Electronic Devices and Circuit Theory, 6th Edition, PHI, 2001.
 M. M. Mano, M. D. Ciletti, Digital Design, 4th Edition, Pearson Education, 2008.
 Floyd and Jain, Digital Fundamentals, 8th Edition, Pearson.
 A. E. Fitzgerald, C. Kingsley Jr. and S. D. Umans, Electric Machinery, 6th Edition, Tata McGrawHill, 2003.
 D. P. Kothari and I. J. Nagrath, Electric Machines, 3rd Edition, McGrawHill, 2004.
HS103  Communicative English for Engineers  20.516  HSS 

In today’s ‘global village’, there are many who believe that ‘Communication is like breathing and life would cease to continue without it’. This particular course on communication skills imbibes the same and therefore, it aims to equip the students with getting the basics right of communication and presentation skills for academic and professional purposes. It is designed to help the second language learners acquire fluency in both spoken and written English to communicate information with clarity, precision and confidence especially in the professional sphere. It will introduce learners not only to the basic concepts in communication but also focus on providing them a handson experience of the same. It is hoped that after commanding the skills required in spoken and written English, learners will be able to express themselves more effectively.
The course will have ten units and shall focus on the following topics:
Unit 1: Language and Communication
What is Communication
Nature, Style and Process of Communication
Communication Barriers
Objectives and Importance of Communication
Formal and Informal Communication
Verbal and NonVerbal Communication
Unit 2: English Language Remedial Skills
Construction of Sentences
SubjectVerb Agreement
Tenses
Active and Passive Voice
Direct and Indirect Speech
Common Errors
Unit 3: Oral Skills
Public Speaking
Dealing with lack of confidence
Making an Effective Presentation
Telephone Etiquette
Understanding GD
Why conduct a GD?
How to gear up for a GD?
Different Phases of GD
Unit 4: Listening Skills
Meaning of Listening
Different Types of Listening
Barriers to Listening and Methods to overcome them
Various strategies to develop effective Listening
Semantic Markers
Unit 5: Reading Skills
What is Reading?
Types of Reading
Reading Comprehension
Unit 6: Writing Skills
Business Correspondence
Element and Style of Writing
Report Writing
Notice, Agenda and Minutes
Unit 7: Interview Techniques
How to prepare for an Interview
An Interview
Text and Reference Books:
 V. S. Kumar, P.K. Dutt and G. Rajeevan, A Course in Listening and SpeakingI, Foundation books, 2007.
 V.Sasikumar, P.KiranmaiDutt, Geetha Rajeevan, "A Course in Listening and SpeakingII', Foundation books, 2007.
 Rizvi, Ashraf, Effective Technical Communication, Tata McGraw Hill, 2005.
 Nitin Bhatnagar and MamtaBhatnagar, 'Communicative English for Engineers and Professionals, Pearson, 2010.
MA101  Mathematics I  3108  Mathematics 

Properties of real numbers. Sequences of real numbers, montone sequences, Cauchy sequences, divergent sequences. Series of real numbers, Cauchy’s criterion, tests for convergence. Limits of functions, continuous functions, uniform continuity, montoneand inverse functions. Differentiable functions, Rolle's theorem, mean value theorems and Taylor's theorem, power series. Riemann integration, fundamental theorem of integral calculus, improper integrals. Application to length, area, volume, surface area of revolution. Vector functions of one variable and their derivatives. Functions of several variables, partial derivatives, chain rule, gradient and directional derivative. Tangent planes and normals. Maxima, minima, saddle points, Lagrange multipliers, exact differentials. Repeated and multiple integrals with application to volume, surface area, moments of inertia. Change of variables. Vector fields, line and surface integrals. Green’s, Gauss’ and Stokes’ theorems and their applications.
Text Books:
 G. B. Thomas and R. L. Finney, Calculus and Analytic Geometry, 6th Ed/9th Ed, Narosa/ Addison Wesley/ Pearson, 1985/ 1996.
 T. M. Apostol, Calculus, Volume I, 2nd Ed, Wiley, 1967. T. M. Apostol, Calculus, Volume II, 2nd Ed, Wiley, 1969.
Reference Books:
 R. G. Bartle and D. R. Sherbert, Introduction to Real Analysis, 5th Ed, Wiley, 1999.
 J. Stewart, Calculus: Early Transcendentals, 5th Ed, Thomas Learning (Brooks/ Cole), Indian Reprint, 2003.
ME110  WorkshopI  0033  Mechanical 

Sheet Metal Working:
Sheet material: GI sheets, aluminium, tin plate, copper, brass etc.; Tools: steel rule, Vernier calipers, micrometer, sheet metal gauge, scriber, divider, punches, chisels, hammers, snips, pliers, stakes etc.; operations: scribing, bending, shearing, punching etc.; Product development: hexagonal box with cap, funnel etc.
Pattern Making and Foundry Practice:
Pattern material: wood, cast iron, brass, aluminium, waxes etc.; Types of patterns: split, single piece, match plate etc.; Tools: cope, drag, core, core prints, shovel, riddle, rammer, trowel, slick, lifter, sprue pin, bellow, mallet, vent rod, furnace etc. Moulding sands: green sand, dry sand, loam sand, facing sand etc., Sand casting: Sand preparation, mould making, melting, pouring, and cleaning. Joining: Classifications of joining processes; Introduction to Arc welding processes; power source; electrodes; edge preparation by using tools bench vice, chisels, flat file, square file, half round file, round file, knife edge file, scrapers, hacksaws, try squares; cleaning of job, Job: lap and butt joints using manual arc welding.
Machining Centre:
Introduction to different machine tools; Working principle of lathe, milling, drilling etc.; Setting and preparation of job using lathe and milling; Performing different operations namely, straight turning, taper turning, knurling, thread cutting etc.; Introduction to dividing head, indexing, performing operation in milling using indexing mechanism.
CNC Centre:
Introduction to CNC machines; Fundamentals of CNC programming using G and M code; setting and operations of job using CNC lathe and milling, tool reference, work reference, tool offset, tool radius compensation.
Text and Reference Books:
 H. Choudhury, H. Choudhary and N. Roy, Elements of Workshop Technology, vol. I,Mediapromoters and Publishers Pvt. Ltd., 2007.
 W. A. J. Chapman, Workshop Technology, Part 1, 1st South Asian Edition, Viva Book Pvt Ltd., 1998.
 P.N. Rao, Manufacturing Technology, Vol.1, 3rd Ed., Tata McGraw Hill PublishingCompany, 2009.
 B.S. Pabla, M.Adithan, CNC machines,New Age International, 2012.
 G. B. Thomas and R. L. Finney, Calculus and Analytic Geometry, 6th Ed/9th Ed, Narosa/Addison Wesley/Pearson, 1985/1996.
 T. M. Apostol, Calculus, Volume I, 2nd Ed, Wiley, T. M. Apostol, Calculus, Volume II, 2nd Ed, Wiley, 1969/1967.
PH103  PhysicsI  3–1–0–8  PH 

Orthogonal coordinate systems and frames of reference, conservative and nonconservative forces, workenergy theorem, potential energy and concept of equilibrium; Rotation about fixed axis, translationalrotational motion, vector nature of angular velocity, rigid body rotation and its applications, Euler's equations; Gyroscopic motion and its application; Accelerated frame of reference, centrifugal and Coriolis forces.
Harmonic oscillator, damped and forced oscillations, resonance, coupled oscillations, small oscillation, normal modes, longitudinal and transverse waves, wave equation, plane waves, phase velocity, superposition wave packets and group velocity, two and threedimensional waves.
Failure of classical concepts, Black body radiation, photoelectric effect, Compton effect, Davison and Germer's experiment, FrankHertz experiment, Bohr's theory, Sommerfeld's model, correspondence principle, Planck hypothesis, De Broglie's hypothesis, Hilbert space, observables, Dirac notation, principle of superposition, wave packets, phase and group velocities, probability & continuity equation, eigenvalues and Eigen functions, orthonormality, expectation values, uncertainty principle, postulates of Quantum Mechanics, Schrodinger equation & its applications to 1D potentials, field quantization, periodic potential wells: Kronig Penny model and origin of band gap.
Textbooks:
 D. Kleppner and R. J. Kolenkow, An introduction to Mechanics, Tata McGrawHill, New Delhi, 2000.
 David Morin, Introduction to Classical Mechanics, Cambridge University Press, NY, 2007.
 Frank S. Crawford, Berkeley Physics Course Vol 3: Waves and Oscillations, McGraw Hill, 1966.
 Eyvind H. Wichmann, Berkeley Physics Course Vol 4: Quantum physics, McGraw Hill, 1971.
Reference Books:
 R. P. Feynman, R. B. Leighton and M. Sands, The Feynman Lecture in Physics, Vol I, Narosa Publishing House, New Delhi, 2009.
 R. P. Feynman, R. B. Leighton and M. Sands, The Feynman Lecture in Physics, Vol III, Narosa Publishing House, New Delhi, 2009.
 R. Eisberg and R. Resnick, Quantum Physics of atoms, molecules, solids, nuclei and particles, John Wiuley and Sons (Asia) Pvt. Ltd., Singapore, 2002.
 A. J. Dekker, Solid State Physics, Macmillan Pub. India Ltd., New Delhi, 2009.
 David J. Griffith, Introduction to Quantum Mechanics, Pearson Education Ltd, New Delhi, 2009.
 B.H. Bransden& C.J. Joachain, Quantum Mechanics, Pearson Education Ltd, New Delhi, 2008.
PH110  Physics Laboratory  0033  PH 

The list of experiments is as follows:
 Instructions to Students
 Introduction to Error Analysis
Ex 1 Decay of Current in A Capacitive Circuit
Ex 2 QFactor of an LCR Circuit
Ex 3 Study of Hall Effect
Ex 4 Speed of Sound in Air
Ex 5 ‘g’ by A Compound Pendulum
Ex 6 Speed of Light in Glass
Ex 7 Determination of e/m
Ex 8 Interference of Light: Newton’s Ring
Ex 9 Surface Tension of Water by Method of Capillary Ascent
Ex 10 Determination of Plank’s constant by Photoelectric Effect
NSS/NOS/Cultural  NSS/NOS/Cultural  P/NP 

Semester II
CB102&CE102  Biology and Environment Studies  3006  CB & CE 

Module 1  Biology: 1. Cell – Structure and logic of optimization; 2. Blood – The following tissue – Basis and rationale; 3. Organs – Structure, function, interactions, failure; 4. Molecular basis of disorders – example: Diabetes; 5. Modern techniques of evaluations and corrections; 6. Open discussions – Feedback from students
Module 2 – Environmental Science / Studies: 1.Ecology and Sustainable Development – Ecosystems, Natural cycles, Biodiversity, Man and environment; 2. Water Resources – Hydrologic cycle and its components, Groundwater and surface water, Water quality; 3. Environmental Sanitation: Conventional and ecological sanitation; 4. Environmental Pollution and Control – Air, Water, Soil, Noise Pollution, Solid and Hazardous Waste, Biomedical Waste, Ewaste: Sources, effect, treatment and control; 5. Environmental Legislations and Standards; 6.Current Environmental Issues: Greenhouse gases and global warming, Acid rain, Ozone layer depletion, Climate change
Text Books:
 Any basic Biology Book of CBSE Curriculum at +2 Level/ Etext Books
 Davis, M.L. and Masten,S.J., Principles of Environmental Engineering and Science,2nd Edition, McGrawHill, 2013.
 Kaushik, A. and Kaushik, C.P., Perspectives in Environmental Studies, 4thEdition, New Age International, 2014.
Reference Books:
 Botkin,D.B. and Keller,E.A., Environmental Science,8th Edition, Wiley, 2012.
 Cunningham, W.P. and Cunningham, M.A., Environmental Science: A Global Concern, 13thEdition, McGrawHill, 2015
CH103  Introductory Chemistry  3108  Chemistry 

PHYSICAL CHMEISTRY
Thermodynamics: The fundamental definition and concept, the zeroth and first law. Work, heat, energy and enthalpies. Second law: entropy, free energy and chemical potential. Change of Phase. Third law. Chemical equilibrium, Chemical kinetics: The rate of reaction, elementary reaction and chain reaction.
Electrochemistry: Conductance of solutions, equivalent and molar conductivities and its variation with concentration. Kohlrausch’s lawionic mobilities, Transference number of ions. activities, application of DebyeHuckel theory. The Walden’s rule. DebyeHuckelOnsager treatment. Electrochemical cells, Nernst equation. Application of EMF measurements. Liquid junction potential, commercial cells – the primary and secondary cells. Fuel cells.
INORGANIC CHEMISTRY
Coordination chemistry: ligand, nomenclature, isomerism, stereochemistry, valence bond, crystal field and molecular orbital theories. Bioinorganic chemistry: Trace elements in biology, heme and nonheme oxygen carriers, haemoglobin and myoglobin; organometallic chemistry.
ORGANIC CHEMISTRY
Stereo and regiochemistry of organic compounds, conformers. Bioorganic chemistry: amino acids, peptides, proteins, enzymes, carbohydrates, nucleic acids and lipids. Modern techniques in structural elucidation of compounds (UV – Vis, IR, NMR). Solid phase synthesis and combinatorial chemistry. Green chemical processes.
Textbooks:
 P. W. Atkins, Physical Chemistry, ELBS, 5th Ed, 1994.
 J. O'M. Bockris and A. K. N. Reddy, Modern Electrochemistry, Vol. 1 and 2, Kluwer Academic, 2000.
 K. L. Kapoor, A Textbook of Physical Chemistry, Macmillan India, 2nd Ed, 1986.
 F. A. Cotton and G. Wilkinson, Advanced Inorganic Chemistry, Wiley Eastern Ltd, New Delhi, 3rd Ed, 1972 (reprint in 1998).
 D. J. Shriver, P. W. Atkins and C. H. Langford, Inorganic Chemistry, ELBS, 2nd Ed, 1994.
 S. H. Pine, Organic Chemistry, McGraw Hill, 5th Ed, 1987
Reference Books:
 Levine, Physical Chemistry, McGraw Hill, 4th Ed, 1995.
 J. E. Huheey, E. A. Keiter and R. L. Keiter, Inorganic Chemistry: Principle, structure and reactivity, Harper Collins, 4th Ed, 1993.
 L. G. Wade Jr., Organic Chemistry, Prentice Hall, 1987
CH110  Chemistry Laboratory  0033  Chemistry 

Estimation of metal ion: Determination of total hardness of water by EDTA titration. Experiments based on chromatography: Identification of a mixture containing two organic compounds by TLC. Experiments based on pH metry.: Determination of dissociation constant of weak acids by pH meter. Experiments based on conductivity measurement: Determination of amount of HCl by conductometric titration with NaOH. Synthesis and characterization of inorganic complexes: e.g. Mn(acac)3, Fe(acac)3, cisbis(glycinato)copper (II) monohydrate and their characterization by m. p. IR etc. Synthesis and characterization of organic compounds: e.g. Dibenzylideneacetone. Kinetics: Acid catalyzed hydrolysis of methyl acetate. Verification of BeerLamberts law and determination of amount of iron present in a supplied solution. Experiments based on electro gravimetry and electroplating. Experiments based on magnetometry.
CS102  Programming and Data Structures  3006  CS 

Introduction to digital computers; introduction to programming variables, assignments; expressions; input/output; conditionals and branching; iteration; functions; recursion; arrays; introduction to pointers; structures; introduction to dataprocedure encapsulation; dynamic allocation; linked structures; introduction to data structures stacks, queues and trees; time and space requirements.
References:
 B. W. Kernighan and D. Ritchie, The C Programming Language, Prentice Hall of India (2nd Edition).
 A. Kelley and I. Pohl, A Book on C, Pearson Education (4th Edition).
 P.J. Deitel and H.M. Deitel , C How To Program, Pearson Education (7th Edition).
CS112  Programing and Data Structures Laboratory  0033  CS 

Introduction to Unix commands; Introduction to program development tools vi editor, GNU compiler, testing and debugging, etc.; Implementation of programs in C language.
EE103  Basic Electronics Laboratory  0033  EE 

Experiments using diodes and bipolar junction transistor (BJT): design and analysis of half wave and fullwave rectifiers, clipping circuits and Zener regulators, BJT characteristics and BJT amplifiers; experiments using operational amplifiers (op amps): summing amplifier, comparator, precision rectifier, astable and mono stable multi vibrators and oscillators; experiments using logic gates: combinational circuits such as staircase switch, majority detector, equality detector, multiplexer and demultiplexer; experiments using flipflops: sequential circuits such as non overlapping pulse generator, ripple counter, synchronous counter, pulse counter and numerical display.
Reference Books:
 A. P. Malvino, Electronic Principles. New Delhi: Tata McGrawHill, 1993.
 R. A. Gayakwad, OpAmps and Linear Integrated Circuits. New Delhi: Prentice Hall of India, 2002.
 R.J. Tocci: Digital Systems; PHI, 6e, 2001.
MA102  MathematicsII  3108  MA 

Linear Algebra: Vector spaces (over the field of real and complex numbers). Systems of linear equations and their solutions. Matrices, determinants, rank and inverse. Linear transformations. Range space and rank, null space and nullity. Eigenvalues and eigenvectors. Similarity transformations. Diagonalization of Hermitian matrices. Bilinear and quadratic forms.
Ordinary Differential Equations: First order ordinary differential equations, exactness and integrating factors. Variation of parameters. Picard's iteration. Ordinary linear differential equations of nth order, solutions of homogeneous and nonhomogeneous equations. Operator method. Method of undetermined coefficients and variation of parameters.
Power series methods for solutions of ordinary differential equations. Legendre equation and Legendre polynomials, Bessel equation and Bessel functions of first and second kind. Systems of ordinary differential equations, phase plane, critical point, stability.
Textbooks:
 K. Hoffman and R. Kunze, Linear Algebra, Prentice Hall, 1996.
 T. M. Apostol, Calculus, Volume II, 2nd Ed, Wiley, 1969.
 S. L. Ross, Differential Equations, 3rd Ed, Wiley, 1984.
 E. A. Coddington, An Introduction to Ordinary Differential Equations, Prentice Hall, 1995.
 W.E. Boyce and R.C. DiPrima, Elementary Differential Equations and Boundary Value Problems, 7th Ed, Wiley, 2001.
Reference Books:
 E. Kreyszig, Advanced Engineering Mathematics, 9th Edition, Wiley, 2005.
ME102  Engineering Mechanics  3108  MA 

 Rigid body statics: Equivalent force system. Equations of equilibrium, Freebody diagram, Reaction, Static indeterminacy.
 Structures: 2D truss, Method of joints, Method of section. Beam, Frame, types ofloading and supports, axial force, Bending moment, Shear force and Torque Diagrams for a member:
 Friction: Dry friction (static and kinetic), wedge friction, disk friction (thrust bearing), belt friction, square threaded screw, journal bearings, Wheel friction, Rolling resistance.
 Centroid and Moment of Inertia
 Virtual work and Energy method: Virtual Displacement, principle of virtual work, mechanical efficiency, work of a force/couple (springs etc.), Potential Energy and equilibrium, stability.
 Introduction to stress and strain: Definition of Stress, Normal and shear Stress. Relation between stress and strain, Cauchy formula.
 Stress in an axially loaded member,
 Stresses due to pure bending,
 Complementary shear stress,
 Stresses due to torsion in axisymmetric sections:
 Twodimension state of stress, Mohr’s circle representation, Principal stresses
Text and Reference books:
 I. H. Shames, Engineering Mechanics: Statics and dynamics, 4th Ed, PHI, 2002.
 F. P. Beer and E. R. Johnston, Vector Mechanics for Engineers, Vol I  Statics, 3rd Ed, TataMcGraw Hill, 2000.
 J. L. Meriam and L. G. Kraige, Engineering Mechanics, Vol I  Statics, 5th Ed, John Wiley, 2002.
 E.P. Popov, Engineering Mechanics of Solids, 2nd Ed, PHI, 1998.
 F. P. Beer and E. R. Johnston, J.T. Dewolf, and D.F. Mazurek, Mechanics of Materials, 6th Ed, McGraw Hill Education (India) Pvt. Ltd., 2012.
NSS/NOS/Cultural  NSS/NOS/Cultural  P/NP 

Semester III
MA2XX  Mathematical Statistics  3–0–0–6  MA 

Ordered Statistics, probability distributions of Sample Range, Minimum and Maximum Order Statistics. Random Sampling, Sampling distributions: Chisquare, T, F distributions.
Point Estimation: Sufficiency, Factorization theorem, Consistency, Moment method of estimation, Unbiased Estimation, Minimum Variance Unbiased Estimator and their properties, RaoCramer lower bound, RaoBlackwellization, Fisher Information, Maximum Likelihood Estimator and properties, Criteria for evaluating estimators: Mean squared error.
Interval Estimation: Coverage Probabilities, Confidence level, Sample size determination, Shortest Length interval, Pivotal quantities, interval estimators for various distributions.
Testing of Hypotheses: Null and Alternative Hypotheses, Simple hypothesis, Composite hypothesis, Test Statistic, Critical region, Error Probabilities, Power Function, Level of Significance, NeymanPearson Lemma, One and TwoSided Tests for Mean, Variance and Proportions, One and Two Sample TTest, Pooled TTest, Paired TTest, ChiSquare Test, Contingency Table Test, Maximum Likelihood Test, Duality between Confidence Intervals.
Bayesian Estimation: Prior and Posterior Distributions, Quadratic Loss Function, Posterior Mean, Bayes Estimates for well Known Distributions (Normal, Gamma, Exponential, Binomial, Poisson, Beta etc.)
Text Books:
 Mathematical Statistics with applications, Kandethody M. Ramachandran, Chris P. Tsokos, Academic Press.
 Hogg R.V. & Craig A.T. (1978): Introduction to Mathematical Statistics
 Probability and Statistics in Engineering, William W. Hines, Douglas C. Montgomery, David M. Goldsman, John Wiley & Sons, Inc.
Reference Books:
 Statistical Inference, G. Casella and R.L. Berger, Duxbury Advanced Series.
HS2XX  HSS Elective – I  3–0–0–6  HSS 

CS204  Algorithms  3–0–0–6  CS 

Asymptotic notations, introduction to complexity (time/space) analysis of algorithms. Basic introduction to algorithmic paradigms like divide and conquer, recursion, greedy, dynamic programming, etc. Searching: binary search trees, balanced binary search trees, AVL trees and redblack trees, Btrees, hashing. Priority queues, heaps, Interval trees. Sorting: quick sort, heap sort, merge sort, radix sort, bucket sort, counting sort, etc. and their analysis. Graph Algorithms: BFS, DFS, connected components, topological sort, minimum spanning trees, shortest paths, network flow. Reducibility between problems and NPcompleteness: discussion of different NPcomplete problems.
Books
 M. A. Weiss, Data Structures and ProblemSolving Using Java, 2nd Ed, AddisonWesley, 2002.
 T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, Introduction to Algorithms, MIT Press, 2001.
 B. W. Kernighan and D. Ritchie, The C Programming Language, 2nd Ed, Prentice
 Hall of India, 1988.
 A. Aho, J. E. Hopcroft and J. D. Ullman, The Design and Analysis of Computer
 Algorithms, AddisonWesley, 1974.
 S. Sahni, Data Structures, Algorithms and Applications in C++, McGrawHill, 2001.
 M. T. Goodrich and R. Tamassia, Algorithm Design: Foundations, Analysis and Internet
 Examples, John Wiley & Sons, 2001.
CS224  Algorithms Laboratory  0–0–3–3  CS 

The laboratory component will emphasize two areas: Implementation of algorithms covered in class: This will involve running the algorithms under varying input sets and measuring running times, use of different data structures for the same algorithm (wherever applicable) to see its effect on time and space, comparison of different algorithms for the same problem etc. Design of Algorithms: This will involve design and implementation of algorithms for problems not covered in class but related to topics covered in class. The exact set of algorithms to design and implement is to be decided by the instructor. In addition, there will be at least one significantly large design project involving some realworld application. An efficient design of the project should require the use of multiple data structures and a combination of different algorithms/techniques. The lab work can be carried out using any programming language.
CS234  Linear Algebra for Data Science  3–0–0–6  CS 

Vectors: addition, scalar multiplication, inner product. Linear functions: linear functions, Taylor approximation and regression model. Clustering: norm, distances, clustering, and the kmeans algorithm. Linear independence: linear dependence, basis, orthonormal vectors. Matrices: matrix operations, inverse matrices, simultaneous linear equations, Eigenvalues, and eigenvectors Least squares: least square problem, least square data fitting; the Schur decomposition, spectral expansion, rank1 expansions. Fundamental theorem of linear algebra, ranknullity theorem, singular value decomposition. Painter style and motifs, bases for a large dimensional space. GramSchmidt algorithm, projection, least squares, data fitting. Data compression, simplification of complex models from structural engineering (reducedorder systems). Discrete Fourier series: diagonal matrices in Fourier basis, applications
Text Books:
 Stephen Boyd and Lieven Vandenberghe, Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares (Cambridge University Press, 3rd edition)
 Gilbert Strang, Introduction to Linear Algebra (Wellesley Cambridge Press, 5th edition)
CS209  Computer Architecture  3–0–3–9  CS 

CPU  registers, instruction execution cycle, RTL interpretation of instructions, addressing modes, instruction set. Case study  instruction sets of some common CPUs; Assembly language programming for some processor; Data representation: signed number representation, fixed and floatingpoint representations, character representation. Computer arithmetic  integer addition and subtraction, ripple carry adder, carry lookahead adder, etc. multiplication – shiftandadd, Booth multiplier, carry save multiplier, etc. Division  nonrestoring and restoring techniques, floating point arithmetic; CPU control unit design: hardwired and microprogrammed design approaches, Case study  design of a simple hypothetical CPU; Pipelining: Basic concepts of pipelining, throughput and speedup, pipeline hazards; Memory organization: Memory interleaving, concept of hierarchical memory organization, cache memory, cache size vs block size, mapping functions, replacement algorithms, write policy; Peripheral devices and their characteristics: Inputoutput subsystems, I/O transfers  program controlled, interrupt driven and DMA, privileged and nonprivileged instructions, software interrupts and exceptions. Programs and processes  role of interrupts in process state transitions.
CS271  Optimization techniques  3–0–0–6  CS 

Linear programming: Introduction and Problem formulation, Concept from Geometry, Geometrical aspects of LPP, Graphical solutions, Linear programming in standard form, Simplex, Big M and TwoPhase Methods, Revised simplex method, Special cases of LPP.
Duality theory: Dual simplex method, Sensitivity analysis of LP problem, Transportation, Assignment and travelling salesman problem.
Integer programming problems: Branch and bound method, Gomory cutting plane method for all integer and for mixed integer LPP.
Theory of games: saddle point, linear programming formulation of matrix games, twoperson zerosum games with and without saddlepoints, pure and mixed strategies, graphical method of solution of a game, solution of a game by simplex method. Computational complexity of the Simplex algorithm, Karmarkar's algorithm for LPP. Acquaintance to softwares like TORA and MATLAB.
Text Books:
 Hamdy A. Taha, Operations Research: An Introduction, Eighth edition, PHI, New Delhi (2007).
 S. Chandra, Jayadeva, Aparna Mehra, Numerical Optimization with Applications, Narosa Publishing House (2009).
 A. Ravindran, D.T. Phillips, J.J. Solberg, Operation Research, John Wiley and Sons, New York (2005).
 M. S. Bazaraa, J. J. Jarvis and H. D. Sherali, Linear Programming and Network Flows, 3rd Edition, Wiley (2004).
Reference Books:
 D. G. Luenberger, Linear and Nonlinear Programming, 2nd Edition, Kluwer, (2003).
 S. A. Zenios (editor), Financial Optimization, Cambridge University Press (2002).
 F. S. Hiller, G. J. Lieberman, Introduction to Operations Research, Eighth edition, McGraw Hill (2006).
CS230  Software Lab/Tools  0–0–33  CS 

Bash shell programming – basic concepts, expressions, decision making selections, repetition, special parameters  positional parameters, shift, argument validation, script examples.
Android Basics: Getting started with Android development, project folder structure, simple programming, running project, generating build/APK of the app from Android Studio
First application: Creating Android Project, Android Virtual Device Creation, set up debugging environment, Workspace set up for development, launching emulator, debugging on mobile devices. Basic UI design: Basics about Views, Layouts, Drawable Resources, input controls, Input Events etc. Understand the app idea and design user interface/wireframes of mobile app
Set up the mobile app development environment.
Semester IV
HS2XX  HSS ElectiveII  3006  HSS 

MA2XX  Prob Theory and Random Processes  3006  MA 

Algebra of sets, probability spaces, random variables, cumulative distribution functions, mathematical expectations, conditional probability and expectation, moments and inequalities, special discrete and continuous probability distributions, function of a random variable, random vectors and their distributions, convolutions, joint, marginal and conditional distributions, product moments, independence of random variables, bivariate distributions and properties, order statistics and their distributions, sampling distributions, Central Limit Theorem, strong law of large numbers, sequence of random variables, modes of convergence, distributions of the sample mean and the sample variance for a normal population, chisquare, t and F distributions, method of moments and maximum likelihood estimation, concepts of unbiasedness, criteria for choosing estimators, consistency and efficiency of estimates, confidence intervals, pivotal quantities, confidence intervals for proportions, simple and composite hypothesis, null and alternative hypotheses, types of error, level and size of tests, the most powerful test and Neyman  Pearson Fundamental Lemma, tests for one and twosample problems for normal populations, tests for proportions, likelihood ratio tests, chisqaure test for goodness of fit. discrete and continuous stochastic processes, markov chains, transition probability matrix, state spaces, classification of states, stationary distributions, ergodicity, poisson process, birth and death process. Introduction to reliability analysis: Application of Bayes theorem in real life problem; Reliability analysis of simple syste serial, parallel and combined systems; First order uncertainty and reliability analysis (FORM), First order second mom (FOSM) and Advanced FOSM methods; Applications of risk and reliability analysis in engineering systems.
Text / Reference Books:
 Scheaffer, R. L., Mulekar, M. S. and McClave, J. T., (2011): Probability and statistics for Engineers, Fifth Edition, Broo Cole, Cengage Learning.
 Ang, A. HS., and Tang, W. H., (2006): Probability Concepts in Engineering, Volumes 1. John Wiley and Sons.
 Halder, A and Mahadevan, S., (2000): Probability, Reliability and Statistical Methods in Engineering Design, John Wiley Sons.
 Rao, S.S., (1992): ReliabilityBased Design, McGraw Hill, Inc.
 Harr, M.E., (1987): ReliabilityBased Design in Civil Engineering. McGraw Hill, Inc.
 Ang, A. HS, and Tang, W. H., (1975): Probability Concepts in Engineering Planning and Design, Volumes 2. John Wiley and Sons
 Benjamin, J., and Cornell. A., (1963): Probability, Statistics, and Decision for Civil Engineers. McGraw Hill.
CS3XX  Artificial Intelligence  3006  CS 

 Introduction, Motivation of the course
 Problem Solving: Uninformed search, Informed search, Local Search,
 Game Playing: Minmax, AlphaBeta Pruning, Constraint Satisfaction Problems: Factor Graphs, Backtracking Search, Dynamic Ordering, Arc consistency
 Knowledge, Reasoning and Planning: Propositional and Predicate Calculus, Semantic Nets, Automated Planning
 Machine Learning: Learning from examples and analogy, Naive Bayes, Decision Tree, Introduction to Graphical Models (HMM, MEMM, CRF), Neural Networks
 Application Topics: Introduction to NLP, Introduction to Fuzzy Sets and Logic
References:
 S. Russel and P. Norvig. Artificial Intelligence: A Modern Approach (Third Edition), Prentice Hall, 2009
 E. Rich and K. Knight, Artificial Intelligence, Addison Wesley, 1990
 T. Mitchel, Machine Learning, McGrawHill, 1997
Journals and Conference Proceedings:
 Artificial Intelligence, Machine Learning, ACL Anthology, ICML, ECML etc.
CS2XX  Artificial Intelligence Lab  0033  CS 

Small projects based on the concepts and tools taught in AI class.
CS3XX  Database  3006  CS 

Database system architecture: Data Abstraction, Data Independence, Data Definition and Data Manipulation Languages; Data models: Entityrelationship, network, relational and object oriented data models, integrity constraints and data manipulation operations; Relational query languages: Relational algebra, tuple and domain relational calculus, SQL and QBE; Relational database design: Domain and data dependency, Armstrongs axioms, normal forms, dependency preservation, lossless design; Query processing and optimization: Evaluation of relational algebra expressions, query equivalence, join strategies, query optimization algorithms; Storage strategies: Indices, Btrees, hashing; Transaction processing: Recovery and concurrency control, locking and timestamp based schedulers, multiversion and optimistic Concurrency Control schemes; Recent Trends: XML Data, XML Schema, JSON and “NoSQL Systems, etc.,.
Books:
 Abraham Silberschatz, Henry Korth, and S. Sudarshan, Database System Concepts, McGrawHill.
 Raghu Ramakrishnan, Database Management Systems, WCB/McGrawHill.
 Bipin Desai, An Introduction to Database Systems, Galgotia.
 J. D. Ullman, Principles of Database Systems, Galgotia.
 R. Elmasri and S. Navathe, Fundamentals of Database Systems, AddisonWesley.
 Serge Abiteboul, Richard Hull and Victor Vianu, Foundations of Databases. AddisonWesley
CS34X  Database Lab  0033  CS 

Database schema design, database creation, SQL programming and report generation using a commercial RDBMS like ORACLE/SYBASE/DB2/SQLServer/INFORMIX. Students are to be exposed to front end development tools, ODBC and CORBA calls from application Programs, internetbased access to databases and database administration.
CS2XX  Theory of computation  3006  CS 

Regular Languages: Finite AutomataDeterministic and Nondeterministic, regular operations, Regular Expressions, Equivalence of DFA, NFA and Res, Nonregular Languages and pumping lemma
ContextFree Languages: ContextFree Grammars, Chomsky Normal Form, Pushdown Automata, NonContextFree Languages and pumping lemma, Deterministic ContextFree Languages
Turing Machines: Definition of TM and its variants, Decidability, Reducibility.
Complexity Theory: Time complexity and Space Complexity.
Text Books:
 Introduction to the Theory of Computation, by Michael Sipser,
 Computational Complexity, by Christos H. Papadimitriou, AddisonWesley publishers.
 Computational Complexity: A Modern Approach, by Sanjeev Arora and Boaz Barak.
CS2XX  Machine Learning & DS  3006  CS 

Supervised learning: decision trees, nearest neighbor classifiers, generative classifiers like naive Bayes, linear discriminate analysis, Support vector Machines, feature selection techniques: wrapper and filter approaches, backward selection algorithms, forward selection algorithms, PCA, LDA
Unsupervised learning: Kmeans, hierarchical, EM, Kmedoid, DBScan, cluster validity indices, similarity measures, some modern techniques of clustering
Graphical models: HMM, CRF, MEMM
Semisupervised learning
Primary books
 Pattern recognition and machine learning by Christopher Bishop, Springer Verlag, 2006.
 Hastie, Tibshirani, Friedman the elements of Statistical Learning Springer Verlag
 T. Mitchell. Machine Learning. McGrawHill, 1997.
Supplementary books
 Probability, Random Variables and Stochastic processes by Papoulis and Pillai, 4th Edition, Tata McGraw Hill Edition.
 Linear Algebra and Its Applications by Gilbert Strand. Thompson Books.
 Data Mining: Concepts and Techniques by Jiawei Han, Micheline Kamber, Morgan Kaufmann Publishers.
 A. K. Jain and R. C. Dubes. Algorithms for Clustering Data. Prentice Hall, 1988.
Semester V
XX3XX  Open ElectiveIII  3006 

CS34X  Operating Systems  3006  CS 

Process Management: process; thread; scheduling. Concurrency: mutual exclusion; synchronization; semaphores; monitors; Deadlocks: characterization; prevention; avoidance; detection. Memory Management: allocation; hardware sup port; paging; segmentation. Virtual Memory: demand paging; replacement; allocation; thrashing. File Systems and Imple mentation. Secondary Storage: disk structure; disk scheduling; disk management. (Linux will be used as a running example, while examples will drawn also from Windows NT/7/8.); Advanced Topics: Distributed Systems. Security. RealTime Systems.
Books:
 A. Silberschatz, P. B. Galvin and G. Gagne, Operating System Concepts, 8th Ed, John Wiley & Sons, 2010.
 A. S. Tenenbaum, Modern Operating Systems, 2nd Ed, Prentice Hall of India, 2001.
 H. M. Deitel, P. J. Deitel and D. R. Choffness, Operating Systems, 3rd Ed, Prentice Hall, 2004.
 W. Stallings, Operating Systems: Internal and Design Principles, 5th Ed, Prentice Hall, 2005.
 M. J. Bach, The Design of the UNIX Operating System, Prentice Hall of India, 1994.
 M. K. McKusick et al, The Design and Implementation of the 4.4 BSD Operating System, Addison Wesley, 1996.
CS342  Operating Systems Lab  0–0–33  CS 

Programming assignments to build different parts of an OS kernel.
CS3XX  Computer Network  3006  CS 

Evolution of computer networks; Physical Layer: Theoretical basis for data communication, transmission media and impairments, switching systems Medium Access Control Sublayer: Channel allocation Problem, multiple access protocols, Ethernet Data link layer: Framing, HDLC, PPP, sliding window protocols, error detection and correction Network Layer: Internet addressing, IP, ARP, ICMP, CIDR, routing algorithms (RIP, OSPF, BGP); Transport Layer: UDP, TCP, flow control, congestion control; Introduction to quality of service; Application Layer: DNS, Web, email, authentication, encryption.
Books:
 Peterson & Davie, Computer Networks, A Systems Approach: 5th Edition
 William Stallings Data and Computer Communication, Prentice Hall of India.
 Behrouz A. Forouzan, Data Communication and Networking, McGrawHill.
 Andrew S. Tanenbaum, Computer Networks, Prentice Hall.
 Douglas Comer, Internetworking with TCP/IP, Volume 1, Prentice Hall of India.
 W. Richard Stevens, TCP/IP Illustrated, Volume 1, AddisonWesley.
CS3XX  Computer Network Lab  0033  CS 

Simulation experiments for protocol performance, configuring, testing and measuring network devices and parameters/policies; network management experiments; Exercises in network programming.
CS3XX  Deep Learning  3006  CS 

This course will provide basic understanding of deep learning and how to solve classification problems having large amount of data. In this course several public domain tools will be demonstrated to build deep learning network. Course content will be as follows: Brief introduction of big data problem, Overview of linear algebra, probability, numerical computation
 Scalars, vectors, matrix, tensors, norms, Eigen value, eigenvector, singular value decomposition, determinant
 Probability distribution, Bayes rule, conditional probability, variance, covariance
 Overflow, underflow, gradient based optimization, least square.
Neural network  Perceptron, Multilevel perceptron, Universal approximation theorem
Tutorial for Tools
 Keras, Theano, TensorFlow
 Demo using MNIST
 Deep learning network
 Shallow vs Deep network
 Deep feedforward network
 Gradient based learning  Cost function, soft max, sigmoid function
 Hidden unit  ReLU, Logistic sigmoid, hyperbolic tangent
 Architecture design
 Back propagation algorithm  Chain rule of calculus
 SGD
 Regularization  parameter norm penalties, drop out, noise robustness, early stopping, Batch normalization
 Optimization for training deep model Adagrad, Nesterov momentum
 Advanced topics
 Convolutional Neural Network
 Recurrent Neural Network/ Sequence modeling
 Practical applications  MNIST, etc.
Books
 Ian Goodfellow, Yoshua Bengio and Aaron Courville, “Deep Learning”
 Richard S. Sutton & Andrew G. Barto, Reinforcement Learning: An Introduction” (available online)
 Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie, “The elements of statistical learning”
CS2XX  Innovative Design Lab  0033  CS 

The objective of this lab would be to encourage and provide support to students for some innovative work. The work may focus on inventing a practical solution for a pure Computer Science or multidisciplinary problems. Depending on the nature of the work, it may be carried out in a group or individual mode.
CS3XX  Artificial IntelligenceII  3006  CSE 

 Introduction to the course
 Knowledge Representation: Ontology, Knowledge Graph, Semantic Web3, Uncertain Knowledge and Reasoning: Quantifying uncertainty, Probabilistic Reasoning, Probabilistic Reasoning over time, Multiagent decision making
 Markov Decision Processes: Policy evaluation, Policy improvement, Policy iteration, Value iteration
 Reinforcement Learning: Monte Carlo, SARSA, Qlearning, Exploration/Exploitation, Function approximation, Deep reinforcement learning
 Evolutionary Computation: Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Differential Evolution
 Conversational AI, Explainable AI, Understanding AI Ethics and Safety
References:
 S. Russel and P. Norvig. Artificial Intelligence: A Modern Approach (Third Edition), Prentice Hall, 2009
 E. Rich and K. Knight, Artificial Intelligence, Addison Wesley, 1990
 Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learnng, MIT Press, 2016
 Daphne Koller and Nir Friedman, Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009.
 Sutton and Barto. Reinforcement Learning: An Introduction. Available free online.
 Hastie, Tibshirani, and Friedman. The elements of statistical learning. Available free online.
Journals and Conference Proceedings:
 Artificial Intelligence, Machine Learning, ACL Anthology, COLING, ICML, ECML, Proceedings of Uncertainty in AI, ICCV, ICLR etc.
Semester VI
HS3XX  HSS ElectiveIII  3006  HSS 

CS3XX  Advance Machine Learning  3006  CS 

Mathematics of machine learning,
Overview of supervised, unsupervised learning and Multitask learning
 Undirected graphical models: Undirected graphical models: overview, representation of probability distribution and conditional independence statement, Factorization, CRFs, Applications to NLP, Markov networks.
 Directed graphical models: Bayesian networks.
 Deep Networks for Sequence Prediction: Encoderdecoder models (case study translation), Attention models, LSTM, Memory Networks
 Deep Network for Generation – Sequence to Sequence Models – Variational Auto encoders – Generative Adversarial Networks (GANs) – Pointer Generator Networks – Transformer Networks
Learning Representations – Learning representations for text – Word2Vec, FastText, GLOVE, BERT – Learning representations in images based on context prediction (C. Doersch et al. Unsupervised Visual Representation Learning by Context Prediction, ICCV 2015)
Time series forecasting: models and casestudies
Modern clustering techniques: Multiobjective optimization for clustering, Deep learning for clustering Online Learning, Mistake Bounds, Subspace clustering
Metalearning and federated learning
Casestudies: Recent topics for solving various problems of natural language processing, bioinformatics, information retrieval
Books:
 Kevin P. Murphy. Machine Learning: A Probabilistic Perspective. MIT Press 2012
 Ian Goodfellow, Yoshua Bengio and Aaron Courville. Deep Learning. MIT Press 2016
Other relevant textbooks:
 Yoav Goldberg. 2016. A primer on neural network models for natural language processing. J. Artif. Int. Res. 57, 1 (September 2016), 345420.
 R. G. Cowell, A. P. Dawid, S. L. Lauritzen and D. J. Spiegelhalter. "Probabilistic Networks and Expert Systems". SpringerVerlag. 1999.
 M. I. Jordan (ed). "Learning in Graphical Models". MIT Press. 1998.
CS3XX  Bayesian Data Analysis  3006  CS 

Introduction: Objective vs Subjective Definition of Probability, Axiomatic Definition of Probability, Bayes Theorem Applications of Bayes Theorem
Decision Theoretic framework and major concepts of Bayesian Analysis Likelihood, Prior and posterior, Loss function, Bayes Rule, Conjugate priors and other priors, Sensitivity Analysis, Posterior Convergence, Oneparameter Bayesian models, Poisson Model for Count data, Binomial Model for Count data, Multiparameter Bayesian models, Univariate Gaussian Model, Multivariate Gaussian Model, Covariance Matrix with Wishart Distribution
Bayesian solution for highdimensional problem in Covariance matrix for Portfolio Risk Analysis
MultinomialDirichlet Allocation Models for Topic Model
Bayesian Machine Learning, Hierarchical Bayesian Model
Regression with Ridge prior, LASSO prior, Classification with Bayesian Logistic Regression, Discriminant Analysis
Bayesian Computation with Stan
Estimation of Posterior Mode with Optimization
Estimation of Posterior Mean and other summary with Monte Carlo Simulation
AcceptRejection Sampling
Importance Sampling
Markov Chain and Monte Carlo
MetropolisHastings
Hamiltonian Monte Carlo
Gaussian Process Regression
Introduction
Gaussian Process Regression for Big Data
Bayesian Optimization
Textbook:
 John Kruschke: Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (2014), Academic Press
 Carl Edward Rasmussen and Christopher K. I. Williams: Gaussian Processes for Machine Learning, MIT Press (2006) Available Online
 Sourish Das, Sasanka Roy, Rajiv Sambasivan : Fast Gaussian Process Regression for Big Data, Big Data Research, Volume 14, December 2018, Pages 1226: Preprint Available Here; Python Implementation
CS3XX  Programming for AI/ML  0033  CS 

Programming assignments based on tools and techniques taught in ML/DL/AIII courses. Prolog; Assignment on Logistic regression; Assignment on kmeans clustering.
Introduction to Tensorflow, Pytorch, Keras.
Usage of Tensorflow, Pytorch and/or Keras: Simple ML examples; Assignments on NNs; Assignments on CNNs; Assignments on RNN; Assignment on LSTM, GRU
References:
 Pytorch: https://pytorch.org/assets/deeplearning/DeepLearningwithPyTorch.pdf
 First Contact with TensorFlow: Get Started with Deep Learning Programming by Jordi Torres
 https://analyticsindiamag.com/top10freebooksandresourcesforlearningtensorflow/
 https://keras.io/getting_started/learning_resources/
 HandsOn Machine Learning with ScikitLearn, Keras, and TensorFlow (second edition), by Aurélien Géron
CS3XX  Computer Vision  3006  CS 

The course will have a comprehensive coverage of theory and computation related to imaging geometry, and scene understanding. It will also provide exposure to clustering, classification and deep learning techniques applied in this area. Camera geometry, Stereo geometry, Stereo Geometry, Feature detection and description Feature matching and model fitting, Color Processing, Range image processing Clustering and classification, Dimensionality Reduction and Sparse Representation Deep Neural Architecture and applications.
CS4XX  Capstone ProjectI  0033  CS 

The objective of this project would be to encourage and provide support to students for some innovative work. The work may focus on inventing a practical solution for a AI/DS or multidisciplinary problems. Depending on the nature of the work, it may be carried out in a group or individual mode.
Semester VII
XX4XX  Open Elective  3006  Science/ Engineering Deptt. 

CS4XX  Natural Language Processing  3006  CS 

Course Contents:
Intro to NLP
Simple Word Vector representations: word2vec, GloVe: Distributed Representations of Words and Phrases and their Compositionality, [Efficient Estimation of Word Representations in Vector Space
Advanced word vector representations: language models, GloVe: Global Vectors for Word Representation
PoS tagging and named entity recognition
Language modeling and other tasks, Opinion Mining
Parsing, Sentence classification
Machine Translation,
Dynamic Memory Networks
Question Answering, Natural Language Generation and Summarization
Contextual Word Representations: BERT
Text and References:
 Dan Jurafsky and James H. Martin. Speech and Language Processing (3rd ed. draft)
 Jacob Eisenstein. Natural Language Processing
 Yoav Goldberg. A Primer on Neural Network Models for Natural Language Processing
 Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning
 Delip Rao and Brian McMahan. Natural Language Processing with PyTorch (requires Stanford login).
 Michael A. Nielsen. Neural Networks and Deep Learning
 Eugene Charniak. Introduction to Deep Learning
Conferences: ACL (Association for Computational Linguistics), EACL (European Association for Computational Linguistics), COLING (International Conference on Computational Linguistics), ICML (International Conference on Machine Learning), IJCNLP (International Joint Conference on Natural Language Processing), AAAI (American Association of Artificial Intelligence), ECAI (European Conference on AI), HLT/NAACl (Human language Technology/ North American Association for Computational Linguistics), ICON (International Conference on Natural Language Processing) etc.
CS4XX  Big data Analytics  2026  CS 

Part 1: Introduction to Big Data:
Why Big Data and Where did it come from? Characteristics of Big Data Volume, Variety, Velocity, Veracity, Valence, Value, Challenges and applications of Big Data
Part 2: Enabling Technologies for Big Data:
Introduction to Big Data Stack, Introduction to some Big Data distribution packages
Part 3: Big Data Computing Technology:
Overview of Apache Spark, HDFS, YARN, Introduction to MapReduce, MapReduce Programming Model with Spark, MapReduce Example: Word Count, Page Rank etc.
Part 4: Big Data Storage Technology:
CAP Theorem, Eventual Consistency, Consistency TradeOffs, ACID and BASE, Introduction to Zookeeper and Paxos, Introduction to Cassandra, Cassandra Internals,Introduction to HBase, HBase Internals
Part 5: Big Data Analytics framework:
Introduction to Big Data Streaming Systems, Big Data Pipelines for RealTime computing, Introduction to Spark Streaming, Kafka, Streaming Ecosystem
Part 6: Scalable Machine Learning for Big Data:
Overview of Big Data Machine Learning, Mahout Introduction, Big Data Machine Learning Algorithms in Mahout kmeans, Naïve Bayes etc.
Part 7: Scalable Machine learning with Spark for Big Data Analytics:
Big Data Machine Learning Algorithms in Spark Introduction to Spark MLlib, Introduction to Deep Learning for Big Data
Part 8: Large Scale Graph Processing for Big Data:
Introduction to Pregel, Introduction to Giraph, Introduction to Spark GraphX Laboratory Component: Big Data Analytics Practical sessions on the above topics.
Text Books:
 Bart Baesens, Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, Wiley, 2014
Reference Book:
 Dirk Deroos et al., Hadoop for Dummies, Dreamtech Press, 2014.
 Chuck Lam, Hadoop in Action, December, 2010  336 pages ISBN: 9781935182191
 Mining of Massive Datasets. Leskovec, Rajaraman, Ullman, Cambridge University Press
 Data Mining: Practical Machine learning tools and techniques, by I.H. Witten and E. Frank
 Erik Brynjolfsson et al., The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, W. W. Norton & Company, 2014
CS4XX  ElectiveI  3006  CS 

CS4XX  ElectiveII  3006  CS 

CS4XX  Capstone ProjectII  0033  CS 

The objective of this project would be to encourage and provide support to students for some innovative work. The work may focus on inventing a practical solution for a AI/DS or multidisciplinary problems. Depending on the nature of the work, it may be carried out in a group or individual mode.
Semester VIII
CS4XX  Big data Security  2026  CS 

Data Security Overview, Basic Cryptography, symmetric key Encryption, Asymmetric key encryption, Hash function, User Authentication and Access Control, Database access control, Access control for Distributed system Cryptography for Big data Security, Homomorphic Encryption, Secure multiparty computation, Secure data access for big data Service, Integrating with cloud computing Security, Provable Data possession, Symmetric Secure Searchable Encryption, Asymmetric Secure Searchable Encryption, Privacy of out sourced data storage, Integrity of outsourced data storage and processing.
Text Books:
 Database and Applications Security: Integrating Information Security and Data Management
 Referred Journal/ Conference publication
XX4XX  Elective III  3006    

CS4XX  Elective IV  3006   

CS4XX  individual Project  300/66   

The students who work on a project are expected to work towards the goals and milestones set in AI&DS. At the end there would be demonstration of the solution and possible future work on the same problem. A dissertation outlining the entire problem, including a literature survey and the various results obtained along with their solutions is expected to be produced.
Proposed Electives
Database & Data Mining
Introduction to Computational Topology
Geometric and Topological Modelling for Scientists and Engineers
Mobile Robotics
Cloud Computing
Statistical signal processing
Estimation and Detection
information theory and coding
Introduction to Network Science
Cryptography
High Performance Computing
Social Text Mining,
AI in Healthcare
Conversational AI
Discrete Differential Geometry
Computational Geometry
Topological Data Analysis
Planning Algorithms,
A Mathematical Introduction to Robotics
Advanced Signal Processing for AI and DS
Edge AI
Statistical signal processing,
Estimation and Detection,
Applications of artificial intelligence in Chemistry
Graph Representation Learning,
Advanced Network Science,
Distributed Machine Learning
Deep Learning for NLP
Conversational Artificial Intelligence,
Machine Translation,
Information Retrieval and Mining,
Sentiment and Emotion Analysis
Advanced Operating Systems
Signal Processing and Machine Learning for Data Science
Applied Time Series Analysis
Probability and Random Process
Applied Time Series Analysis
B.Tech (CS) Courses
Course Structure (IIV Sem. for 2021 Onwards and VVIII Sem. for 201920 Batches)
Semester  Course Code  Course name  LTPCredit  Offering Department 

Semester I  CE111  Engineering Drawing  1035  Civil 
EE101  Electrical Sciences  3108  Electrical  
HS103  Communicative English for Engineers  20.516  Humanities and Social Science  
MA101  Mathematics I  3108  Mathematics  
ME110  WorkshopI  0033  Mechanical  
PH103  Physics –I  3108  Physics  
PH 110  Physics Laboratory  0033  Physics  
Total credits: 41  
Semester II  CB102 & CE102  Biology and Environmental Studies  3006  CB & CE 
CH103  Introductory Chemistry  3108  Chemistry  
CH110  Chemistry Laboratory  0033  Chemistry  
CS102  Programming and Data Structures  3006  CS  
CS112  Programming and Data Structures Laboratory  0033  CS  
EE103  Basic Electronics Laboratory  0033  EE  
MA102  Mathematics –II  3108  Mathematics  
ME102  Engineering Mechanics  3108  ME  
Total credits: 45  
Semester III  MA2XX  Mathematical III  3108  Mathematics 
HS2XX  HSS Elective – I  3006  Humanities and Social Science  
CS204  Algorithms  3006  CS  
CS224  Algorithms Laboratory  0033  CS  
CS203  Discrete Mathematics  3006  CS  
CS227  Digital Systems  2026  CS  
CS271  Optimization techniques  3006  CS  
CS230  Software Lab/Tools  0033  CS  
Total credits: 44  
Semester IV  HS2XX  HSS Elective – II  3006  Humanities and Social Science 
MA2XX  Open Elective I (Prob. Theory and Random Processes)  3006  Mathematics  
CS2XX  Computer Architecture  3006  CS  
CS2XX  Computer Architecture Lab  0033  CS  
CS2XX  Theory of computation  3006  CS  
CS2XX  Database  3006  CS  
CS2XX  Database Lab  0033  CS  
Total credits: 36  
Semester V  XX3nn  Open Elective  3006  
CS303  Formal Language & Automata Theory  3108  CS  
CS321  Computer Architecture  3006  CS  
CS354  Database  3006  CS  
CS355  Database Lab  0033  CS  
CS322  Computer Architecture Lab  0033  CS  
Total credits: 32  
Semester VI  HS3nn  HSS Elective  3006  Humanities and Social Science 
CS341  Operating System  3006  CS  
CS358  Computer Network  3006  CS  
CSXXX  CS Elective 1  3006  CS  
CS359  Computer Network Lab  0033  CS  
CS399  Seminar  0033  CS  
CS342  Operating Systems Lab  0135  CS  
CS3XX  Capstone Project  0033  CS  
Total credits: 35  
Semester VII  XX4nn  Open Elective  3006  
CSXXX  CS Elective 2  3039  CS  
CSXXX  CS Elective 3  3006  CS  
CSXXX  CS Elective 4  3006  CS  
CS491  ProjectI  0066  CS  
Total credits: 33  
Semester VIII  CSXXX  CS Elective 5  3006  CS 
CSXXX  CS Elective 6  3006  CS  
CSXXX  CS Elective 7  3006  CS  
CS492  ProjectII  001212  CS  
Total credits: 30  
Total credits for B.Tech CS: 296 
Semester I
Engineering Drawing
CE111  Engineering Drawing  1035  Civil 

Geometrical construction of simple plane figure:Bisecting the line, draw perpendicular, parallel line, bisect angle, trisect angle, construct equatorial triangle, square, polygon, inscribed circle.
Free hand sketching: prerequisites for freehand sketching, sketching of regular and irregular figures.
Drawing scales: Engineering scale, graphical scale, plane scale, diagonal scale, comparative scale, scale of chord.
Orthographic projection: Principle of projection, method of projection, orthographic projection, plane of projection, first angle of projection, third angle of projection, reference line.
Projection of points, lines and plane: A point is situated in the first quadrant, point is situated in the second quadrant, point is situated in the third quadrant, point is situated in the fourth quadrant, projection of line parallel to both the plane, line contained by one or both the plane, line perpendicular to one of the plane, line inclined to one plane and parallel to other, line inclined to both the plane, true length of line.
Missing views: Drawing of missing front view of a solid, missing top view of solids, missing side view of solids, Orthographic projection of simple solid: Introduction, types of solid, projection of solid when axis perpendicular to HP, axis perpendicular to VP, axis parallel to both HP and VP, axis inclined to both HP and VP.
Orthographic projection of simple solid: Introduction, types of solid, projection of solid when axis perpendicular to HP, axis perpendicular to VP, axis parallel to both HP and VP, axis inclined to both HP and VP.
Text and Reference Books:
 B. Agrawal and CM Agrawal, Engineering Drawing, Tata McGrawHill Publishing Company Limited, 2008.
 D. A. Jolhe, Engineering Drawing, Tata McGrawHill Publishing Company Limited, 2006.
 K. Venugopal, Engineering Drawing and Graphics, 2nd ed., New Age International, 1994.
Electrical Sciences
EE101  Electrical Sciences  3108  Electrical 

Circuit Analysis Techniques, Circuit elements, Simple RL and RC Circuits, Kirchhoff’s law, Nodal Analysis, Mesh Analysis, Linearity and Superposition, Source Transformations, Thevnin's and Norton's Theorems, Time Domain Response of RC, RL and RLC circuits, Sinusoidal Forcing Function, Phasor Relationship for R, L and C, Impedance and Admittance.
Semiconductor Diode, Zener Diode, Rectifier Circuits, Clipper, Clamper, Bipolar Junction Transistors, Transistor Biasing, Transistor Small Signal Analysis, Transistor Amplifier, Operational Amplifiers, Opamp Equivalent Circuit, Practical Opamp Circuits, DC Offset, Constant Gain Multiplier, Voltage Summing, Voltage Buffer, Controlled Sources, Instrumentation Circuits, Active Filters and Oscillators.
Number Systems, Logic Gates, Boolean Theorem, Algebraic Simplification, Kmap, Combinatorial Circuits, Encoder, Decoder, Combinatorial Circuit Design, Introduction to Sequential Circuits.
Magnetic Circuits, Mutually Coupled Circuits, Transformers, Equivalent Circuit and Performance, Analysis of ThreePhase Circuits, Electromechanical Energy Conversion, Introduction to Rotating Machines.
Text and Reference Books:
 C. K. Alexander and M. N. O. Sadiku, Fundamentals of Electric Circuits, 3rd Edition, McGrawHill, 2008.
 W. H. Hayt and J. E. Kemmerly, Engineering Circuit Analysis, McGrawHill, 1993.
 Donald A Neamen, Electronic Circuits; analysis and Design, 3rd Edition, Tata McGrawHill Publishing Company Limited.
 Adel S. Sedra, Kenneth C. Smith, Microelectronic Circuits, 5th Edition, Oxford University Press, 2004.
 R. L. Boylestad and L. Nashelsky, Electronic Devices and Circuit Theory, 6th Edition, PHI, 2001.
 M. M. Mano, M. D. Ciletti, Digital Design, 4th Edition, Pearson Education, 2008.
 Floyd and Jain, Digital Fundamentals, 8th Edition, Pearson.
 A. E. Fitzgerald, C. Kingsley Jr. and S. D. Umans, Electric Machinery, 6th Edition, Tata McGrawHill, 2003.
 D. P. Kothari and I. J. Nagrath, Electric Machines, 3rd Edition, McGrawHill, 2004.
Communicative English for Engineers
HS103  Communicative English for Engineers  20.516  HSS 

In today’s ‘global village’, there are many who believe that ‘Communication is like breathing and life would cease to continue without it’. This particular course on communication skills imbibes the same and therefore, it aims to equip the students with getting the basics right of communication and presentation skills for academic and professional purposes. It is designed to help the second language learners acquire fluency in both spoken and written English to communicate information with clarity, precision and confidence especially in the professional sphere. It will introduce learners not only to the basic concepts in communication but also focus on providing them a handson experience of the same. It is hoped that after commanding the skills required in spoken and written English, learners will be able to express themselves more effectively.
The course will have ten units and shall focus on the following topics:
Unit 1: Language and Communication
What is Communication
Nature, Style and Process of Communication
Communication Barriers
Objectives and Importance of Communication
Formal and Informal Communication
Verbal and NonVerbal Communication
Unit 2: English Language Remedial Skills
Construction of Sentences
SubjectVerb Agreement
Tenses
Active and Passive Voice
Direct and Indirect Speech
Common Errors
Unit 3: Oral Skills
Public Speaking
Dealing with lack of confidence
Making an Effective Presentation
Telephone Etiquette
Understanding GD
Why conduct a GD?
How to gear up for a GD?
Different Phases of GD
Unit 4: Listening Skills
Meaning of Listening
Different Types of Listening
Barriers to Listening and Methods to overcome them
Various strategies to develop effective Listening
Semantic Markers
Unit 5: Reading Skills
What is Reading?
Types of Reading
Reading Comprehension
Unit 6: Writing Skills
Business Correspondence
Element and Style of Writing
Report Writing
Notice, Agenda and Minutes
Unit 7: Interview Techniques
How to prepare for an Interview
An Interview
Text and Reference Books:
 V. S. Kumar, P.K. Dutt and G. Rajeevan, A Course in Listening and SpeakingI, Foundation books, 2007.
 V.Sasikumar, P.KiranmaiDutt, Geetha Rajeevan, "A Course in Listening and SpeakingII', Foundation books, 2007.
 Rizvi, Ashraf, Effective Technical Communication, Tata McGraw Hill, 2005.
 Nitin Bhatnagar and MamtaBhatnagar, 'Communicative English for Engineers and Professionals, Pearson, 2010.
Mathematics I
MA101  Mathematics I  3108  Mathematics 

Properties of real numbers. Sequences of real numbers, montone sequences, Cauchy sequences, divergent sequences. Series of real numbers, Cauchy’s criterion, tests for convergence. Limits of functions, continuous functions, uniform continuity, montoneand inverse functions. Differentiable functions, Rolle's theorem, mean value theorems and Taylor's theorem, power series. Riemann integration, fundamental theorem of integral calculus, improper integrals. Application to length, area, volume, surface area of revolution. Vector functions of one variable and their derivatives. Functions of several variables, partial derivatives, chain rule, gradient and directional derivative. Tangent planes and normals. Maxima, minima, saddle points, Lagrange multipliers, exact differentials. Repeated and multiple integrals with application to volume, surface area, moments of inertia. Change of variables. Vector fields, line and surface integrals. Green’s, Gauss’ and Stokes’ theorems and their applications.
Text Books:
 G. B. Thomas and R. L. Finney, Calculus and Analytic Geometry, 6th Ed/9th Ed, Narosa/ Addison Wesley/ Pearson, 1985/ 1996.
 T. M. Apostol, Calculus, Volume I, 2nd Ed, Wiley, 1967. T. M. Apostol, Calculus, Volume II, 2nd Ed, Wiley, 1969.
Reference Books:
 R. G. Bartle and D. R. Sherbert, Introduction to Real Analysis, 5th Ed, Wiley, 1999.
 J. Stewart, Calculus: Early Transcendentals, 5th Ed, Thomas Learning (Brooks/ Cole), Indian Reprint, 2003.
WorkshopI
ME110  WorkshopI  0033  Mechanical 

Sheet Metal Working:
Sheet material: GI sheets, aluminium, tin plate, copper, brass etc.; Tools: steel rule, Vernier calipers, micrometer, sheet metal gauge, scriber, divider, punches, chisels, hammers, snips, pliers, stakes etc.; operations: scribing, bending, shearing, punching etc.; Product development: hexagonal box with cap, funnel etc.
Pattern Making and Foundry Practice:
Pattern material: wood, cast iron, brass, aluminium, waxes etc.; Types of patterns: split, single piece, match plate etc.; Tools: cope, drag, core, core prints, shovel, riddle, rammer, trowel, slick, lifter, sprue pin, bellow, mallet, vent rod, furnace etc. Moulding sands: green sand, dry sand, loam sand, facing sand etc., Sand casting: Sand preparation, mould making, melting, pouring, and cleaning. Joining: Classifications of joining processes; Introduction to Arc welding processes; power source; electrodes; edge preparation by using tools bench vice, chisels, flat file, square file, half round file, round file, knife edge file, scrapers, hacksaws, try squares; cleaning of job, Job: lap and butt joints using manual arc welding.
Machining Centre:
Introduction to different machine tools; Working principle of lathe, milling, drilling etc.; Setting and preparation of job using lathe and milling; Performing different operations namely, straight turning, taper turning, knurling, thread cutting etc.; Introduction to dividing head, indexing, performing operation in milling using indexing mechanism.
CNC Centre:
Introduction to CNC machines; Fundamentals of CNC programming using G and M code; setting and operations of job using CNC lathe and milling, tool reference, work reference, tool offset, tool radius compensation.
Text and Reference Books:
 H. Choudhury, H. Choudhary and N. Roy, Elements of Workshop Technology, vol. I,Mediapromoters and Publishers Pvt. Ltd., 2007.
 W. A. J. Chapman, Workshop Technology, Part 1, 1st South Asian Edition, Viva Book Pvt Ltd., 1998.
 P.N. Rao, Manufacturing Technology, Vol.1, 3rd Ed., Tata McGraw Hill PublishingCompany, 2009.
 B.S. Pabla, M.Adithan, CNC machines,New Age International, 2012.
 G. B. Thomas and R. L. Finney, Calculus and Analytic Geometry, 6th Ed/9th Ed, Narosa/Addison Wesley/Pearson, 1985/1996.
 T. M. Apostol, Calculus, Volume I, 2nd Ed, Wiley, T. M. Apostol, Calculus, Volume II, 2nd Ed, Wiley, 1969/1967.
PhysicsI
PH103  PhysicsI  3–1–0–8  PH 

Orthogonal coordinate systems and frames of reference, conservative and nonconservative forces, workenergy theorem, potential energy and concept of equilibrium; Rotation about fixed axis, translationalrotational motion, vector nature of angular velocity, rigid body rotation and its applications, Euler's equations; Gyroscopic motion and its application; Accelerated frame of reference, centrifugal and Coriolis forces.
Harmonic oscillator, damped and forced oscillations, resonance, coupled oscillations, small oscillation, normal modes, longitudinal and transverse waves, wave equation, plane waves, phase velocity, superposition wave packets and group velocity, two and threedimensional waves.
Failure of classical concepts, Black body radiation, photoelectric effect, Compton effect, Davison and Germer's experiment, FrankHertz experiment, Bohr's theory, Sommerfeld's model, correspondence principle, Planck hypothesis, De Broglie's hypothesis, Hilbert space, observables, Dirac notation, principle of superposition, wave packets, phase and group velocities, probability & continuity equation, eigenvalues and Eigen functions, orthonormality, expectation values, uncertainty principle, postulates of Quantum Mechanics, Schrodinger equation & its applications to 1D potentials, field quantization, periodic potential wells: Kronig Penny model and origin of band gap.
Textbooks:
 D. Kleppner and R. J. Kolenkow, An introduction to Mechanics, Tata McGrawHill, New Delhi, 2000.
 David Morin, Introduction to Classical Mechanics, Cambridge University Press, NY, 2007.
 Frank S. Crawford, Berkeley Physics Course Vol 3: Waves and Oscillations, McGraw Hill, 1966.
 Eyvind H. Wichmann, Berkeley Physics Course Vol 4: Quantum physics, McGraw Hill, 1971.
Reference Books:
 R. P. Feynman, R. B. Leighton and M. Sands, The Feynman Lecture in Physics, Vol I, Narosa Publishing House, New Delhi, 2009.
 R. P. Feynman, R. B. Leighton and M. Sands, The Feynman Lecture in Physics, Vol III, Narosa Publishing House, New Delhi, 2009.
 R. Eisberg and R. Resnick, Quantum Physics of atoms, molecules, solids, nuclei and particles, John Wiuley and Sons (Asia) Pvt. Ltd., Singapore, 2002.
 A. J. Dekker, Solid State Physics, Macmillan Pub. India Ltd., New Delhi, 2009.
 David J. Griffith, Introduction to Quantum Mechanics, Pearson Education Ltd, New Delhi, 2009.
 B.H. Bransden& C.J. Joachain, Quantum Mechanics, Pearson Education Ltd, New Delhi, 2008.
Physics Laboratory
PH110  Physics Laboratory  0033  PH 

The list of experiments is as follows:
 Instructions to Students
 Introduction to Error Analysis
Ex 1 Decay of Current in A Capacitive Circuit
Ex 2 QFactor of an LCR Circuit
Ex 3 Study of Hall Effect
Ex 4 Speed of Sound in Air
Ex 5 ‘g’ by A Compound Pendulum
Ex 6 Speed of Light in Glass
Ex 7 Determination of e/m
Ex 8 Interference of Light: Newton’s Ring
Ex 9 Surface Tension of Water by Method of Capillary Ascent
Ex 10 Determination of Plank’s constant by Photoelectric Effect
Second Semester
Biology and Environment Studies
CB102&CE102  Biology and Environment Studies  3006  CB & CE 

Module 1  Biology: 1. Cell – Structure and logic of optimization; 2. Blood – The following tissue – Basis and rationale; 3. Organs – Structure, function, interactions, failure; 4. Molecular basis of disorders – example: Diabetes; 5. Modern techniques of evaluations and corrections; 6. Open discussions – Feedback from students
Module 2 – Environmental Science / Studies: 1.Ecology and Sustainable Development – Ecosystems, Natural cycles, Biodiversity, Man and environment; 2. Water Resources – Hydrologic cycle and its components, Groundwater and surface water, Water quality; 3. Environmental Sanitation: Conventional and ecological sanitation; 4. Environmental Pollution and Control – Air, Water, Soil, Noise Pollution, Solid and Hazardous Waste, Biomedical Waste, Ewaste: Sources, effect, treatment and control; 5. Environmental Legislations and Standards; 6.Current Environmental Issues: Greenhouse gases and global warming, Acid rain, Ozone layer depletion, Climate change
Text Books:
 Any basic Biology Book of CBSE Curriculum at +2 Level/ Etext Books
 Davis, M.L. and Masten,S.J., Principles of Environmental Engineering and Science,2nd Edition, McGrawHill, 2013.
 Kaushik, A. and Kaushik, C.P., Perspectives in Environmental Studies, 4thEdition, New Age International, 2014.
Reference Books:
 Botkin,D.B. and Keller,E.A., Environmental Science,8th Edition, Wiley, 2012.
 Cunningham, W.P. and Cunningham, M.A., Environmental Science: A Global Concern, 13thEdition, McGrawHill, 2015
CH103  Introductory Chemistry  3108  Chemistry 

PHYSICAL CHMEISTRY
Thermodynamics: The fundamental definition and concept, the zeroth and first law. Work, heat, energy and enthalpies. Second law: entropy, free energy and chemical potential. Change of Phase. Third law. Chemical equilibrium, Chemical kinetics: The rate of reaction, elementary reaction and chain reaction.
Electrochemistry: Conductance of solutions, equivalent and molar conductivities and its variation with concentration. Kohlrausch’s lawionic mobilities, Transference number of ions. activities, application of DebyeHuckel theory. The Walden’s rule. DebyeHuckelOnsager treatment. Electrochemical cells, Nernst equation. Application of EMF measurements. Liquid junction potential, commercial cells – the primary and secondary cells. Fuel cells.
INORGANIC CHEMISTRY
Coordination chemistry: ligand, nomenclature, isomerism, stereochemistry, valence bond, crystal field and molecular orbital theories. Bioinorganic chemistry: Trace elements in biology, heme and nonheme oxygen carriers, haemoglobin and myoglobin; organometallic chemistry.
ORGANIC CHEMISTRY
Stereo and regiochemistry of organic compounds, conformers. Bioorganic chemistry: amino acids, peptides, proteins, enzymes, carbohydrates, nucleic acids and lipids. Modern techniques in structural elucidation of compounds (UV – Vis, IR, NMR). Solid phase synthesis and combinatorial chemistry. Green chemical processes.
Textbooks:
 P. W. Atkins, Physical Chemistry, ELBS, 5th Ed, 1994.
 J. O'M. Bockris and A. K. N. Reddy, Modern Electrochemistry, Vol. 1 and 2, Kluwer Academic, 2000.
 K. L. Kapoor, A Textbook of Physical Chemistry, Macmillan India, 2nd Ed, 1986.
 F. A. Cotton and G. Wilkinson, Advanced Inorganic Chemistry, Wiley Eastern Ltd, New Delhi, 3rd Ed, 1972 (reprint in 1998).
 D. J. Shriver, P. W. Atkins and C. H. Langford, Inorganic Chemistry, ELBS, 2nd Ed, 1994.
 S. H. Pine, Organic Chemistry, McGraw Hill, 5th Ed, 1987
Reference Books:
 Levine, Physical Chemistry, McGraw Hill, 4th Ed, 1995.
 J. E. Huheey, E. A. Keiter and R. L. Keiter, Inorganic Chemistry: Principle, structure and reactivity, Harper Collins, 4th Ed, 1993.
 L. G. Wade Jr., Organic Chemistry, Prentice Hall, 1987
CH110  Chemistry Laboratory  0033  Chemistry 

Estimation of metal ion: Determination of total hardness of water by EDTA titration. Experiments based on chromatography: Identification of a mixture containing two organic compounds by TLC. Experiments based on pH metry.: Determination of dissociation constant of weak acids by pH meter. Experiments based on conductivity measurement: Determination of amount of HCl by conductometric titration with NaOH. Synthesis and characterization of inorganic complexes: e.g. Mn(acac)3, Fe(acac)3, cisbis(glycinato)copper (II) monohydrate and their characterization by m. p. IR etc. Synthesis and characterization of organic compounds: e.g. Dibenzylideneacetone. Kinetics: Acid catalyzed hydrolysis of methyl acetate. Verification of BeerLamberts law and determination of amount of iron present in a supplied solution. Experiments based on electro gravimetry and electroplating. Experiments based on magnetometry.
CS102  Programming and Data Structures  3006  CS 

Introduction to digital computers; introduction to programming variables, assignments; expressions; input/output; conditionals and branching; iteration; functions; recursion; arrays; introduction to pointers; structures; introduction to dataprocedure encapsulation; dynamic allocation; linked structures; introduction to data structures stacks, queues and trees; time and space requirements.
References:
 B. W. Kernighan and D. Ritchie, The C Programming Language, Prentice Hall of India (2nd Edition).
 A. Kelley and I. Pohl, A Book on C, Pearson Education (4th Edition).
 P.J. Deitel and H.M. Deitel , C How To Program, Pearson Education (7th Edition).
CS112  Programing and Data Structures Laboratory  0033  CS 

Introduction to Unix commands; Introduction to program development tools vi editor, GNU compiler, testing and debugging, etc.; Implementation of programs in C language.
EE103  Basic Electronics Laboratory  0033  EE 

Experiments using diodes and bipolar junction transistor (BJT): design and analysis of half wave and fullwave rectifiers, clipping circuits and Zener regulators, BJT characteristics and BJT amplifiers; experiments using operational amplifiers (op amps): summing amplifier, comparator, precision rectifier, astable and mono stable multi vibrators and oscillators; experiments using logic gates: combinational circuits such as staircase switch, majority detector, equality detector, multiplexer and demultiplexer; experiments using flipflops: sequential circuits such as non overlapping pulse generator, ripple counter, synchronous counter, pulse counter and numerical display.
Reference Books:
 A. P. Malvino, Electronic Principles. New Delhi: Tata McGrawHill, 1993.
 R. A. Gayakwad, OpAmps and Linear Integrated Circuits. New Delhi: Prentice Hall of India, 2002.
 R.J. Tocci: Digital Systems; PHI, 6e, 2001.
MA102  MathematicsII  3108  MA 

Linear Algebra: Vector spaces (over the field of real and complex numbers). Systems of linear equations and their solutions. Matrices, determinants, rank and inverse. Linear transformations. Range space and rank, null space and nullity. Eigenvalues and eigenvectors. Similarity transformations. Diagonalization of Hermitian matrices. Bilinear and quadratic forms.
Ordinary Differential Equations: First order ordinary differential equations, exactness and integrating factors. Variation of parameters. Picard's iteration. Ordinary linear differential equations of nth order, solutions of homogeneous and nonhomogeneous equations. Operator method. Method of undetermined coefficients and variation of parameters.
Power series methods for solutions of ordinary differential equations. Legendre equation and Legendre polynomials, Bessel equation and Bessel functions of first and second kind. Systems of ordinary differential equations, phase plane, critical point, stability.
Textbooks:
 K. Hoffman and R. Kunze, Linear Algebra, Prentice Hall, 1996.
 T. M. Apostol, Calculus, Volume II, 2nd Ed, Wiley, 1969.
 S. L. Ross, Differential Equations, 3rd Ed, Wiley, 1984.
 E. A. Coddington, An Introduction to Ordinary Differential Equations, Prentice Hall, 1995.
 W.E. Boyce and R.C. DiPrima, Elementary Differential Equations and Boundary Value Problems, 7th Ed, Wiley, 2001.
Reference Books:
 E. Kreyszig, Advanced Engineering Mathematics, 9th Edition, Wiley, 2005.
ME102  Engineering Mechanics  3108  MA 

 Rigid body statics: Equivalent force system. Equations of equilibrium, Freebody diagram, Reaction, Static indeterminacy.
 Structures: 2D truss, Method of joints, Method of section. Beam, Frame, types ofloading and supports, axial force, Bending moment, Shear force and Torque Diagrams for a member:
 Friction: Dry friction (static and kinetic), wedge friction, disk friction (thrust bearing), belt friction, square threaded screw, journal bearings, Wheel friction, Rolling resistance.
 Centroid and Moment of Inertia
 Virtual work and Energy method: Virtual Displacement, principle of virtual work, mechanical efficiency, work of a force/couple (springs etc.), Potential Energy and equilibrium, stability.
 Introduction to stress and strain: Definition of Stress, Normal and shear Stress. Relation between stress and strain, Cauchy formula.
 Stress in an axially loaded member,
 Stresses due to pure bending,
 Complementary shear stress,
 Stresses due to torsion in axisymmetric sections:
 Twodimension state of stress, Mohr’s circle representation, Principal stresses
Text and Reference books:
 I. H. Shames, Engineering Mechanics: Statics and dynamics, 4th Ed, PHI, 2002.
 F. P. Beer and E. R. Johnston, Vector Mechanics for Engineers, Vol I  Statics, 3rd Ed, TataMcGraw Hill, 2000.
 J. L. Meriam and L. G. Kraige, Engineering Mechanics, Vol I  Statics, 5th Ed, John Wiley, 2002.
 E.P. Popov, Engineering Mechanics of Solids, 2nd Ed, PHI, 1998.
 F. P. Beer and E. R. Johnston, J.T. Dewolf, and D.F. Mazurek, Mechanics of Materials, 6th Ed, McGraw Hill Education (India) Pvt. Ltd., 2012.
Third Semester
MA201  MathematicalIII  3–1–0–8  MA 

Complex Analysis: Complex numbers, geometric representation, powers and roots of complex numbers. Functions of a complex variable: Limit, Continuity, Differentiability, Analytic functions, CauchyRiemann equations, Laplace equation, Harmonic functions, Harmonic conjugates. Elementary Analytic functions (polynomials, exponential function, trigonometric functions), Complex logarithm function, Branches and Branch cuts of multiple valued functions. Complex integration, Cauchy's integral theorem, Cauchy's integral formula. Liouville’s Theorem and MaximumModulus theorem, Power series and convergence, Taylor series and Laurent series. Zeros, Singularities and its classifications, Residues, Rouches theorem (without proof), Argument principle (without proof), Residue theorem and its applications to evaluating real integrals and improper integrals. Conformal mappings, Mobius transformation, SchwarzChristoffel transformation.
Fourier series: Fourier Integral, Fourier series of 2p periodic functions, Fourier series of odd and even functions, Halfrange series, Convergence of Fourier series, Gibb’s phenomenon, Differentiation and Integration of Fourier series, Complex form of Fourier series.
Fourier Transformation: Fourier Integral Theorem, Fourier Transforms, Properties of Fourier Transform, Convolution and its physical interpretation, Statement of Fubini’s theorem, Convolution theorems, Inversion theorem
Partial Differential Equations: Introduction to PDEs, basic concepts, Linear and quasilinear first order PDE, Second order PDE and classification of second order semilinear PDE, Canonical form. Cauchy problems. D’ Alembert’s formula and Duhamel’s principle for one dimensional wave equation, Laplace and Poisson equations, Maximum principle with application, Fourier method for IBV problem for wave and heat equation, rectangular region. Fourier method for Laplace equation in three dimensions.
Text Books:
 R. V. Churchill and J. W. Brown, Complex Variables and Applications, 5th Edition, McGrawHill, 1990.
 K. Sankara Rao, Introduction to Partial Differential Equations, 2nd Edition, 2005.
Reference Books:
 J. H. Mathews and R. W. Howell, Complex Analysis for Mathematics and Engineering, 3rd Edition, Narosa, 1998.
 I. N. Sneddon, Elements of Partial Differential Equations, McGrawHill, 1957. E. Kreyszig, Advanced Engineering Mathematics, 9th Edition, Wiley, 2005.
HS2XX  HSS Elective – I  3–0–0–6  HSS 

CS204  Algorithms  3–0–0–6  CS 

Asymptotic notations, introduction to complexity (time/space) analysis of algorithms. Basic introduction to algorithmic paradigms like divide and conquer, recursion, greedy, dynamic programming, etc. Searching: binary search trees, balanced binary search trees, AVL trees and redblack trees, Btrees, hashing. Priority queues, heaps, Interval trees. Sorting: quick sort, heap sort, merge sort, radix sort, bucket sort, counting sort, etc. and their analysis. Graph Algorithms: BFS, DFS, connected components, topological sort, minimum spanning trees, shortest paths, network flow. Reducibility between problems and NPcompleteness: discussion of different NPcomplete problems.
Books
 M. A. Weiss, Data Structures and ProblemSolving Using Java, 2nd Ed, AddisonWesley, 2002.
 T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, Introduction to Algorithms, MIT Press, 2001.
 B. W. Kernighan and D. Ritchie, The C Programming Language, 2nd Ed, Prentice
 Hall of India, 1988.
 A. Aho, J. E. Hopcroft and J. D. Ullman, The Design and Analysis of Computer
 Algorithms, AddisonWesley, 1974.
 S. Sahni, Data Structures, Algorithms and Applications in C++, McGrawHill, 2001.
 M. T. Goodrich and R. Tamassia, Algorithm Design: Foundations, Analysis and Internet
 Examples, John Wiley & Sons, 2001.
CS224  Algorithms Laboratory  0–0–3–3  CS 

The laboratory component will emphasize two areas: Implementation of algorithms covered in class: This will involve running the algorithms under varying input sets and measuring running times, use of different data structures for the same algorithm (wherever applicable) to see its effect on time and space, comparison of different algorithms for the same problem etc. Design of Algorithms: This will involve design and implementation of algorithms for problems not covered in class but related to topics covered in class. The exact set of algorithms to design and implement is to be decided by the instructor. In addition, there will be at least one significantly large design project involving some realworld application. An efficient design of the project should require the use of multiple data structures and a combination of different algorithms/techniques. The lab work can be carried out using any programming language.
CS203  Discrete Mathematics  3–0–0–6  CS 

Propositional logic: Syntax, semantics, valid, satisfiable and unsatisfiable formulas, encoding and examining the validity of some logical arguments; Recurrences, summations, generating functions, asymptotic; Sets, relations and functions: Operations on sets, relations and functions, binary relations, partial ordering relations, equivalence relations, principles of mathematical induction, Finite and infinite sets, countable and uncountable sets, Cantor’s diagonal argument and the power set theorem; Introduction to counting: Basic counting techniques  inclusion and exclusion, pigeonhole principle, permutation, combination, generating function; Algebraic structures and morphisms: semigroups, groups, subgroups, homomorphism, rings, integral domains, fields; Introduction to graphs: paths, connectivity, subgraphs, isomorphic and homeomorphic graphs, trees, complete graphs, bipartite graphs, matchings, colourability, planarity, digraphs;
Text Books:
 J. P. Tremblay and R. P. Manohar, Discrete Mathematics with Applications to Computer Science, Tata McGrawHill, 1999.
 C. L. Liu, Elements of Discrete Mathematics, 2nd Ed, Tata McGrawHill, 2000.
 R. L. Graham, D. E. Knuth, and O. Patashnik, Concrete Mathematics, 2nd Ed, AddisonWesley,1994.
 N. Deo, Graph Theory with Applications to Engineering and Computer Science, Prentice Hall of India, 1974.
 S. Lipschutz and M. L. Lipson, Schaums Outline of Theory and Problems of Discrete Mathematics, 2ndEd, Tata McGrawHill, 1999
CS227  Digital Systems  2–0–2–6  CS 

Number Systems, Boolean algebra, logic gates, minimization of completely and incompletely specified switching functions, Karnaugh map and QuineMcCluskey method, multiple output minimization, twolevel and multilevel logic circuit synthesis. Clocks, flipflops, latches, counters and shift registers, finite state machine model, synthesis of synchronous sequential circuits, minimization and state assignment, Programmable logic devices: memory design. Data path control path partitionbased design.
Experiments: Combinational logic circuits: Design and implementation of combinational circuits such as ALU and 7segment LED display driver; Sequential Circuits: Design of sequence generators and detectors, counters, design of ASMs such as, traffic light controllers, lift controllers, etc. Digital design project: The students design and implement a final digital project of their choice.
References:
 Z. Kohavi, Switching and Finite Automata Theory, 2nd Ed, Tata McGrawHill, 1995.
 M. M. Mano, Digital Design, 3rd Ed, Pearson Education Asia, 2002.
 S. Brown and Z. Vranesic, Fundamentals of Digital Logic  With Verilog Design, Tata McGrawHill, 2002.
 S. Brown and Z. Vranesic, Fundamentals of Digital Logic  With VHDL Design, Tata McGrawHill, 2002 .
 J. P Uyemura, A First Course in Digital System Design  An Integrated Approach, Vikas Publishing House, 2001.
CS271  Optimization techniques  3–0–0–6  CS 

Linear programming: Introduction and Problem formulation, Concept from Geometry, Geometrical aspects of LPP, Graphical solutions, Linear programming in standard form, Simplex, Big M and TwoPhase Methods, Revised simplex method, Special cases of LPP.
Duality theory: Dual simplex method, Sensitivity analysis of LP problem, Transportation, Assignment and travelling salesman problem.
Integer programming problems: Branch and bound method, Gomory cutting plane method for all integer and for mixed integer LPP.
Theory of games: saddle point, linear programming formulation of matrix games, twoperson zerosum games with and without saddlepoints, pure and mixed strategies, graphical method of solution of a game, solution of a game by simplex method. Computational complexity of the Simplex algorithm, Karmarkar's algorithm for LPP. Acquaintance to softwares like TORA and MATLAB.
Text Books:
 Hamdy A. Taha, Operations Research: An Introduction, Eighth edition, PHI, New Delhi (2007).
 S. Chandra, Jayadeva, Aparna Mehra, Numerical Optimization with Applications, Narosa Publishing House (2009).
 A. Ravindran, D.T. Phillips, J.J. Solberg, Operation Research, John Wiley and Sons, New York (2005).
 M. S. Bazaraa, J. J. Jarvis and H. D. Sherali, Linear Programming and Network Flows, 3rd Edition, Wiley (2004).
Reference Books:
 D. G. Luenberger, Linear and Nonlinear Programming, 2nd Edition, Kluwer, (2003).
 S. A. Zenios (editor), Financial Optimization, Cambridge University Press (2002).
 F. S. Hiller, G. J. Lieberman, Introduction to Operations Research, Eighth edition, McGraw Hill (2006).
CS230  Software Lab/Tools  0–0–33  CS 

Bash shell programming – basic concepts, expressions, decision making selections, repetition, special parameters  positional parameters, shift, argument validation, script examples.
Android Basics: Getting started with Android development, project folder structure, simple programming, running project, generating build/APK of the app from Android Studio
First application: Creating Android Project, Android Virtual Device Creation, set up debugging environment, Workspace set up for development, launching emulator, debugging on mobile devices. Basic UI design: Basics about Views, Layouts, Drawable Resources, input controls, Input Events etc. Understand the app idea and design user interface/wireframes of mobile app
Set up the mobile app development environment.
Fourth Semester
HS2XX  HSS ElectiveII  3006  HSS 

MA2XX  Open Elective I (Prob. Theory and Random Processes)  3006  MA 

Algebra of sets, probability spaces, random variables, cumulative distribution functions, mathematical expectations, conditional probability and expectation, moments and inequalities, special discrete and continuous probability distributions, function of a random variable, random vectors and their distributions, convolutions, joint, marginal and conditional distributions, product moments, independence of random variables, bivariate distributions and properties, order statistics and their distributions, sampling distributions, Central Limit Theorem, strong law of large numbers, sequence of random variables, modes of convergence, distributions of the sample mean and the sample variance for a normal population, chisquare, t and F distributions, method of moments and maximum likelihood estimation, concepts of unbiasedness, criteria for choosing estimators, consistency and efficiency of estimates, confidence intervals, pivotal quantities, confidence intervals for proportions, simple and composite hypothesis, null and alternative hypotheses, types of error, level and size of tests, the most powerful test and Neyman  Pearson Fundamental Lemma, tests for one and twosample problems for normal populations, tests for proportions, likelihood ratio tests, chisqaure test for goodness of fit. discrete and continuous stochastic processes, markov chains, transition probability matrix, state spaces, classification of states, stationary distributions, ergodicity, poisson process, birth and death process. Introduction to reliability analysis: Application of Bayes theorem in real life problem; Reliability analysis of simple syste serial, parallel and combined systems; First order uncertainty and reliability analysis (FORM), First order second mom (FOSM) and Advanced FOSM methods; Applications of risk and reliability analysis in engineering systems.
Text / Reference Books:
 Scheaffer, R. L., Mulekar, M. S. and McClave, J. T., (2011): Probability and statistics for Engineers, Fifth Edition, Broo Cole, Cengage Learning.
 Ang, A. HS., and Tang, W. H., (2006): Probability Concepts in Engineering, Volumes 1. John Wiley and Sons.
 Halder, A and Mahadevan, S., (2000): Probability, Reliability and Statistical Methods in Engineering Design, John Wiley Sons.
 Rao, S.S., (1992): ReliabilityBased Design, McGraw Hill, Inc.
 Harr, M.E., (1987): ReliabilityBased Design in Civil Engineering. McGraw Hill, Inc.
 Ang, A. HS, and Tang, W. H., (1975): Probability Concepts in Engineering Planning and Design, Volumes 2. John Wiley and Sons
 Benjamin, J., and Cornell. A., (1963): Probability, Statistics, and Decision for Civil Engineers. McGraw Hill.
CS2XX  Computer Architecture  3006  CS 

CPU  registers, instruction execution cycle, RTL interpretation of instructions, addressing modes, instruction set. Case study  instruction sets of some common CPUs; Assembly language programming for some processor; Data representation: signed number representation, fixed and floating point representations, character representation. Computer arithmetic  integer addition and subtraction, ripple carry adder, carry lookahead adder, etc. multiplication – shiftandadd, Booth multiplier, carry save multiplier, etc. Division  nonrestoring and restoring techniques, floating point arithmetic; CPU control unit design: hardwired and microprogrammed design approaches, Case study  design of a simple hypothetical CPU; Pipelining: Basic concepts of pipelining, throughput and speedup, pipeline hazards; Memory organization: Memory interleaving, concept of hierarchical memory organization, cache memory, cache size vs block size, mapping functions, replacement algorithms, write policy; Peripheral devices and their characteristics: Inputoutput subsystems, I/O transfers  program controlled, interrupt driven and DMA, privileged and nonprivileged instructions, software interrupts and exceptions. Programs and processes  role of interrupts in process state transitions.
CSXX  Computer Architecture Lab  0033  CS 

Familiarization with assembly language programming; Synthesis/design of simple data paths and controllers, processor design using HDL like verilog/vhdl; Interfacing  DAC, ADC, keyboarddisplay modules, etc. Development kits as well as Microprocessors/PCs may be used for the laboratory, along with design/simulation tools as and when necessary.
CS2XX  Theory of computation  3006  CS 

Regular Languages: Finite AutomataDeterministic and Nondeterministic, regular operations, Regular Expressions, Equivalence of DFA, NFA and Res, Nonregular Languages and pumping lemma
ContextFree Languages: ContextFree Grammars, Chomsky Normal Form, Pushdown Automata, Non ContextFree Languages and pumping lemma, Deterministic ContextFree Languages
Turing Machines: Definition of TM and its variants, Decidability, Reducibility.
Complexity Theory: Time complexity and Space Complexity.
Text Books:
 Introduction to the Theory of Computation, by Michael Sipser.
 Computational Complexity, by Christos H. Papadimitriou, AddisonWesley publishers.
 Computational Complexity: A Modern Approach, by Sanjeev Arora and Boaz Barak.
CS2XX  Database  3006  CS 

Database system architecture: Data Abstraction, Data Independence, Data Definition and Data Manipulation Languages; Data models: Entityrelationship, network, relational and object oriented data models, integrity constraints and data manipulation operations; Relational query languages: Relational algebra, tuple and domain relational calculus, SQL and QBE; Relational database design: Domain and data dependency, Armstrong’s axioms, normal forms, dependency preservation, lossless design; Query processing and optimization: Evaluation of relational algebra expressions, query equivalence, join strategies, query optimization algorithms; Storage strategies: Indices, Btrees, hashing; Transaction processing: Recovery and concurrency control, locking and timestamp based schedulers, multiversion and optimistic Concurrency Control schemes; Recent Trends: XML Data, XML Schema, JSON and “NoSQL Systems, etc.
Books:
 Abraham Silberschatz, Henry Korth, and S. Sudarshan, Database System Concepts, McGrawHill.
 Raghu Ramakrishnan, Database Management Systems, WCB/McGrawHill.
 Bipin Desai, An Introduction to Database Systems, Galgotia.
 J. D. Ullman, Principles of Database Systems, Galgotia.
 R. Elmasri and S. Navathe, Fundamentals of Database Systems, AddisonWesley.
 Serge Abiteboul, Richard Hull and Victor Vianu, Foundations of Databases. AddisonWesley
CS2XX  Database Lab  0033  CS 

Database schema design, database creation, SQL programming and report generation using a commercial RDBMS like ORACLE/SYBASE/DB2/SQLServer/INFORMIX. Students are to be exposed to front end development tools, ODBC and CORBA calls from application Programs, internet based access to databases and database administration.
Fifth Semester
XX3nn  Open Elective  3006   

CS303  Formal Language & Automata Theory  3108  CS 

Introduction: Alphabet, languages and grammars, productions and derivation, Chomsky hierarchy of lan guages. Regular languages and finite automata: Regular expressions and languages, deterministic finite automata (DFA) and equivalence with regular expressions, nondeterministic finite automata (NFA) and equivalence with DFA, regular grammars and equivalence with finite automata, properties of regular languages, pumping lemma for regular languages, minimization of finite automata. Contextfree languages and pushdown automata: Contextfree grammars (CFG) and languages (CFL), Chomsky and Greibach normal forms, nondeterministic pushdown automata (PDA) and equivalence with CFG, parse trees, ambiguity in CFG, pumping lemma for contextfree languages, deterministic pushdown automata, closure properties of CFLs. Contextsensitive languages: Contextsensitive grammars (CSG) and languages, linear bounded automata and equivalence with CSG. Turing machines: The basic model for Turing machines (TM), Turing recognizable (recursively enumerable) and Turingdecidable (recursive) languages and their closure properties, variants of Turing machines, nondeterministic TMs and equivalence with deterministic TMs, unrestricted grammars and equivalence with Turing machines, TMs as enumera tors. Undecidability: ChurchTuring thesis, universal Turing machine, the universal and diagonalization languages, reduction between languages and Rice’s theorem, undecidable problems about languages.
References:
 J. E. Hopcroft, R. Motwani and J. D. Ullman, Introduction to Automata Theory, Languages and Computation, Pearson Education India (3rd edition).
 K. L. P. Mishra, N. Chandrasekaran, Theory of Computer Science: Automata, Languages and Computation, PHI Learning Pvt. Ltd. (3rd edition).
 D. I. A. Cohen, Introduction to Computer Theory, John Wiley & Sons, 1997.
 J. C. Martin, Introduction to Languages and the Theory of Computation, Tata McGrawHill (3rd Ed.).
 H. R. Lewis and C. H. Papadimitriou, Elements of the Theory of Computation, Prentice
CS321  Computer Architecture  3006  CS 

Basic functional blocks of a computer: CPU, memory, inputoutput subsystems, control unit. Instruction set architecture of a CPU  registers, instruction execution cycle, RTL interpretation of instructions, addressing modes, instruction set. Case study  instruction sets of some common CPUs; Assembly language programming for some processor; Data representation: signed number representation, fixed and floating point representations, character representation. Computer arithmetic  integer addition and subtraction, ripple carry adder, carry lookahead adder, etc. multiplication – shiftandadd, Booth multiplier, carry save multiplier, etc. Division  nonrestoring and restoring techniques, floating point arithmetic; CPU control unit design: hardwired and micro programmed design approaches, Case study  design of a simple hypothetical CPU; Pipelining: Basic concepts of pipelining, throughput and speedup, pipeline hazards; Memory organization: Memory interleaving, concept of hierarchical memory organization, cache memory, cache size vs block size, mapping functions, replacement algorithms, write policy; Peripheral devices and their characteristics: Inputoutput subsystems, I/O transfers  program controlled, interrupt driven and DMA, privileged and nonprivileged instructions, software interrupts and exceptions. Programs and processes  role of interrupts in process state transitions.
References:
 David A. Patterson, John L. Hennessy, Computer Organization and Design, Fourth Edition: The Hardware/Software Interface, Morgan Kaufmann; 4 edition, 2011.
 A. Tenenbaum, Structured Computer Organization, 4th Ed, PrenticeHall of India, 1999.
 W. Stallings, Computer Organization and Architecture: Designing for Performance, 6th Ed, Prentice Hall, 2005.
 J. Hennessy and D. Patterson, Computer Architecture A Quantitative Approach, 3rd Ed, Morgan Kaufmann, 2002.
CS322  Computer Architecture Lab  0033  CS 

Familiarization with assembly language programming; Synthesis/design of simple data paths and controllers, processor design using HDL like verilog/vhdl; Interfacing  DAC, ADC, keyboarddisplay modules, etc. Development kits as well as Microprocessors/PCs may be used for the laboratory, along with design/simulation tools as and when necessary.
CS354  Database  3006  CS 

Database system architecture: Data Abstraction, Data Independence, Data Definition and Data Manipulation Languages; Data models: Entityrelationship, network, relational and object oriented data models, integrity constraints and data manipulation operations; Relational query languages: Relational algebra, tuple and domain relational calculus, SQL and QBE; Relational database design: Domain and data dependency, Armstrongs axioms, normal forms, dependency preservation, lossless design; Query processing and optimization: Evaluation of relational algebra expressions, query equivalence, join strategies, query optimization algorithms; Storage strategies: Indices, Btrees, hashing; Transaction processing: Recovery and concurrency control, locking and timestamp based schedulers, multiversion and optimistic Concurrency Control schemes; Recent Trends: XML Data, XML Schema, JSON and “NoSQL Systems, etc,.
References:
 Abraham Silberschatz, Henry Korth, and S. Sudarshan, Database System Concepts, McGrawHill.
 Raghu Ramakrishnan, Database Management Systems, WCB/McGrawHill.
 Bipin Desai, An Introduction to Database Systems, Galgotia.
 J. D. Ullman, Principles of Database Systems, Galgotia.
 R. Elmasri and S. Navathe, Fundamentals of Database Systems, AddisonWesley.
 Serge Abiteboul, Richard Hull and Victor Vianu, Foundations of Databases. Addison Wesley
CS355  Database Laboratory  0033  CS 

Database schema design, database creation, SQL programming and report generation using a commercial RDBMS like ORACLE/SYBASE/DB2/SQLServer/INFORMIX. Students are to be exposed to front end development tools, ODBC and CORBA calls from application Programs, internet based access to databases and database administration.
CS322  Computer Architecture Lab  0033  CS 

Sixth Semester
HS3nn  HSS Elective  3006  HSS 

CS341  Operating System  3006  CS 

Process Management: process; thread; scheduling. Concurrency: mutual exclusion; synchronization; semaphores; monitors; Deadlocks: characterization; prevention; avoidance; detection. Memory Management: allocation; hardware sup port; paging; segmentation. Virtual Memory: demand paging; replacement; allocation; thrashing. File Systems and Implementation. Secondary Storage: disk structure; disk scheduling; disk management. (Linux will be used as a running example, while examples will drawn also from Windows NT/7/8.); Advanced Topics: Distributed Systems. Security. RealTime Systems.
References:
 Silberschatz, P. B. Galvin and G. Gagne, Operating System Concepts, 9th Ed, John Wiley & Sons, 2010.
 A. S. Tenenbaum, Modern Operating Systems, 2nd Ed, Prentice Hall of India, 2001.
 H. M. Deitel, P. J. Deitel and D. R. Choffness, Operating Systems, 3rd Ed, Prentice Hall, 2004.
 W. Stallings, Operating Systems: Internal and Design Principles, 5th Ed, Prentice Hall, 2005.
 M. J. Bach, The Design of the UNIX Operating System, Prentice Hall of India, 1994.
 M. K. McKusick et al, The Design and Implementation of the 4.4 BSD Operating System, Addison Wesley, 1996.
CS342  Operating System Laboratory  0135  CS 

Programming assignments to build different parts of an OS kernel.
CS358  Computer Network  3006  CS 

Evolution of computer networks; Physical Layer: Theoretical basis for data communication, transmission media and impairments, switching systems Medium Access Control Sublayer: Channel allocation Problem, multiple access protocols, Ethernet Data link layer: Framing, HDLC, PPP, sliding window protocols, error detection and correction Network Layer: Internet addressing, IP, ARP, ICMP, CIDR, routing algorithms (RIP, OSPF, BGP); Transport Layer: UDP, TCP, flow control, congestion control; Introduction to quality of service; Application Layer: DNS, Web, email, authentication, encryption.
References:
 Peterson & Davie, Computer Networks, A Systems Approach: 5th Edition
 William Stallings Data and Computer Communication, Prentice Hall of India.
 Behrouz A. Forouzan, Data Communication and Networking, McGrawHill.
 Andrew S. Tanenbaum, Computer Networks, Prentice Hall.
 Douglas Comer, Internetworking with TCP/IP, Volume 1, Prentice Hall of India.
 W. Richard Stevens, TCP/IP Illustrated, Volume 1, AddisonWesley.
CS359  Computer Network Lab  0033  CS 

Simulation experiments for protocol performance, configuring, testing and measuring network devices and parameters/policies; network management experiments; Exercises in network programming.
Seventh Semester
CS491  ProjectI  0066  CS 

The project can span the course ProjectII. Hence it is expected that the problem specification and the milestones to be achieved in solving the problem are clearly specified.
Eighth Semester
CS492  ProjectII  001212  CS 

The students who work on a project are expected to work towards the goals and milestones set in course ProjectI. At the end there would be demonstration of the solution and possible future work on the same problem. A dissertation outlining the entire problem, including a literature survey and the various results obtained along with their solutions is expected to be produced.
M.Tech Courses
M. Tech. AI
MTech in Artificial Intelligence
SI. No.  Course Number  Course Title  L  T  P  C 
1  CS561  Artificial Intelligence  3  0  0  6 
2  MA501  Probability Statistics andStochastic Processes  3  0  0  6 
3  CS564  Foundations of Machine Learning  3  0  0  6 
4  CSXXX  ElectiveI  3  0  0  6 
5  EE/MEXXX  ElectiveII  3  0  0  6 
6  CSXXX  AI LabI  0  0  3  3 
7  HS5XX  HSS Elective  2  0  0  4 
TOTAL  17  0  3  37 
2^{nd} SEMESTER
SI. No.  Course Number  Course Title  L  T  P  C 
1  MAXXX  Linear Algebra and Optimization techniques  3  0  0  6 
2  CSXXX  Big Data Analytics  3  0  0  6 
3  CS551  Intro to Deep Learning  3  0  0  6 
4  CS563/EE XXX  Natural Language Processing/Computer Vision/Image Processing  3  0  0  6 
5  CS/ME/EEXXX  ElectiveIII  3  0  0  6 
6  CSXXX  AI LabII  0  0  4  4 
7  CSXXX  Comprehensive Viva  0  0  4  4 
TOTAL  15  0  8  38 
3^{rd} SEMESTER
SI. No.  Course Number  Course Title  L  T  P  C 
1  CS695  Project ThesisI  0  0  20  20 
2.  CS592  Research Seminar  0  0  4  4 
TOTAL  24 
4^{th} SEMESTER
SI. No.  Course Number  Course Title  L  T  P  C 
1  CS696  Project ThesisII  0  0  24  24 
TOTAL  24 
Total Credit  37  34  24  24  122 
Core Courses:
CS541  Foundations of Computer Systems  3006  Prerequisites: Nil 

Review of concepts of computer architecture: Study of an existing CPU: architecture, instruction set and the addressing modes, assembly language programming. Control unit Design: instruction interpretation, hardwired and microprogrammed methods of design. Pipelining and parallel processing, RISC and CISC paradigms, I/O Transfer techniques: programmed, interruptdriven and DMA; Memory organization: hierarchical memory systems, cache memories, cache coherence, virtual memory.
Review of concepts of operating systems: Processes, threads, Unix forkexec model, Unix signals, Interprocess communication, scheduling, memory management.
Review of concepts of computer networks: link layer protocols, local area networks (Ethernet and variants), interconnecting networks with IP, routing, transport layer protocols. Advanced concepts of distributed networked systems: Virtualization, distributed file systems, mass storage systems, recovery and fault tolerance, content networking including multimedia delivery.
Texts:
 A. Silberschatz, P. B. Galvin and G. Gagne, Operating System Concepts, 7th Ed, John Wiley and Sons, 2004.
 J. Kurose and K. W. Ross, Computer Networking: A Top down approach, 3rd Ed, Pearson India, 2004. M. Singhal and N. Shivratri, Advanced Concepts in Operating Systems, McGraw Hill, 1994. A. S. Tanenbaum and Van Steen, Distributed Systems: Principles and Paradigms, Prentice Hall India, 2007.
CS511:  Foundations of Theoretical Computer Science  3006  Prerequisites: Nil 

Discrete Structures Sets, Relations and Functions; Proof Techniques, Algebraic Structures, Morphisms, Posets, Lattices and Boolean Algebras.
Logic Propositional calculus and Predicate Calculus, Satisfiabiliy and validity, Notions of soundness and completeness. Automata and Languages  Finite automata and regular expressions, pushdown automata and contextfree grammars, pumping lemmas and closure properties of regular and contextfree languages, noncontextfree languages.
Computability theory ChurchTuring thesis, Hilbert's problem, decidability, halting problem, reducibility; Complexity theory: time and space complexity, Classes P, NP, NPcomplete, PSPACE, and PSPACEcomplete
Texts:
 M. Sipser, Introduction to the Theory of Computation, Thomson, 2004. 2. H. R. Lewis, C. H. Papadimitriou, Elements of the Theory of Computation, PHI, 1981.
References:
 J. E. Hop croft, J. D. Ullman, Introduction to Automata Theory, Languages and Computation,Narosa,1979.
 S. Arora, B. Barak, Computational Complexity: A Modern Approach, Cambridge UniversityPress,2009.
 C. H. Papadimitriou, Computational Complexity, AddisonWesley Publishing Company, 1994.
 D.C.Kozen, Theory of Computation, Springer, 2006.
 D. S. Garey, G. Johnson, Computers and Intractability: A Guide to the Theory of NPCompleteness, Freeman, New York, 1979.
CS 512:  Data Structure and Algorithms  3006  Prerequisites: Nil 

Problem Solving using Computers  Abstraction  Abstract data types; Data Representation; Elementary data types; Basic concepts of data Structures; Mathematical preliminaries  bigOh notation; efficiency of algorithms; notion of time and space complexity; performance measures for data structures.
ADT array  Computations on arrays sorting and searching algorithms. ADT Stack, Queue, list  array, linked list, cursor based implementations of linear structures.
ADT Tree  tree representation, traversal of trees;
ADT Binary tree  binary trees, threaded binary trees, application of binary trees Huffman coding; application of threaded binary trees  differentiation;
Search Tree  Binary search tree; balanced binary search trees  AVL tree; Applications of Search Trees  TRIE; 23 tree, 234 tree; concept of BTree.
ADT Dictionary  array based and tree based implementations; hashing  definition and application  LZW encoding. ADT Priority Queue  Heaps; heapbased implementations; applications of heaps  sorting; Graphs  shortest path, minimum spanning tree, DFS, BFS  an application of DFS and BFS.
Algorithm Design Paradigms  greedy, divide and conquer, dynamic Programming, backtracking.
References:
 Mark Allen Weiss, "Data Structures and Algorithms in C++", Addison Wesley, 2003.
 Adam Drozdek, "Data Structures and Algorithms in C++", Brooks and Cole, 2001.
 Aho, Hopcroft and Ullmann, "Data structures and Algorithm", Addison Welsey, 1984.
MA501:  Probability, Statistics and Stochastic Processes  3006  Prerequisites: Nil 

Probability : algebra of sets, monotone class, sigma fields, Borel sigma fields, set function, product spaces, measurable transformations, probability measure, notions of probability space and some consequences, BorelCantelli Lemma Discrete, continuous and mixed type probability spaces, cumulative distribution functions, probability mass (density) functions, mathematical expectations, general concepts of conditional probability and expectation, conditional expectation given a sigma field, properties of conditional expectation, moments, moment and probability generating functions, moment inequalities: Markov, ChebyshevBienayme, Lyapunov.
Special Probability Distributions : Discrete and continuous uniform, binomial, beta, Cauchy, Negative Binomial, Hypergeometric, Gamma, Normal, Lognormal, Weibull, Pareto distributions, generalized distributions, Approximation properties of discrete distributions, BetaBinomial and PoissonGamma relationship. Function of a random variable, random vectors and their distributions, convolutions, Joint, marginal and conditional distributions, product moments, correlation, independence of random variables, bivariate distributions and properties, order statistics and their distributions, further properties.
Sampling Distributions: The Central Limit Theorem, Demoivre theorem, uniform convergence in CLT, characteristics functions, continuity theorems, strong law of large numbers, Sequence of random variables, modes of convergence and some results, Slutsky theorem, distributions of the sample mean and the sample variance for a normal population, Chi  Square, t and F distributions and their distributional properties Point and Interval Estimation : The method of moments and the method of maximum likelihood estimation, large sample properties, concepts of unbiasedness, criteria for choosing estimators, consistency and efficiency of estimates, confidence intervals for the parameters of common distributions, pivotal quantities, confidence intervals for proportions (one and two samples problems) .
Testing of Hypotheses : simple and composite hypothesis, Null and alternative hypotheses, critical and acceptance regions, two types of error, level and size of test, error probabilities of a test, the most powerful test and Neyman  Pearson Fundamental Lemma, tests for one sample and two sample problems for normal populations, tests for one sample and two sample proportions, Likelihood ratio tests, Chisqaure test for goodness of fit.
Stochastic Processes: illustrations of stochastic processes, stochastic matrices, Markov chains: finite and countably infinite state spaces, Classification of states, strong markov property, stationary distributions, time reversible markov chains, Branching processes, ergodic and nonergodic markov chains, recurrent and transient random walk, General Markov processes in discrete and continuous state spaces. Poisson process: homogeneous and nonhomogeneous,
pure birth process, birth and death process, regenerative processes, notions of queuing models
References:
 Rohatgi, V.K., and Saleh, A.K.Md. Ehsanes (2009). An introduction to probability and statistics. Second Edition, Wiley India.
 Introduction to the Theory of Statistics; Alexander M. Mood, Franklin A. Graybill, Duane C. Boes, Tata McGraw Hill.
 Milton, J.S. and Arnold, J.C. (2009) Introduction to Probability and Statistics, Fourth Edition, Tata McgrawHill.
 Ross, S.M.(2008) Introduction to Probability Models, Ninth edition, Academis Press.
 Statistical Inference (2007), G. Casella and R.L. Berger, Duxbury Advanced Series .
 Ash, Robert B. (2009), Probability & Measure Theory, Academic Press.
Elective Courses (Elective I –III)
CS561:  Artificial Intelligence  3006  Prerequisites: Nil 

Introduction, Problem Solving: Uninformed search, Informed search, local Search, Online search; Knowledge and Reasoning: Building a Knowledge Base, Semantic Nets, Frames, First order logic, Inference in First Order Logic; Probabilistic Reasoning Systems: Bayes’ Nets; Learning: Learning from examples and analogy, Naive Bayes, Computational Learning Theory, Explanation Based Learning, Neural Networks; Evolutionary Optimization: Genetic algorithms, Multi objective optimization, Differential Evolution, Particle Swarm Optimization; Introduction to NLP;
Introduction to Fuzzy sets.
References:
 S. Russel and P. Norvig. Artificial Intelligence: A Modern Approach (Second edition), Pearson
 E. Charniak, Introduction to Artificial Intelligence, Addison Wesley, 1985.
 P. H. Winston, Artificial Intelligence, Addison Wesley, 1993.
 E. Rich and K. Knight, Artificial Intelligence, Addison Wesley, 1990.
 R.Honavar and E. Uhr, Artificial Intelligence and Neural Networks, Academic Press, 1992.
 F. Hayes Roth, Building Expert Systems, Addison Wesley, 1983.
 P. R. Cohen, The Handbook of Artificial Intelligence, Vol.1,2 and 3, Kaufman Inc.,1982.
 B. K. P. Horn, Robot Vision, MIT Press, 1985. J. Carbonell, Machine Learning paradigms and Methods, MIT Press, 1990.
Journals: Artificial Intelligence, AI Magazine, IEEE Expert, Machine Learning, Computer Vision Image Processing and Graphics, IEEE Transactions on Neural Networks.
CS542:  Software Testing  3006  Prerequisites: Nil 

Testing Background, The Realities of Software Testing, Verification and Validation, Testing Fundamentals, Examining the Specification, Examining the Code, Configuration Testing, Compatibility Testing, Usability Testing, Special Testing Techniques; Test Management, Test Automation and Testing Tools; Recent Trends in Software Testing;
Books:
 Software Testing by Ron Patton, Sams Publishing
 Lessons Learned in Software Testing by Kaner, Bach and Pettichord
CS543:  Distributed Systems  3006  Prerequisites:Nil 

Basic concepts. Models of computation: shared memory and message passing systems, synchronous and asynchronous systems. Logical time and event ordering. Global state and snapshot algorithms, mutual exclusion, clock synchronization, leader election, deadlock detection, termination detection, spanning tree construction. Programming models: remote procedure calls, distributed shared memory. Fault tolerance and recovery: basic concepts, fault models, agreement problems and its applications, commit protocols, voting protocols, checkpointing and recovery, reliable communication. Security and Authentication: basic concepts, Kerberos. Resource sharing and load balancing. Special topics: distributed objects, distributed databases, directory services, web services.
References:
 Mukesh Singhal and Niranjan Shivaratri, Advanced Concepts in Operating Systems, McGrawHill.
 Nancy Lynch, Distributed Algorithms, Morgan Kaufmann.
 Andrew S. Tanenbaum, Distributed Operating Systems, ACM Press.
 Jie Wu, Distributed Systems, CRC Press.
 Hagit Attiya, Jennifer Welch, Distributed Computing: Fundamentals, Simulations and Advanced Topics, McGrawHill.
 Sape Mullender (ed.), Distributed Systems, AddisonWesley.
MA511:  Large Scale Scientific Computation  3006  Prerequisites:Nil 

Introduction to sparse matrices, Storage Schemes, Permutations and Reorderings, , Sparse Direct Solution Methods. Iterative methos and Preconditioning Convergence Krylov Subspaces, Arnoldi’s Method, GMRES, Symmetric Lanczos Algorithm, conjugate Gradient Algorithm, Convergence Analysis, Block Krylov Methods, Preconditioned Conjugate Gradient, Preconditioned GMRES, Jacobi, SOR, and SSOR Preconditioners, ILU Factorization Preconditioners, Block Preconditioners, Types of Partitionings, Techniques, Direct Solution and the Schur Complement, Schur Complement Approaches, Full Matrix Methods, Graph Partitioning: Geometric Approach, Spectral Techniques. Newton’s method and some of its variations, Newton method in several dimension, continuation methods, conjugate direction method and DavidonFletcherPowell Algorithms, Introduction to Non linear Multigrid with applications. HPC kernels (BLAS, multicore and GPU computing)
Texts / References:
 O. Axelsson, Iterative Solution Methods Cambridge Univ. Press, 1994.
 W. Hackbusch, Multigrid Methods and Applications. SpringerVerlag, 1985.
 J.M. Ortega and W.C. Rheinboldt, Iterative Solution of Nonlinear Equations in Several Variables. Academic Press, NY, 1970.
 C.W. Ueberrhuber, Numerical Computation : Methods, Software and Analysis. SpringerVerlag, Berlin, 1997.
 P. Wesseling, An Introduction to Multigrid Methods. John Wiley & Sons, 1992.
 Yousef Saad, Iterative Methods for Sparse Linear Systems, SIAM 2003.
CS528:  CAD for VLSI  3006  Prerequisites:Nil 

Introduction: VLSI design flow, challenges.
Verilog/VHDL: introduction and use in synthesis, modeling combinational and sequential logic, writing test benches. Logic synthesis: twolevel and multilevel gatelevel optimization tools, state assignment of finite state machines. Basic concepts of highlevel synthesis: partitioning, scheduling, allocation and binding. Technology mapping. Testability issues: fault modeling and simulation, test generation, design for testability, builtin selftest. Testing SoC's. Basic concepts of verification. Physical design automation. Review of MOS/CMOS fabrication technology. VLSI design styles: fullcustom, standardcell, gatearray and FPGA.
Physical design automation algorithms: floorplanning, placement, routing, compaction, design rule check, power and delay estimation, clock and power routing, Special considerations for analog and mixedsignal designs.
References::
 D. D. Gajski, N. D. Dutt, A.C.H. Wu and S.Y.L. Lin, HighLevel Synthesis: Introduction to Chip and System Design”Springer, 1st edition, 1992.
 Giovanni De Michelli, “Synthesis and Optimization of Digital Circuits” McGrawHill Higher Education, 1994
 N. A. Sherwani, “Algorithms for VLSI Physical Design Automation”, Bsp Books Pvt. Ltd., 3rd edition, 2005.
CS 544:  Introduction to Network Science  3006  Prerequisites: Probability & Statistics 

Introduction and background knowledge of complex networks; Network analysis metrics like paths, components, degree distribution, clustering, degree correlations, centrality etc., social network analysis methods; Introduction to network analysis tools like iGraph and Pajek; Properties of networks like scalefree, small world; Network evolution models like random networks, preferential attachment models and its variants, Watts & Strogatz model; Community detection methods and real world application of community detection; Dynamics on networks like percolation,
spreading, synchronization and real world applications.
Texts:
 M.E.J. Newman, Networks  An introduction , Oxford Univ Press, 2010.
References:
 R. Cohen and S. Havlin, Complex Networks  Structure, Robustness and Function , Cambridge Univ Press, 2010.
 Barrat, M. Barthelemy and A. Vespignani, Dynamical Processes on Complex Networks, Cambridge Univ Press, 2008.
 D. Easley and J. Kleinberg, Networks, Crowds and Markets , Cambridge Univ Press, 2010.
Elective Courses (Elective IV –VI)
CS 548:  Wireless Networks  3006  Prerequisites:Nil 

Wireless technologies: Antennas and radio propagation. Signal encoding and modulation techniques. Spread spectrum. Coding and error control.
Wireless Networking: Cellular wireless networks and systems principles. Mobile IP and Wireless Access Protocol. Multiple access techniques.
Wireless LANs: Wireless LAN technology. Wireless standard (IEEE 802.11 etc.). Bluetooth. Adhoc Networks. Architectures and routing protocols for hybrid wireless networks, Issues and challenges in wireless sensor networks:
Texts:
 W. Stallings, "Wireless Communications and Networks", Pearson Education, 2nd Ed.
References:
 T S Rappaport, "Wireless Communications: Principles & Practice", Second Edition, Pearson Education, 2002.
 J Schiller, "Mobile Communications", Addison Wesley, 2000.
 V K Garg, "IS95 CDMA and CDMA2000", Prentice Hall PTR, 2000.
 Murthy, "Adhoc Wireless Networks: Architectures and Protocols", Pearson, 2004.
 Research papers.
CS 549:  Computer And Network Security  3006  Prerequisites: Nil 

Overview: vulnerabilities, risk assessment, incidents.
Cryptography: Classical Cryptography, Symmetric Cryptography, Public Key (Asymmetric cryptography), Modern Cryptography(RSA, ECC), Hash Functions, Digital Signature.
Authentication and Key Management : Entity authentication, Key exchange, Key management, Kerberos Networking. Security: Security at application layer (PGP, S/MIME), Security at Transport Layer (SSL and TLS), Security at Network Layer (IPSEC)
System Security: Unix Security, Vulnerabilities and Counter Measures (Viruses, worms, Trojan horses, backdoors, buffer overflows, RPC), Exploits (Buffer overflow, Port Scanning etc). Firewalls, VPN etc, Secure (commerce) Transaction over a network.
Current network security Issues: Texts :
 W. Stallings, Cryptography and Network Security: Principles and Practice, 5th Ed,Prentice Hall
References:
 B. Schneier, Applied Cryptography, 2nd Ed, John Wiley & Sons, Inc., 1996.
 A. Menezes, P. van Oorshot and S. Vanstone, Handbook of Applied Cryptogrphy, CRC Press, 1997.
 B.A. Foruzan and D. Mukhopadhyay Cryptography and Network Security, second edn.Tata Mchrawhill
 Related publications in Journals/Conferences.
CS 508:  Formal Methods for Analysis and Verification  3006  Prerequisites:Nil 

Introduction to formal methods; Analysis Vs. Verification; Correctness and soundness theorem; Formal semantics: operational, denotational, axiomatic; Specification Languages; Various formal methods and their application to verification and analysis: Model Checking, Abstract Interpretation, Shadow semantics, Hoare logic, Theorem Proving.
References:
 Flemming Nielson, Hanne R. Nielson, Chris Hankin. Principles of Program Analysis, Springer, 1999.
 Edmund M. Clarke, Orna Grumberg, Doron A. Peled. Model Checking, The MIT Press, 1999.
 Glynn Winskel. The formal semantics of programming languages: an introduction, The MIT Press, 1993.
 Annabelle McIver, Carroll Morgan. Abstraction, Refinement and Proof for Probabilistic Systems, Springer, 2005 edition.
 Recent Research Papers relevant to the course.
CS502:  Pattern Recognition  3006  Prerequisites:Nil 

Syllabus : Introduction to Pattern Recognition: Learning paradigms, Supervised and unsupervised learning; Bayesian decision theory: Minimum error rate classifier.
Parameter estimation: Maximum likelihood and Bayesian Estimation; Hidden Markov models; Nonparametric techniques: Nearest neighbor rules, Parzen windows; Decision trees: Axisparallel, Oblique, Impurity measures; Feature selection: Forward, backward search; Component analysis and discriminate functions: Principal component analysis, Fisher linear discriminate, Perceptron, Support vector machines; Generalization ability of learning methods: Bias and variance, Regularization; Bootstrapping, Boosting, Bagging; Unsupervised learning and clustering: kMeans methods.
Texts:
 R. O. Duda, P. E. Hart and D. G. Stork, Pattern classification, John Wiley & Sons, 2002.
 S. Theodoridis and K. Koutroumbas , Pattern Recognition, 4th Edition, Academic Press, 2008.
References:
 C. M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995.
 V. N. Vapnik, The Nature of Statistical Learning Theory, Springer, 2000.
 N. Cristianini and J. ShaweTaylor, An Introduction to Support Vector Machines, Cambridge University Press, 2000.
 Selected Research Papers.
CS743:  Advanced Topics in Database Systems  3006  Prerequisites:Nil 

Database Computation Models: Page and Object Models
Correctness in databases: Serializability  review of the basic theory, multiversion serializability, semantic serializability, relative atomicity, relative serializability, etc.
Concurrency control methods: Two phase locking, timestamp and optimistic methods, tree locking. Correctness in Software Transactional Memory (STM): Opacity, Virtual Worlds Consistency, Abort Shielded Consistency.
Page model crash and recovery: Expanded Schedules, PageModel Correctness Criteria, Sufficient Syntactic Conditions, Further Relationships Among Criteria, Extending PageModel CC Algorithms, Redo, undo algorithms. Object model crash and recovery: Unified concurrency control and recovery, compensating transactions, Algorithm for 2Layered Systems, Algorithm for General Executions.
Special Database Systems: Object based, Semistructured, Active, Deductive, Temporal, Spatial, Multimedia. Database Security: Access Control Models MAC, DAC, RBAC.
Datawarehousing: Multidimensional data model, OLAP, Data Warehouse Architecture This course will draw materials mainly from the books given below. However, there are many research papers that will help understand the course contents. These will be provided on time to time basis.
Suggested Text Books:
 G. Weikum and G. Vossen – “Transactional Information Systems: Theory, Algorithms and the Practice of Concurrency Control and Recovery”, (Morgan Kaufmann), 2002
 A. Silberschatz, H. F. Korth and S. Sudarsan – “Database System Concepts”, (McGraw Hill), 2011
 R. Elamsri, S. B. Navathe – “Fundamentals of Database Systems”, (Pearson Education), 2011
 R.Kimball – Data Warehouse Toolkit (J.Wiley & Sons), 2nd Edition 2002
Reference Books:
 P. A. Bernstein, V. Hadzilacos and N. Goodman  Concurrency Control and Recovery in Database Systems, (Addison Wesley), 1987
 P. A. Bernstein and E. Newcomer – Principles of Transaction Processing, (Morgan Kaufmann), 1997
 A. Elmagarmid (Ed.) Database Transaction Models for Advanced Applications, (Morgan Kaufmann), 1992.
 J. Pieprzyk, T. Hardjono and J. Seberry – Fundamentals of Computer Security. (Springer), 2009 .
Lab Courses
CS558:  Computer Systems Lab – 1  3006  Prerequisites:Nil 

Basics of OS programming: process creation and synchronization, shared memory and semaphore, shell programming.
Socket programming, database creation and update, building large client server applications. Basics of compiler writing using lex and yacc .
CS513:  Computer Systems Lab – 2  3006  Prerequisites:Nil 

Objectoriented programming concepts and implementation of abstract data types. Implementation of graph algorithms. Linear programming with applications.
Ph.D. Courses
Distributed Systems and Alogorithms
CS701  Distributed Systems and Alogorithms  3006 

Basic concepts. Models of computation: shared memory and message passing systems, synchronous and asynchronous systems. Logical time and event ordering. Global state and snapshot algorithms, mutual exclusion, clock synchronization, leader election, deadlock detection, termination detection, spanning tree construction. Programming models: remote procedure calls, distributed shared memory. Fault tolerance and recovery: basic concepts, fault models, agreement problems and its applications, commit protocols, voting protocols, checkpointing and recovery, reliable communication. Security and Authentication: basic concepts, Kerberos. Resource sharing and load balancing. Special topics: distributed objects, distributed databases, directory services, web services.
Texts:
 B. W. Kernighan and D. Ritchie, The C Programming Language, 2nd Ed, Prentice Hall of India, 1988.
 N. Lynch, Distributed Algorithms, Elsevier India Private Limited, (2009)
 Hagit Attiya, Jennifer Welch, Distributed Computing: Fundamentals, Simulations and Advanced Topics, Wiley, (2006)
References:
 S.Ghosh, Distributed Systems: An Algorithmic Approach, Chapman & Hall, (2006)
 A. Kshemkalyani, M. Singhal, Distributed Computing: Principles, Algorithms, and Systems, Cambridge University Press, (2008)
 Gerard Tel, Introduction to Distributed Algorithms, 2nd edition, Cambridge University Press, (2004)
 Technical papers from major distributed systems journals and conferences
Topics in Computer Networks
CS741  Topics in Computer Networks  3006 

Overview of computer networks, the Internet and OSI model Responsibilities of the Data Link Layer, Network Layer and Transport Layer; Local Area Networks – Ethernet, Token Ring etc. Scheduling algorithms and MAC layer protocols (Link Layer) Routing protocols  BGP, RIP, OSPF, AODV etc. (Network Layer). Congestion control Algorithms (Transport Layer). Peertopeer and clientserver programming using sockets in TCP and UDP. Quality of Service (QoS) Provisioning Network Security
Texts:
 A. S. Tanenbaum, Computer Networks, 4th Ed, Prentice Hall, (2003)
References:
 B. A. Forouzan, Data Communications and Networking, 3rd Ed, McGraw Hill, (2004)
 W. Stallings, Data and Computer Communications, 7th Ed, Prentice Hall of India, (2004)
 J. F.Kurose and K. W. Ross,Computer networking: A Topdown Approach Featuring the Internet, 3rd Ed, AddisonWesley, (2005)
 W. Stevens and G. Wright, TCP/IP Illustrated, Volumes 13, (2002)
 Technical papers from major networking journals and conferences
Cryptography and Network Security
CS742  Cryptography and Network Security  3006 

Symmetric key encryption algorithm, Key distribution, Stream Ciphers, Pseudo Random Numbers, Public Key Cryptography, Hashes and Message Digests, Digital Signatures, Certificates, User Authentication. System authentication, IPSec, Virtual Private Networks Secure Socket layer, transport layer security.
Texts:
 W. Stalling: Cryptography and Network security Principles and Practices, 4th Edition PHI, (2006)
 D. R. Stinson: Cryptography theory and practices, 2nd Edition, CRC Press,(2006)
References:
 Technical papers from major reputed journals and conferences and internet resources
Advance in Alogorithms
CS702  Advance in Alogorithms  3006 

Algorithmic paradigms: Dynamic Programming, Greedy, Branchandbound; Asymptotic complexity, Amortized analysis; Graph Algorithms: Shortest paths, Flow networks; NPcompleteness; Approximation algorithms; Randomized algorithms; Linear programming; Special topics: Geometric algorithms (range searching, convex hulls, segment intersections, closest pairs), Numerical algorithms (integer, matrix and polynomial multiplication, FFT, extended Euclid's algorithm, modular exponentiation, primality testing, cryptographic computations), Internet algorithms (text pattern matching, tries, information retrieval, data compression, Web caching).
References:
 T. H. Cormen, C. L. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2nd edition, Prenticehall Of India Pvt.. Ltd, (2007)
 J. Kleinberg and E. Tardos, Algorithm Design, AddisonWesley, (2008)
 Rajeev Motwani and Prabhakar Raghavan, Randomized Algorithms, Cambridge University Press, (1995)
 Vijay Vazirani, Approximation Algorithms, Springer, (2004)
 Soumen Chakrabarti, Mining the Web: Discovering Knowledge from Hypertext Data, Elsevier India Private Limited, (2005)
References:
 Technical papers from major reputed journals in the area of algorithms design.