Computer Science & Engineering (Data Science)
| Course Title | Code | L | T | P | Credits |
|---|---|---|---|---|---|
| Machine Learning | 153501 | 3 | 0 | 0 | 3 |
| Database Management System | 153502 | 3 | 0 | 0 | 3 |
| Computer Networks | 153503 | 3 | 0 | 0 | 3 |
| Python Programming | 153504 | 3 | 0 | 0 | 3 |
| Seminar | 153505 | 1 | 0 | 0 | 1 |
| Program Electives Courses-I | 1535XX | 3 | 0 | 0 | 3 |
| Professional Practice, Law & Ethics | - | 3 | 0 | 0 | 0 |
| Summer Entrepreneurship-II | 153511P | - | - | - | 6 |
| NPTEL Course | 153512P | 0 | 0 | 4 | 2 |
| Database Management System Lab | 153502P | 0 | 0 | 4 | 2 |
| Computer Networks Lab | 153503P | 0 | 0 | 2 | 1 |
| TOTAL | - | - | - | - | 27 |
Unit 1.0: Introduction
Overview • Turing test • Intelligent agents
Unit 2.0: Problem Solving
Solving Problems by Searching: Uninformed search - Depth First Search • Breadth First Search • DFID • Heuristic search - Generate and Test • Best First Search • Beam Search • Hill Climbing • Problem reduction search • Stochastic search methods
Unit 3.0: Search and Optimization
AND/OR Graphs • AO* • Constraint satisfaction • Means-ends analysis • Simulated Annealing • Particle Swarm Optimization • Game Playing Minimax algorithm • Alpha-beta pruning
Unit 4.0: Knowledge and Reasoning
Building a knowledge base - Propositional logic • First order logic • Inference in first order logic • Resolution refutation proofs • Theorem Proving in First Order Logic • Planning • Partial order planning • Uncertain Knowledge and Reasoning • Probabilities • Bayesian Networks
Unit 5.0: Learning
Overview of different forms of learning: unsupervised • Supervised • Semi-supervised • K-means clustering algorithm • Decision Trees • Neural Networks • Deep Learning
Unit 6.0: Advanced topics
Introduction to Computer Vision • Natural Language Processing • Expert Systems • Robotics • Genetic Algorithm
Unit 1.0: Discrete Fourier Transform (DFT)
Z-transform and DTFT • Frequency domain sampling (Sampling of DTFT) • DFT and its inverse • Zero padding • DFT as a linear transformation (matrix method) • Properties • Spectrum analysis using DFT • Filtering of long data sequences using DFT: overlap save method • Overlap add method
Unit 2.0: Fast Fourier Transform (FFT)- Radix-2 FFT algorithms
Decimation-in-time (DIT-FFT) algorithm • Decimation-in-frequency (DIF-FFT) algorithm • Inverse DFT using FFT algorithms • Goertzel algorithm • Chirp-z transform algorithm
Unit 3.0: Filter Concepts
Frequency response and filter characteristics • Phase delay and group delay • Zero-phase filter • Linear-phase filter • Simple FIR filters • Simple IIR filters • All pass filter • Minimum-phase system • Averaging filter • Comb filter • Digital resonator • Notch filter • Digital sinusoidal oscillator
Unit 4.0: FIR and IIR Digital Filter
Desirability of linear-phase filters • Frequency response of linear phase FIR filters • Filter specifications: absolute specifications • Relative specifications • Analog filter specifications • Design techniques: windowing • Frequency sampling method • Digital Hilbert transformer • Analog filters • Butterworth and Chebyshev approximation • Bilinear transformation method • Warping effect • Spectral transformation • Design of low pass • High pass • Band pass and band elimination filter
Unit 5.0: Realizations of Digital Filters
FIR filter structures: direct form • Cascade form • Linear-phase form • FIR Lattice structure • IIR filter structures: direct form-I • Direct form-II • Cascade form • Parallel form • All pole lattice structure • Lattice-ladder (pole-zero) lattice structure
Unit 6.0: Multirate Signal Processing
Decimation • Interpolation • The polyphase decomposition • Digital filter banks • Nyquist filters • Two-channel QMF
Unit 1.0: Introduction
Alphabet • Languages and grammars • Productions and derivation • Chomsky hierarchy of languages
Unit 2.0: 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
Unit 3.0: Context-free languages and pushdown automata
Context-free grammars (CFG) and Context-free languages (CFL) • Chomsky and Greibach normal forms • Nondeterministic pushdown automata (PDA) and equivalence with CFG • Parse trees • Ambiguity in CFG • Pumping lemma for context-free languages • Deterministic pushdown automata • Closure properties of CFLs
Unit 4.0: Context-sensitive languages
Context-sensitive grammars (CSG) and Context-sensitive languages • Linear bounded automata and equivalence with CSG
Unit 5.0: Turing machines
The basic model for Turing machines (TM) • Turing recognizable (Recursively enumerable) and Turing-decidable (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 enumerators
Unit 6.0: Undecidability
Church-Turing thesis • Universal Turing machine • The universal and diagonalization languages • Reduction between languages and Rice's theorem • Undecidable problems about languages
Unit 1.0: Linear Algebra
Systems of Linear Equations • Matrices • Solving Systems of Linear Equations • Vector Spaces • Linear Independence • Basis and Rank • Linear Mappings • Affine Spaces
Unit 2.0: Analytic Geometry
Norms • Inner Products • Lengths and Distances • Angles and Orthogonality • Orthonormal Basis • Orthogonal Complement • Inner Product of Functions • Orthogonal Projections • Rotations
Unit 3.0: Matrix Decompositions
Determinant and Trace • Eigenvalues and Eigenvectors • Cholesky Decomposition • Eigen Decomposition and Diagonalization • Singular Value Decomposition • Principal Component Analysis • Linear Discriminant Analysis • Matrix Approximation • Matrix Phylogeny
Unit 4.0: Vector Calculus
Differentiation of Univariate Functions • Partial Differentiation and Gradients • Gradients of Vector-Valued Functions • Gradients of Matrices • Useful Identities for Computing Gradients • Backpropagation and Automatic Differentiation • Higher-Order Derivatives • Linearization and Multivariate Taylor Series
Unit 5.0: Probability measures
Elementary probability • Basic facts • Events • Probability measures • Continuity of measures • Integral with respect to a measure • Probabilities on finite and denumerable sets • Probabilities on denumerable sets • Probabilities on uncountable sets • Conditional probability • Bayes formula • Random variables • Random variables • Expected value • Functions of random variables • Variance • Markov and Chebyshev inequalities • A few discrete distributions • Bernoulli distribution • Binomial distribution • Hypergeometric distribution • Poisson distribution • Geometric distribution
Unit 6.0: Discrete Time Markov chains
Stochastic matrices • Oriented graphs • Markov chains • Stochastic processes • Transition matrices • Homogeneous processes • Markov chains • Canonical Markov chains • Some characteristic parameters • Steps for a first visit • Probability of (at least) r visits • Recurrent and transient states • Mean first passage time • Hitting time and hitting probabilities
Unit 1.0: Introduction
What is Software Engineering and its history • Software crisis • Evolution of a Programming System Product • Characteristics of Software • Brooks' No Silver Bullet • Software Myths • Software Development Life Cycles: Software Development Process • The Code-and-Fix model • The Waterfall model • The Evolutionary Model • The Incremental Implementation • Prototyping • The Spiral Model • Software Reuse • Critical Comparisons of SDLC models • An Introduction to Non-Traditional Software Development Process: Rational Unified Process • Rapid Application Development • Agile Development Process
Unit 2.0: Requirements
Importance of Requirement Analysis • User Needs • Software Features and Software Requirements • Classes of User Requirements: Enduring and Volatile • Sub phases of Requirement Analysis • Functional and Nonfunctional requirements • Barriers to Eliciting User requirements • The software requirements document and SRS standards • Requirements engineering • Case Study of SRS for a Real Time System • Tools for Requirements Gathering: Document Flow Chart • Decision Table • Decision Tree • Introduction to nontraditional Requirements
Unit 3.0: Software Design
Goals of good software design • Design strategies and methodologies • Data oriented software design • Coupling • Cohesion • Modular structure • Packaging • Structured Analysis: DFD • Data Dictionary • Structured Design: Structure chart • Object oriented design • Top-down and bottom-up approach • UML • UML Diagrams • Design patterns
Unit 4.0: Software Project Management
Overview of Project Manager Responsibilities & project planning • Software Measurement and Metrics: Line of Code (LOC) • Function Point (FP) based measures • Various Size Oriented Measures: Halstead's software science • Project Size estimation Metrics Project Estimation • Techniques • COCOMO • Staffing Level Estimation • Scheduling • Organization & Team Structures Staffing • Risk Management
Unit 5.0: Software Coding & Testing
Development: Selecting a language • Coding guidelines • Writing code • Code documentation • Testing process • Design of test cases • Functional Testing: Boundary value analysis • Equivalence class testing • Decision table testing • Cause effect graphing • Structural testing • Cyclomatic Complexity Measures: Control flow graphs • Path testing • Data flow and mutation testing • Integration and system testing • Debugging • Alpha & beta testing • Testing tools & standards
Unit 6.0: Software Maintenance
Management of maintenance • Maintenance process • Maintenance models • Regression testing • Reverse engineering • Software reengineering • Configuration management • Documentation • Software Reliability & Quality Management: Introduction to reliability and metrics to reliability measure • Overview of S/W Quality management System ISO 9000 • SEI CMM