subjectId	Discipline Name	Subject Name	Coordinators	Type	Institute	Content
106101007	Computer Science and Engineering	Natural Language Processing	Prof. Pushpak Bhattacharyya	Video	IIT Bombay	Select L1-Introduction L2-Stages of NLP L3-Stages of NLP Continue… L4-Two approaches to NLP L5-Sequence Labelling and Noisy Channel L6-Noisy Channel: Argmax Based Computation L7-Argmax Based Computation L8-Noisy Channel Application to NLP L9-Brief on Probabilistic Parsing & Start of Part of Speech Tagging L10-Part of Speech Tagging L11-Part of Speech Tagging counted… L12-Part of Speech Tagging counted… & Indian Language in Focus; Morphology Analysis L13-PoS Tagging contd… , Indian Language Consideration; Accuracy Measure L14-PoS Tagging; Fundamental Principle; Why Challenging; accuracy L15-PoS Tagging; Accuracy Measurement; Word categories L16-AI and Probability; HMM L17-HMM L18-HMM, Viterbi, Forward Backward Algorithm L19-HMM, Viterbi, Forward Backward Algorithm Contd.. L20-HMM, Forward Backward Algorithms, Baum Welch Algorithm L21-HMM, Forward Backward Algorithms, Baum Welch Algorithm Contd... L22-Natural Language Processing and Informational Retrieval L23-CLIA; IR Basics L24-IR Models: Boolean Vector L25-IR Models: NLP and IR Relationship L26-NLP and IR: How NLP has used IR, Toward Latent Semantic L27-Least Square Method; Recap of PCA; Towards Latent Semantic Indexing(LSI) L28-PCA; SVD; Towards Latent Semantic Indexing(LSI) L29-Wordnet and Word Sense Disambiguation L30-Wordnet and Word Sense Disambiguation(contd…) L31-Wordnet; Metonymy and Word Sense Disambiguation L32-Word Sense Disambiguation L33-Word Sense Disambiguation; Overlap Based Method; Supervised Method L34-Word Sense Disambiguation: Supervised and Unsupervised methods L35-Word Sense Disambiguation: Semi - Supervised and Unsupervised method; resource - constrained WSD L36-Resource Constrained WSD; Parsing L37-Parsing L38-Parsing Algorithm L39-Parsing Ambiguous Sentences; Probabilistic Parsing L40-Probabilistic Parsing Algorithms
106101059	Computer Science and Engineering	Design and Analysis of Algorithms	Prof. Abhiram G Ranade	Web	IIT Bombay	Select Part I
106101060	Computer Science and Engineering	Design and Analysis of Algorithms	Prof. Abhiram G Ranade	Video	IIT Bombay	Select Overview of the course Framework for Algorithms Analysis Algorithms Analysis Framework - II Asymptotic Notations Algorithm Design Techniques : Basics Divide And Conquer-I Divide And Conquer -II Median Finding Divide And Conquer -III Surfing Lower Bounds Divide And Conquer -IV Closest Pair Greedy Algorithms -I Greedy Algorithms - II Greedy Algorithms - III Greedy Algorithms - IV Pattern Matching - I Pattern Matching - II Combinational Search and Optimization I Combinational Search and Optimization II Dynamic Programming Longest Common Subsequences Matrix Chain Multiplication Scheduling with Startup and Holding Costs Average case Analysis of Quicksort Bipartite Maximum Matching Lower Bounds for Sorting Element Distinctness Lower Bounds NP-Completeness-I -Motivation NP - Completeness - II NP-Completeness - III NP-Completeness - IV NP-Completeness - V NP-Completeness - VI Approximation Algorithms Approximation Algorithms Approximation Algorithms for NP
106101061	Computer Science and Engineering	Software Engineering	Prof. Rushikesh K Joshi	Video	IIT Bombay	Select Introduction to Software Engineering-Challenges Introduction to Software Engineering Overview of Phases Overview of Phases Requirements Engineering / Specification Formal Specification Algebraic Specification Methods Systems Modeling Overview Process Modeling - DFD , Function Decomp Process Modeling - DFD, Function Decomp Data Modeling - ER Diagrams, Mapping Data Modeling - ER Diagrams, Mapping Production Quality Software - Introduction Software Design - Primary Consideration Design Patterns Class and Component Level Design Architectural Design Software Testing - I Software Testing - II Structural Programming and Some implementation Software Metrics and Quality Verification and Validation Case Study Case Study Software Evolution Agile Development Software Reuse CBSE Reuse Continued Introduction to Project Management Project Scope Management Project Time Management Estimation - I Estimation - II Project Quality Management Quality Management Systems - I Quality Management Systems Project Configuration Management Project Risk Management Other PM Processes
106101163	Computer Science and Engineering	NOC:Software testing	Prof. Meenakshi D'souza	Video	IIITB	Select Lecture 49_Testing of Object-Oriented Applications Lecture 48_Testing of Object-Oriented Applications Lecture 47_Testing of web Applications and Web Services Lecture 46_Testing of web Applications and Web Services Lecture 45_Testing of web Applications and Web Services Lecture 44:Software Testing Course: Summary after Week 9 Lecture 43:Mutation testing : Grammars and inputs Lecture 42:Mutation Testing:Mutation for integration Lecture 41:Mutation testing Lecture 40:Assignment Solving for Week8 Lecture 6 - Structural Graph Coverage Criteria Lecture 9 - Algorithms: Structural Graph Coverage Criteria Graph Coverage and Finite state Machines Assignment 4: Graph Coverage Criteria Logic: Basics Needed for Software Testing Logic: Coverage Criteria Coverage Criteria, Contd. Logic Coverage Criteria Logic Coverage Criteria: Applied to Test Code_1 Logic Coverage Criteria: Applied to Test Code_2 Logic Coverage Criteria: Issues in Applying to Test Code Logic Coverage Criteria: Applied to Test Specifications Logic Coverage Criteria: Applied to Finite State Machines Lecture 30_Week 6 Assignment Solving Lecture 31_Functional Testing Lecture 32_Input Space Partitioning Lecture 33_Input Space Partitioning: Coverage Criteria Lecture 34_Input Space Partitioning Coverage Criteria: Example Design Integration Testing and Graph Coverage Specification Testing and Graph Coverage Data Flow Graph Coverage Criteria : Applied to Test Code Software Design and Integration Testing Algorithms: Data Flow Graph Coverage Criteria Graph Coverage Criteria: Applied to Test Code Testing Source Code: Classical Coverage Criteria Assignment 2: Structural Coverage Criteria Data Flow Graphs Lecture 7 - Elementary Graph Algorithms Lecture 8 - Elementary Graph Algorithms - Part 2 Lecture 4 -Automation - JUnit as an example Lecture 5 - Basics of Graphs: As used in testing Lecture 1 - Motivation Lecture 2 - Terminologies Lecture 3 - Testing based on Models and Criteria Syntax-Based Testing Mutatioon Testing Mutation Testing for Programs Mutation Testing: Mutation Operators for Source Code Mutation Testing Vs. Graphs and Logic Based Testing Symbolic Testing Symbolic Testing 2 DART: Directed Automated Random Testing DART: Directed Automated Random Testing - 2 DART: Directed Automated Random Testing 3 Testing of Object-Oriented Applications Testing of Mobile Applications Non-Functional System Testing Regression Testing Assignment: Week 11 Solving Software Testing: Summary at the End of the Course
106102011	Computer Science and Engineering	Computational Geometry	Prof. Sandeep Sen	Video	IIT Delhi	Select Introduction Visibility Problems 2D Maxima Line Sweep Method Segment Intersection Problem Line Sweep: Rectangle Union Convex Hull Convex Hull Contd Quick Hull More Convex Hull Algorithms Intersection of Half Planes and Duality Intersection of Half Planes and Duality Contd Lower Bounds Planar Point Location Point Location and Triangulation Contd... Triangulation of Arbitrary Polygon. Voronoi Diagram : Properties Voronoi Diagram Construction Delaunay Triangulation. Quick sort and Backward Analysis Generalized RIC RIC Continued Arrangements Zone Theorem and Application Levels Range Searching : Introduction Orthogonal Range searching Priority Search Trees Non - Orthogonal Range Searching Half - Plane Range Query Well Separated Partitioning Quadtrees Epsilon -WSPD Construction of Epsilon - WSPD Epsilon - WSPD to Geometric Spanner Epsilon-Nets & VC Dimension Epsilon-Nets & VC Dimension contd Geometric Set Cover Geometric Set Cover (with Bounded VC Dimension) Shape Representation Shape Comparison
106102013	Computer Science and Engineering	Logic for CS	Prof. S. Arun Kumar	Video	IIT Delhi	Select Introduction Propositional Logic Syntax Semantics of Propositional Logic Logical and Algebraic Concepts Identities and Normal forms Tautology Checking Propositional Unsatisfiability Analytic Tableaux Consistency and Completeness The Completeness Theorem Maximally Consistent Sets Formal Theories Proof Theory : Hilbert-style Derived Rules The Hilbert System : Soundness The Hilbert System :Completeness Introduction to Predicate Logic The Semantic of Predicate Logic Subsitutions Models Structures and Substructures First - Order Theories Predicate Logic: Proof Theory (Contd..) Existential Quantification Normal Forms Skalemization Substitutions and Instantiations Unification Resolution in FOL More on Resolution in FOL Resolution : Soundness and Completeness Resolution and Tableaux Completeness of Tableaux Method Completeness of the Hilbert System First -Order Theories Towards Logic Programming Verification of Imperative Programs Verification of WHILE Programs References
106102062	Computer Science and Engineering	Computer Architecture	Prof. Anshul Kumar	Video	IIT Delhi	Select Introduction to Computer Architecture History of Computers Instruction Set Architecture - I Instruction Set Architecture - II Instruction Set Architecture - III Recursive Programs Architecture Space Architecture Examples Performance Performance Binary Arithmetic, ALU Design ALU Design, Overflow Multiplier Design Divider Design Fast Addition , Multiplication Floating Point Arithmetic Processor Design - Introduction Processor Design Processor Design - Simple Design Processor Design - Multi Cycle Approach Processor Design - Control for Multi Cycle Processor Design Micro programmed Control Processor Design Exception Handling Pipelined Processor Design Basic Idea Pipelined Processor Design: Data path Pipelined Processor Design: Handling Data Pipelined Processor Design Memory Hierarchy : Basic Idea Memory Hierarchy : Cache Organization Memory Hierarchy : Cache Organization Memory Hierarchy : Virtual Memory Memory Hierarchy : Virtual Memory Input / Output Subsystem: Introduction Input / Output Subsystem: Interfaces and buses Input / Output Subsystem: Interfaces and buses Input / Output Subsystem: I/O Operations Input / Output Subsystem: Designing I/O Systems Concluding Remarks
106102063	Computer Science and Engineering	Computer Graphics	Prof. Prem K Kalra	Web	IIT Delhi	Select Definition Basic elements History Application Graphic rendering pipeline Input devices Line Drawing Algorithm Midpoint Circle Algorithm Ellipse drawing algoritm Point Clipping Line Clipping Polygon Clipping Two - Dimensional Three - Dimensional 3D Viewing Parametric Curves Introduction Generation of Fractals Geometric fractals Recapitulation Random Fractals Applications Conventional Animation Real time vs Image Animation Techniques Rotoscopy Key Framing Spline Driven Animation Morphing Particle Systems Illumination Model Polygon Shading Solid Models
106102064	Computer Science and Engineering	Data Structures And Algorithms	Prof. Naveen Garg	Video	IIT Delhi	Select Introduction to Data Structures and Algorithms Stacks Queues and Linked Lists Dictionaries Hashing Trees Tree Walks / Traversals Ordered Dictionaries Deletion Quick Sort AVL Trees AVL Trees Trees Red Black Trees Insertion in Red Black Trees Disk Based Data Structures Case Study: Searching for Patterns Tries Data Compression Priority Queues Binary Heaps Why Sorting More Sorting Graphs Data Structures for Graphs Two Applications of Breadth First Search Depth First Search Applications of DFS DFS in Directed Graphs Applications of DFS in Directed Graphs Minimum Spanning Trees The Union Prims Algorithm for Minimum Spanning Trees Single Source Shortest Paths Correctness of Dijkstras Algorithm Single Source Shortest Paths
106102065	Computer Science and Engineering	Introduction to Computer Graphics	Prof. Prem K Kalra	Video	IIT Delhi	Select Introduction Raster Graphics Raster Graphics (Contd.) Clipping Polygon Clipping and Polygon Scan Conversion Transformations Transformations (contd.) 3D Viewing 3D Viewing (Contd.) Curves Assignment - I Curves (Contd.) Curves (Contd.) Curves (Contd.) Curves (Contd.) Surfaces Surfaces(Contd.) Surfaces(Contd.) Surfaces(Contd.) Hierarchical Models Rendering Rendering(Contd.) Rendering(Contd.) Ray Tracing Ray Tracing(Contd.) Ray Tracing(Contd.) Assignment: Ray Tracing Hidden Surface Elimination Hidden Surface Elimination(Contd.) Hidden Surface Elimination(Contd.) Fractals Fractals(Contd.) Computer Animation Animation(Contd.) Animation(Contd.)
106102066	Computer Science and Engineering	Introduction to Problem Solving and Programming	Prof. S. Arun Kumar	Web	IIT Delhi	Select Introduction to computing Our computing tool Primitives: Integer & Real Example : Fibonacci Primitives: Booleans Technical completeness & Algorithms Algorithm Refinement Variations: Algorithms & code Names,Scopes & Recursion Floating point Root Finding,Composition and Recursion Termination and space complexity Efficiency measures and Speed-ups Invariance & Correctness Tuples, Lists & the Generation of Primes Compound Data & Lists Compound Data & Lists Algorithms Higher order Functions Structured data user defined structured data types Introducing a memory model Imperative programming Arrays Large Example : Tautology Checking Tautology Checking contd
106102067	Computer Science and Engineering	Principles of Programming Languages	Prof. S. Arun Kumar	Video	IIT Delhi	Select Introduction Syntax Grammars Ambiguity PLO:Syntax Semantics Syntactic Classes Transition Systems PL0 : Expressions Binding Environments Declarations Commands Stores Summary Declarations and Commands Blocks Qualification Pragmatics Data Structured Data Sequences Control Non- Determinacy Programming Languages Programming Languages Programming Languages Data as Functions Data and Fixpoints Normal Forms Programming Languages Monomorphism Polymorphism Type Checking Contexts Abstracts Procedures Meanings Parameters The Future
106102114	Computer Science and Engineering	Parallel Computing	Dr. Subodh Kumar	Video	IIT Delhi	Select Introduction Parallel Programming Paradigms Parallel Architecture Parallel Architecture (case studies) Open MP Open MP(Contd.) Open MP(Contd..) Open MP&PRAM Model of Computation PRAM Models of Parallel Computation,Complexity Memory Consistency Memory Consistency & Performance Issues Parallel Program Design Shared Memory & Message Passing MPI MPI(Contd.) MPI(Contd..) Algorithmic Techniques Algorithmic Techniques(Contd.) Algorithmic Techniques(Contd..) CUDA CUDA(Contd.) CUDA(Contd..) CUDA(Contd...) CUDA(Contd....) CUDA(Contd.....) CUDA(Contd......) Algorithms,Merging & Sorting Algorithms,Merging & Sorting(Contd.) Algorithms,Merging & Sorting(Contd..) Algorithms,Merging & Sorting(Contd...) Algorithms,Merging & Sorting(Contd....) Lower Bounds Lock Free Synchronization,Load Stealing Lock Free Synchronization,Graph Algorithms
106102157	Computer Science and Engineering	NOC:Computer Architecture	Prof. Smruti R.Sarangi	Video	IIT Delhi	Select Introduction to Computer Architecture The Language of Bits Part-I The Language of Bits Part-II The Language of Bits Part-III Assembly Language Part-I Assembly Language Part-II Assembly Language Part-III ARM Assembly Language Part-I ARM Assembly Language Part-II x86 Assembly Language Part-I x86 Assembly Language Part-II x86 Assembly Language Part-III x86 Assembly Language Part-IV A Primer on Digital Logic Part-I A Primer on Digital Logic Part-II A Primer on Digital Logic Part-III Computer Arithmetic Part-I Computer Arithmetic Part-II Computer Arithmetic Part-III Computer Arithmetic Part-IV Computer Arithmetic Part-V Computer Arithmetic Part-VI Processor Design Part-I Processor Design Part-II Processor Design Part-III Principles of Pipelining Part-I Principles of Pipelining Part-II Principles of Pipelining Part-III Principles of Pipelining Part-IV The Memory Systems Part-I The Memory Systems Part-II The Memory Systems Part-III The Memory Systems Part-IV
106102163	Computer Science and Engineering	NOC:Introduction to Parallel Programming in OpenMP	Dr. Yogish Sabharwal	Video	IIT Delhi	Select Manual distribution of work and critical sections Distributing for loops and reduction Vector-Vector operations (Dot product) Matrix-Vector operations (Matrix-Vector Multiply) Matrix-Matrix operations (Matrix-Matrix Multiply) Introduction to tasks Task queues and task execution Accessing variables in tasks Completion of tasks and scoping variables in tasks Recursive task spawning and pitfalls Understanding LU Factorization Parallel LU Factorization Locks Advanced Task handling Matrix Multiplication using tasks The OpenMP Shared Memory Consistency Model Shared Memory Consistency Models and the Sequential Consistency Model Computing sum: first attempt at parallelization OpenMP: thread private variables and more constructs Race Conditions OpenMP: Scoping variables and some race conditions Context Switching OpenMP: Basic thread functions Program with Single thread Program Memory with Multiple threads and Multi-tasking OpenMP: A parallel Hello World Program Interconnection networks in Distributed Memory architectures Intuition for Shared and Distributed Memory architectures Shared and Distributed Memory architectures OpenMP: About OpenMP Cache and Temporal Locality Cache, Memory bandwidth and Spatial Locality Parallel Architectures and Programming Models Pipelining Superpipelining and VLIW Memory Latency Introduction to Parallel Programming
106103015	Computer Science and Engineering	Computational Number Theory & Cryptography	Dr. Pinaki Mitra	Web	IIT Guwahati	Select Complexity of Computation & Complexity Classes Encoding Scheme Elementary Number-Theory Euclid's Algorithm Modular Arithmetic Groups Subgroups Primitive Roots Generator Computation Solving modular linear equations Modular exponentiation Chinese Remainder Theorem Discrete Logarithm Problem Quadratic Residues Diffie Hellman key Exchange Cryptosystems Based on Discrete Log Public Key Cryptosystem & RSA Choice of the Public Key Attacks on RSA & Remedies Rabin Cryptosystem Pollard-Rho Method Pollard Rho Analysis Current state of the art Large prime variant Dixon's factorization method Primality Testing Fermat Primality Test AKS PRIMALITY TEST Elliptic Curve Cryptography Zero Knowledge Proof Elliptic Curves Elgamal Digital Signature Scheme Blind & Prony Signature Short signature scheme I Short signature scheme II Video Data Cippers Cryptographic Hash Function Quadratic-Sieve Factoring Elliptic Curves(contd.) and Finite Fields ECDLP
106103016	Computer Science and Engineering	VLSI Design Verification and Test	Prof. Jatindra Kumar Deka	Web	IIT Guwahati	Select Introduction to Digital VLSI Design Flow High Level Design Representation Transformations for High Level Synthesis Introduction to HLS: Scheduling, Allocation and Binding Problem Scheduling Algorithms Binding and Allocation Algorithms Two level Boolean Logic Synthesis Heuristic Minimization of Two-Level Finite State Machine Synthesis Multilevel Implementation Introduction and construction Ordered Binary Decision Diagram Operations on Ordered Binary Decision Diagram Ordered Binary Decision Diagram for Sequential Circuits Introduction and Basic Operations on Temporal Logic Syntax and Semantics of CLT Equivalence between CTL Formulas Verification Techniques Model Checking Algorithm Symbolic Model Checking Introduction to Digital VLSI Testing Functional and Structural Testing Fault Equivalence Fault Simulation Testability Measures (SCOAP) Introduction to Automatic Test Pattern Generation (ATPG) and ATPG Algebras D-Algorithm ATPG for Synchronous Sequential Circuits Scan Chain based Sequential Circuit Testing Built in Self Test Memory Testing
106103068	Computer Science and Engineering	Computer Organization and Architecture	Prof. Jatindra Kumar Deka	Web	IIT Guwahati	Select Introduction to computer System and its submodules Number System and Representation of information Brief History of Computer Evolution Problems-Introduction Arithmetic and logical operation and Hardware implementation Implementation issues of some operation Problems-Arithmatic and Logic Unit Concept of Memory Cache Memory Memory Management Virtual Memory Problems-Memory Various Addressing Modes Machine Instruction Instruction Format Problems-Instruction Set & Addressing Introduction to CPU Design Processor Organization Execution of complete Instruction Design of control unit Microprogrammed Control - I Microprogrammed Control - II Problems-CPU Design Introduction to I/O Program Controlled I/O Interrupt Controlled I/O Direct Memory Access Problems-Input / Output I/O Buses External Storage Devices Disk Performance Problems-I/O Device Connection Introduction to RISC Design issues of RISC Problems-Reduced Instruction Set Programming Introduction to Pipeline Processor Performance Issues Branching Problems-Pipelining Processor Introduction to Parallel Processing Interconnection Networks Cache Coherence Problems-Multi-Processor / Parallel Processing Organization of Intel 8085 Micro-Processor Instruction set of Intel 8085 Micro-Processor Organization of Intel 8086 Micro-Processor Instruction formats of Intel 8086 Programming of Micro-processor Problems-Intel 8085/8086 Micro-Processor
106103069	Computer Science and Engineering	Data Structures and Program Methodology	Dr. S.V. Rao	Web	IIT Guwahati	Select What is Data Structure Methods of Interpreting bit Setting Type of Data Structure Introductions to Algorithms Time Complexity Recurrence Linear Data Structures Linked Lists Introduction to Sorting Sink Sort Selection Sort Merge Sort Quick Sort Radix Sort Searching Graphs I : Representation and Traversal Graphs II: Basic Algorithms Binary Tree Heap sort AVL-tree B-Tree Hashing Techniques Introduction String Algorithm String copy Pattern Matching Life cycle Problems-Introduction to Data Structures Example 1-Introduction to Algorithms Example 2-Introduction to Algorithms Problems-Introduction to Algorithms Example-Introduction to Stack Example-Introduction to Queue Problems-Linear Data Structures Example-Inserting and Removing Nodes from a List Example-Linked Implemented of Stacks Example-Getnode and Freenode Operation Example-Linked Implemented of queues Example-List Implementation of Priority queue Example-Header Nodes Example-Circular Lists Example-Doubly Linked List Problems-Linked list Example-Linear Search Example-Binary Search Example-k nigsberg bridge problem Problems-GRAPHS Representation Example-Minimum Spanning tree Example-Single Source Shortest Path Problems Example-Array Representation of Binary Tree Example-Linked Representation of Binary Tree Example-Examples-Heap sort Problems-Heap sort Problems-Search Trees Problems-Tables Problems-Sets Problems-STRING ALGORITHM Example-Code Designing Example-Coding Example-Programming Style Examples-Program devlopment Problems-Program devlopment Example-Testing Method Example-Verification Procedures Problems-Program Testing and Verification
106103070	Computer Science and Engineering	Theory of Automata and Formal Languages	Dr. Diganta Goswami	Web	IIT Guwahati	Select Alphabets, Strings and languages Automata and Grammars Finite Automata Removing Transition Nondeterministic Finite Automata (NFA) Regular Expression Regular Grammars Pumping Lenma-Description Minimization of Deterministic Finite Automata Some decision properties of Regular Languages Description-Context-free Grammars Formal Definition ,behavior -PDA Equivalence of PDAs and CFGs PDAs and CFGs Description-Deterministic PDA Description-DPDA and DCFLs Description-Simplification of CFG Description-Context Free Language(CFL) Description- Closure Property of CFLs Description-Decision Algorithms for CFLs Description-Turing Machines Description-Recursively Enumerable Language Description- Post's Correspondence Problem (PCP) Description-Chomsky Hierarchy
106103115	Computer Science and Engineering	Human-Computer Interaction	Dr.Samit Bhattacharya	Web	IIT Guwahati	Select Course objective and overview Historical evolution of the field Concept of usability - definition and elaboration HCI and software engineering GUI design and aesthetics Prototyping techniques Introduction to different types of models Keystroke Level Model -I Keystroke Level Model - II (CMN)GOMS Individual Models of Human Factors - I Individual Models of Human Factors - II A Case Study on Model-Based Design - I A Case Study on Model-Based Design - II Shneiderman’s eight golden rules Norman’s seven principles Norman’s model of interaction Nielsen’s ten heuristics with example of its use Heuristic evaluation Contextual inquiry Cognitive walkthrough Introduction to Empirical Research - I Introduction to Empirical Research - II Analysis of Empirical Data Empirical Research Case Study Hierarchical task analysis (HTA) Engineering Task Models and CTT CTT Example Introduction to formalism in dialog design, design using FSM StateCharts Petri Nets Use of Formalism Introduction Model Human Processor - I Model Human Processor - II OOP- Introduction OOM- Object Oriented Modeling of User Interface Design Case Study 1- Multi-Key press Hindi Text Input Method on a Mobile Phone Case Study 2 - GUI design for a mobile phone based Matrimonial application.during emergency Case Study 3 - Employment Information System for unorganised construction workers on a Mobile Phone.
106103116	Computer Science and Engineering	Design Verification and Test of Digital VLSI Circuits	Prof. Jatindra Kumar Deka	Video	IIT Guwahati	Select Introduction to Digital VLSI Design Flow High Level Design Representation Transformations for High Level Synthesis Introduction to HLS: Scheduling, Allocation and Binding Problem Scheduling Algorithms-1 Scheduling Algorithms-2 Binding and Allocation Algorithms Two level Boolean Logic Synthesis-1 Two level Boolean Logic Synthesis-2 Two level Boolean Logic Synthesis-3 Heuristic Minimization of Two-Level Circuits Finite State Machine Synthesis Multilevel Implementation Introduction to formal methods for design verification Temporal Logic: Introduction and Basic Operators Syntax and Semantics of CTL Syntax and Semantics of CTL – Continued Equivalence between CTL Formulas Introduction to Model Checking Model Checking Algorithms I Model Checking Algorithms II Model Checking with Fairness Binary Decision Diagram: Introduction and construction Ordered Binary Decision Diagram Operation on Ordered Binary Decision Diagram Ordered Binary Decision Diagram for State Transition Systems Symbolic Model Checking Introduction to Digital VLSI Testing Functional and Structural Testing Fault Equivalence Fault Simulation-1 Fault Simulation-2 Fault Simulation-3 Testability Measures (SCOAP) Introduction to Automatic Test Pattern Generation (ATPG) and ATPG Algebras D-Algorithm-1 D-Algorithm-2 ATPG for Synchronous Sequential Circuits Scan Chain based Sequential Circuit Testing-1 Scan Chain based Sequential Circuit Testing-2 Built in Self Test-1 Built in Self Test-2 Memory Testing-1 Memory Testing-2
106104019	Computer Science and Engineering	Computer Algorithms - 2	Prof. Shashank K. Mehta	Video	IIT Kanpur	Select Lecture-01-Graph_Basics Lecture-02-Breadth_First_Search Lecture-03-Dijkstra_Algo Lecture-04-All Pair Shortest Path Lecture-05-Matriods Lecture-06-Minimum Spanning Tree Lecture-07-Edmond's Matching Algo I Lecture-08-Edmond's Matching Algo II Lecture-09-Flow Networks Lecture-10-Ford Fulkerson Method Lecture-11-Edmond Karp Algo Lecture-12-Matrix Inversion Lecture-13-Matrix Decomposition Lecture-14-Knuth Morris Pratt Algo Lecture-15-Rabin Karp Algo Lecture-16-NFA Simulation Lecture-17-Integer-Polynomial OpsI Lecture-18-Integer-Polynomial OpsII Lecture-19-Integer-Polynomial OpsIII Lecture-20-Chinese RemainderI Lecture-21-Chinese RemainderII Lecture-22-Chinese RemainderIII Lecture-23-:Discrete Fourier TransformI Lecture-24-Discrete Fourier TransformII Lecture-25-Discrete Fourier TransformIII Lecture-26-Schonhage Strassen Algo Lecture-27-Linear ProgrammingI Lecture-28-Linear ProgrammingII Lecture-29-GeometryI Lecture-30-GeometryII Lecture-31-GeometryIII Lecture-32-Approximation AlgoI Lecture-33-Approximation AlgoII Lecture-34-Approximation AlgoIII Lecture-35-General: Dynamic Programming
106104021	Computer Science and Engineering	Indexing and Searching Techniques in Databases	Dr. Arnab Bhattacharya	Web	IIT Kanpur	Select Basic Database Queries Advanced Database Queries Error Measures Memory and Disk Accesses Vector and Metric Spaces Distance Functions Earth Mover's Distance (EMD) Earth Mover's Distance (EMD) Static and Dynamic Hashing Linear hashing Locality Sensitive Hashing and Grid File One-dimensional Orderings Index structure Quadtrees and k-d-trees Range Trees and Interval Trees Voronoi Diagrams and Tries Disk-based Index Structures General Framework R-trees R-trees R-tree Variants SS-trees,SR-trees,P-trees X-tree Analysis of High Dimensional Data Analysis of Index Structures Pyramid Technique and VA-files M-trees Dimensionality Reduction Singular Value Decomposition (SVD) Principal Component Analysis (PCA) FastMap Embedding Embedding DFT and DCT Wavelets V-optimal Histograms Aggregation Incremental Nearest Neighbor Skyline Queries Skyline Queries Reading Material
106104024	Computer Science and Engineering	Parallel Computer Architecture	Dr. Mainak Chaudhuri	Web	IIT Kanpur	Select Evolution of Processor Architecture Moore's Law and Multi-cores Evaluating Performance Shared Memory Multiprocessors Pipelining and Hazards Instruction Issue Algorithms Virtual Memory, TLB, and Caches Cache Hierarchy and Memory-level Parallelism MIPS R10000: A Case Study Communication Architecture Design Issues in Parallel Computers Steps in Writing a Parallel Program Parallelizing a Sequential Program Load Balancing and Domain Decomposition Locality and Communication Optimizations Multiprocessor Organizations and Cache Coherence Introduction to Cache Coherence Protocols Introduction to Cache Coherence Sequential Consistency and Cache Coherence Protocols Performance of Coherence Protocols Introduction to Synchronization Scalable Locking Primitives Barriers and Speculative Synchronization Write Serialization in a Simple Design Protocols for Split-transaction Buses Case Studies Scalable Snooping and AMD Hammer Protocol Scalable Multiprocessors Basics of Directory SGI Origin 2000 Managing Directory Overhead Protocol Occupancy and Directory Controllers SCI Protocol Sequential Consistency and Relaxed Models Release Consistency and Delayed Consistency Software Distributed Shared Memory Multiprocessors Introduction to Routers Routing Algorithms Simultaneous Multithreading and Chip-multiprocessing Case Studies: IBM Power4 and IBM Power5 Case Studies: Intel Montecito and Sun Niagara
106104025	Computer Science and Engineering	Program Optimization for Multi-core Architectures	Prof. Sanjeev K Aggarwal	Web	IIT Kanpur	Select Evolution of Processor Architecture Introduction to Multi-core Architecture Virtual Memory and Caches Cache Hierarchy and Memory-level Parallelism Communication Architectures and Communication Costs Preliminaries of Parallel Programming Examples of Shared Memory and Message Passing Programming Optimizing Shared Memory Performance Performance Issues in Shared Memory Introduction to Coherence Introduction to Snoopy Coherence Cache Coherence Protocols Introduction to Atomic Primitives Scalable Locks and Barriers Memory Consistency Models and Case Studies of Multi-core Case Studies of Multi-core Multiprocessor Organizations and Cache Coherence Sharing Patterns and Cache Coherence Protocols What is Parallelization? The “omp sections” Directive Clause and Routines Intel Compilers and Threading Tools Intel Compilers and Threading Tool Code Optimization Supercomputing Applications SIMD Architecture Algorithm and Interval Structural Analysis Reaching Definition Analysis Data Dependence Analysis Iteration Data Dependence in Parallel Loops Symbolic Analysis Amdahl’s Law Cycle Shrinking Multi-core computing CPU Scheduling Priority and Schedule Multi-processor Scheduling Multi-core Computing Synchronization Solution to Critical Section Problem Multi-core ComputingInter-process Communication Multiprocessor Techniques Cryptography and ECB
106104028	Computer Science and Engineering	Theory of Computation	Prof. Somenath Biswas	Video	IIT Kanpur	Select Lecture-01 What is theory of computation? Set membership problem, basic notions like alphabet, strings, formal languages. Lecture-02-Introduction to finite automaton. Lecture-03-Finite automata continued, deterministic finite automata(DFAs), language accepted by a DFA. Lecture-04-Regular languages, their closure properties. Lecture-05-DFAs solve set membership problems in linear time, pumping lemma. Lecture-06-More examples of nonregular languages, proof of pumping lemma, pumping lemma as a game, converse of pumping lemma does not hold. Lecture-07-A generalization of pumping lemma, nondeterministic finite automata (NFAs), computation trees for NFAs. Lecture-08-Formal description of NFA, language accepted by NFA, such languages are also regular. Lecture-09-'Guess and verify' paradigm for nondeterminism. Lecture-10-NFA's with epsilon transitions. Lecture-11-Regular expressions, they denote regular languages. Lecture-12-Construction of a regular expression for a language given a DFA accepting it. Algebraic closure properies of regular languages. Lecture-13-Closure properties continued. Lecture-14-Closure under reversal, use of closure properties. Lecture-15-Decision problems for regular languages. Lecture-16-About minimization of states of DFAs. Myhill-Nerode theorem. Lecture-17-Continuation of proof of Myhill-Nerode theorem. Lecture-18-Application of Myhill-Nerode theorem. DFA minimization. Lecture-19-DFA minimization continued. Lecture-20-Introduction to context free languages (cfls) and context free grammars (cfgs). Derivation of strings by cfgs. Lecture-21-Languages generated by a cfg, leftmost derivation, more examples of cfgs and cfls. Lecture-22-Parse trees, inductive proof that L is L(G). All regular languages are context free. Lecture-23-Towards Chomsky normal forms: elimination of useless symbols, analysis of reachable symbols, generating nonterminals, order of substeps matter. Lecture-24-Simplification of cfgs continued, Removal of epsilon productions: algorithm and its correctness. Lecture-25-Elimination of unit productions. Converting a cfg into Chomsky normal form. Towards pumping lemma for cfls Lecture-26-Pumping lemma for cfls. Adversarial paradigm. Lecture-27-Completion of pumping lemma proof. Examples of use of pumping lemma. Converse of lemma does not hold. Closure properties of cfls. Lecture-28-Closure properties continued. cfls not closed under complementation. Lecture-29-Another example of a cfl whose complement is not a cfl. Decision problems for cfls. Lecture-30-More decision problems. CYK algorithm for membership decision. Lecture-31-Introduction to pushdown automata (pda). Lecture-32-pda configurations, acceptance notions for pdas. Transition diagrams for pdas Lecture-33-Equivalence of acceptance by empty stack and acceptance by final state. Lecture-34-Turing machines (TM): motivation, informal definition, example, transition diagram. Lecture-35-Execution trace, another example (unary to binary conversion). Lecture-36-Example continued. Finiteness of TM description, TM configuration, language acceptance, definition of recursively enumerable (r.e.) languages. Lecture-37-Notion of non-acceptance or rejection of a string by a TM. Multitrack TM, its equivalence to standard TM. Multitape TMs. Lecture-38-Simulation of multitape TMs by basic model. Nondeterministic TM (NDTM). Equivalence of NDTMs with deterministic TMs. Lecture-39-Counter machines and their equivalence to basic TM model. Lecture-40-TMs can simulate computers, diagonalization proof. Lecture-41-Existence of non-r.e. languages, recursive languages, notion of decidability. Lecture-42-Separation of recursive and r.e. classes, halting problem and its undecidability.
106104072	Computer Science and Engineering	Compiler Design	Prof. Sanjeev K Aggarwal	Web	IIT Kanpur	Select Introduction to the course Introduction to Compilers Lexical Analysis Syntax Analysis Semantic Analysis Runtime System Intermediate Representation and Symbol Table Intermediate Code Generation Code Generation Questions
106104073	Computer Science and Engineering	Computer Organisation and Architecture	Prof. Bhaskaran Raman	Web	IIT Kanpur	Select Computer Architecture Performance Comparison Amdahl's Law Instruction Set DLX DLX Unpipelined Implementation Data Hazards Exceptions and Pipelining Pipelining Multi-cycle Opns Handling WAW Hazards Instruction Level Parallelism Handling Control Dependence Dynamic Scheduling Branch Prediction Buffer Superscalar DLX Hardware Support for Speculation Speculation Block Placement Cache Performance Prioritize Read Misses over Writes Small and Simple Caches Main Memory Multiprocessors Multiprocessing: Classification Cache Coherence Snooping-Based Protocols Synchronization Sequential Consistency Interconnection Networks Buses for Communication I/O Performance Log-Structured File System Vector Processing Key Take-Away Ideas
106104074	Computer Science and Engineering	Introduction to Problem Solving and Programming	Prof. D. Gupta	Video	IIT Kanpur	Select Lecture 1 Lecture 2 Lecture 3 Lecture 4 Lecture 5 Lecture 6 Lecture 7 Lecture 8 Lecture 9 Lecture 10 Lecture 11 lecture 12 Lecture 13 Lecture 14 Lecture 15 Lecture 16 Lecture 17 Lecture 18 Lecture 19 Lecture 20 Lecture 21 Lecture 21 Lecture 23 Lecture 24
106104118	Computer Science and Engineering	Riemann Hypothesis and its Applications	Prof. Manindra Agrawal	Video	IIT Kanpur	Select Lecture-01 Lecture-02 Lecture-03 Lecture-04 Lecture-05 Lecture-06 Lecture-07 Lecture-08 Lecture-09 Lecture-10 Lecture-11 Lecture-12 Lecture-13 Lecture-14 Lecture-15 Lecture-16 Lecture-17 Lecture-18 Lecture-19 Lecture-20 Lecture-21 Lecture-22 Lecture-23 Lecture-24 Lecture-25 Lecture-26 Lecture-27 Lecture-28 Lecture-29 Lecture-30
106104119	Computer Science and Engineering	Biometrics	Prof. Phalguni Gupta	Video	IIT Kanpur	Select Lecture-01 Biometrics Lecture-02 Biometrics Lecture-03 Biometrics Lecture-04 Biometrics Lecture-05 Biometrics Lecture-06 Biometrics Lecture-07 Biometrics Lecture-08 Biometrics Lecture-09 Biometrics Lecture-10 Biometrics Lecture-11 Biometrics Lecture-12 Biometrics Lecture-13 Biometrics Lecture-14 Biometrics Lecture-15 Biometrics Lecture-16 Biometrics Lecture-17 Biometrics Lecture-18 Biometrics Lecture-19 Biometrics Lecture-20 Biometrics Lecture-21 Biometrics Lecture-22 Biometrics Lecture-23 Biometrics Lecture-24 Biometrics Lecture-25 Biometrics Lecture-26 Biometrics
106104120	Computer Science and Engineering	Parallel Algorithm	Prof. Phalguni Gupta	Video	IIT Kanpur	Select Lecture-21 Parallel Algorithm Lecture-20 Parallel Algorithm Lecture-19 Parallel Algorithm Lecture-18 Parallel Algorithm Lecture-17 Parallel Algorithm Lecture-16 Parallel Algorithm Lecture-15 Parallel Algorithm Lecture-14 Parallel Algorithm Lecture-13 Parallel Algorithm Lecture-12 Parallel Algorithm Lecture-11 Parallel Algorithm Lecture-10 Parallel Algorithm Lecture-09 Parallel Algorithm Lecture-08 Parallel Algorithm Lecture-07 Parallel Algorithm Lecture-06 Parallel Algorithm Lecture-05 Parallel Algorithm Lecture-04 Parallel Algorithm Lecture-01 Parallel Algorithm Lecture-02 Parallel Algorithm Lecture-03 Parallel Algorithm Lecture-22 Parallel Algorithm Lecture-23 Parallel Algorithm Lecture-24 Parallel Algorithm Lecture-25 Parallel Algorithm
106104122	Computer Science and Engineering	Computer Architecture	Dr. Mainak Chaudhuri	Video	IIT Kanpur	Select Lecture-01-Introduction, Amdahl's law, CPI equation Lecture-02-CPI equation, research practices, instruction set architecture Lecture-03-Instruction set architecture Lecture-04-Instruction set architecture Lecture-05-Instruction set architecture, case study with MIPS-I Lecture-06-Case study with MIPS-I Lecture-07-Case study with MIPS-I Lecture-08-Binary instrumentation for architectural studies: PIN Lecture-09-Binary instrumentation for architectural studies: PIN Lecture-10-Basic pipelining, branch prediction Lecture-11-Basic pipelining, branch prediction Lecture-12-Basic pipelining, branch prediction Lecture-13-Basic pipelining, branch prediction Lecture-14-Basic pipelining, branch prediction Lecture-15-Basic pipelining, branch prediction Lecture-16-Basic pipelining, branch prediction Lecture-17-Basic pipelining, branch prediction Lecture-18-Basic pipelining, branch prediction Lecture-19-Basic pipelining, branch prediction Lecture-20-Dynamic scheduling, speculative execution Lecture-21-Dynamic scheduling, speculative execution Lecture-22-Dynamic scheduling, speculative execution Lecture-23-Dynamic scheduling, speculative execution Lecture-24-Dynamic scheduling, speculative execution Lecture-25-Virtual memory and caches Lecture-26-Virtual memory and caches Lecture-27-Virtual memory and caches Lecture-28-Topics in memory system, DRAM and SRAM technology Lecture-29-Topics in memory system, DRAM and SRAM technology Lecture-30-Topics in memory system, DRAM and SRAM technology Lecture-31-Case study: MIPS R10000 Lecture-32-Case study: MIPS R10000 Lecture-33-Case study: Alpha 21264 Lecture-34-Case study: Intel Pentium 4 Lecture-35-Input/Output Lecture-36-Simultaneous multithreading, multi-cores
106104123	Computer Science and Engineering	Compiler Design	Prof. Sanjeev K Aggarwal	Video	IIT Kanpur	Select Lecture-01 Lecture-02-Compiler Design Lecture-03-Compiler Design Lecture-04-Compiler Design Lecture-05-Compiler Design Lecture-06-Compiler Design Lecture-07-Compiler Design Lecture-08-Compiler Design Lecture-09-Compiler Design Lecture-10-Compiler Design Lecture-11-Compiler Design Lecture-12-Compiler Design Lecture-13-Compiler Design Lecture-14-Compiler Design Lecture-15-Compiler Design Lecture-16-Compiler Design Lecture-17-Compiler Design Lecture-18-Compiler Design Lecture-19-Compiler Design Lecture-20-Compiler Design Lecture-21-Compiler Design Lecture-22-Compiler Design Lecture-23-Compiler Design Lecture-24-Compiler Design Lecture-25-Compiler Design Lecture-26-Compiler Design Lecture-27-Compiler Design Lecture-28-Compiler Design Lecture-29-Compiler Design Lecture-30-Compiler Design
106104128	Computer Science and Engineering	NOC:Introduction to programming in C	Prof.Satyadev Nandakumar	Video	IIT Kanpur	Select Intro - Process of programming Intro - GCD Intro - Programming cycle Intro - Tracing a simple program Intro - Variables Intro - Operators Loops - While Loops - While example Loops - While GCD example Loops - Longest 1 Loops - Longest 2 Loops - Longest 3 Loops - Do-while Loops - Matrix using nested loops Loops - For Loops - Matrix using nested for loops Loops - Break statement Loops - Continue statement Loops - Continue statement example Data types in C ASCII code Operators Expressions Associativity Precedence of operators Expression evaluation Functions - Introduction Functions - How functions are executed Functions - Examples - 1 Functions - Examples - 2 Arrays in C Initializing arrays Initializing character arrays Pointers in C Pointer arithmetic Function with pointer arguments Example - copy a subarray Programming using arrays and pointers Sizeof operator Returning pointers from functions Example - return duplicate of a string Recursion - Linear Recursion Recursion - Linear Recursion - 2 Recursion - Two-way Recursion Multidimensional Arrays Multidimensional Arrays and Pointers Multidimensional Arrays and Pointers - continued (2) Multidimensional Arrays and Pointers - continued (3) File Handling Some other file-handling functions Structures in C - 1 Structures in C - 2 Singly Linked Lists Doubly Linked Lists - introduction Organizing code into multiple files - 1 Organizing code into multiple files - 2 Pre and post increment
106104135	Computer Science and Engineering	NOC:Fundamentals of Database Systems(Course sponsored by Aricent)	Dr. Arnab Bhattacharya	Video	IIT Kanpur	Select Introduction to Databases Relational Data Model Relational Algebra Basic Operators Relational Algebra Composition of Operators Relational Algebra Additional Operators Relational Algebra Extended Relational Algebra Relational Algebra: Database Modifications SQL: Introduction and Data Definition SQL: Basic Queries SQL: Advanced Queries SQL: Updates, Joins, Views and Triggers Normalization Theory: Motivation Normalization Theory: 1 NF and 2NF Normalization Theory: 3NF Normalization Theory: BCNF Normalization Theory: MVD Physical Design Database Indexing: Hashing Database Indexing: Tree-based Indexing Query Processing: Selection Query Processing: Sorting Query Processing: Nested-Loop joins and Merge join Query Processing: Hash join and other Operations Query Optimization: Equivalent Expressions and Simple Equivalance Rules Query Optimization: Complex Equivalence Rules Query Optimization: Join Order Query Optimization: Heuristics and Sizes Database Transactions: Properties and Failures Database Transactions: States and Systems Recovery Systems: Deferred Database Modification Recovery Systems: Immediate Database Modification. Recovery Systems: Checkpointing and Shadow Paging Schedules: Introduction Schedules: Conflict Serializability Schedules: View Serializability Schedules: Result Equivalence and Testing for Serializability Schedules: Recoverability Concurrency Control: Locks Concurrency Control: Two-phase Locking Protocol Concurrency Control: Timestamp Ordering Protocol Concurrency Control: Validation-based Protocol Concurrency Control: Multiple Granularity for Locks Concurrency Control: Deadlock Prevention and Deadlock Detection Concurrency Control: Deadlock Recovery and Update Operations NoSQL: Introduction and Properties NoSQL: Columnar Families NoSQL: Different NoSQL Systems Big Data
106104148	Computer Science and Engineering	NOC:Theory of Computation	Prof. Raghunath Tewari	Video	IIT Kanpur	Select Examples of non- CFLs Non-CFLs, pumping lemma Deterministic Context Free Languages Turing Machine More on Turing Machine Pushdown Automata - Examples and Relation with CFGs Pushdown Automata - Definition and Example Closure Properties of CFLs Introduction to CFGs DFA minimization Equivalence of NFA and DFA, Closure properties Regular expressions Algebraic properties, RE to NFA conversion GNFA to RE conversion More closure properties of regular languages Non-regular languages and pumping lemma Examples of CFGs, Reg subset of CFL Pushdown Automata Basic Notation and Convention, DFA Edit Lesson Introduction to Finite Automata Normal forms, Chomsky normal form Parse tree, derivation, ambiguity Examples of non-regular languages More on Undecidability Applications of Reduction Example of DFAs Non deterministic Turing Machine Edit Lesson Configuration Graphs Closure Properties of Decidable and Turing recognizable languages Decidability properties of Regular and Context Free Languages Undecidability NFA, definition and examples Introduction to Nondeterminism Reduction Rice's theorem Introduction to Computational Complexity Theory More on the class NP NP-Completeness Computation by DFA and Regular operation More on NP-Completeness
106104149	Computer Science and Engineering	NOC:Modern Algebra	Prof. Manindra Agrawal	Video	IIT Kanpur	Select Lecture 15 - Cauchy sequences and real numbers Lecture 14 - Fields Lecture 13 - Rings: Quotient Rings Lecture 12 - Rings: Dedekind Domains Lecture 11 - Rings: Special Ideals Lecture 10 - Rings: Ideal Arithmetic Lecture 3 - Groups: Isomorphism Lecture 16 - Properties of Fields Lecture 8 - Rings: Failure of Unique Factorization Lecture 9 - Rings: Birth of Ideals Lecture 7 - Rings: Introduction Lecture 6 - Groups: Applications Lecture 5 - Groups: Structure Theorem Lecture 4 - Groups: Quotienting Lecture 2 - Groups: Subgroups and homomorphism Lecture 17 - Finite Fields Lecture 1 - Groups: Introduction to abstraction Lecture 18 - Application of Fields
106105031	Computer Science and Engineering	Cryptography and Network Security	Dr. Debdeep Mukhopadhyay	Video	IIT Kharagpur	Select Introduction Overview on Modern Cryptography Introduction to Number Theory Probability and Information Theory Classical Cryptosystems Cryptanalysis of Classical Ciphers Shannons Theory Shannons Theory (Contd...1) Shannons Theory (Contd...2) Symmetric Key Ciphers Block Cipher Standards (DES) Block Cipher Standards (AES) Block Cipher Standards (AES) (Contd.) Linear Cryptanalysis Differential Cryptanalysis Few other Cryptanalytic Techniques Overview on S-Box Design Principles Modes of Operation of Block Ciphers Stream Ciphers Stream Ciphers (Contd...1) Stream Ciphers (Contd...2) Pseudorandomness Cryptographic Hash Functions Cryptographic Hash Functions (Contd...1) Cryptographic Hash Functions (Contd...2) Message Authentication Codes More Number Theoretic Results The RSA Cryptosystem Primality Testing Factoring Algorithms Some Comments on the Security of RSA Discrete Logarithm Problem (DLP) The Diffie-Hellman Problem and Security of ElGamal Systems An Introduction to Elliptic Curve Cryptography Application of Elliptic Curves to Cryptography Implementation of Elliptic Curve Cryptography Secret Sharing Schemes A Tutorial on Network Protocols System Security Firewalls and Intrusion Detection Systems Side Channel Analysis of Cryptographic Implementations
106105032	Computer Science and Engineering	Digital Image Processing	Dr. G. Harit	Web	IIT Kharagpur	Select Introduction Introduction (Contd.) Introduction (Contd.) Spatial Domain Filtering Spatial Domain Filtering (Contd) Spatial Domain Filtering (Continued) Spatial Domain Filtering (Contd.) Spatial Domain Filtering (Contd.) Filtering in the Frequency Domain Filtering in the Frequency Domain(Contd.) Filtering in the Frequency Domain (Contd.) Filtering in the Frequency Domain (Contd.) Filtering in the Frequency Domain (Contd.) Filtering in the Frequency Domain (Contd.) Image Restoration Image Restoration (Contd.) Image Restoration(Contd.) Image Restoration (Contd.) Image Restoration (Contd.) Image Compression Image Compression (Contd.) Image Compression(Contd.) Image Compression (Contd.) Image Compression (Contd.) Image Compression (Contd.) Image Compression (Contd. ) Image Compression ( Contd.) Wavelet based Image Compression Wavelet based Image Compression (Contd.) Wavelet based Image Compression (Contd.) Morphological Image Processing Morphological Image Processing (Contd.) Morphological Image Processing (Contd. ) Morphological Image Processing ( Contd. ) Morphological Image Processing (Contd.) Image Segmentation Image Segmentation (Contd.) Image Segmentation (Contd.) Image Segmentation (Contd.) Image Segmentation (Contd .) Image Segmentation(Contd.)
106105033	Computer Science and Engineering	High Performance Computer Architecture	Prof. Ajit Pal	Video	IIT Kharagpur	Select Introduction and Course Outline Performance Instruction Set Architecture MIPS ISA Processor MIPS ISA Processor (Contd.) Pipelining Introduction Instruction Pipelining Pipeline Hazards Data Hazards Software Pipelining In Quest of Higher ILP In Quest of Higher ILP (Contd.) Dynamic Instruction Scheduling Dynamic Instruction Scheduling (Contd.) Control Hazards Branch Prediction Branch Prediction (Contd.) Dynamic Instruction Scheduling with Branch Prediction Hardware Based Speculation Tutorial - I Hierarchical Memory Organization Hierarchical Memory Organization (Contd.) Hierarchical Memory Organization (Contd.) Hierarchical Memory Organization (Contd.) Cache Optimization Techniques (Contd.) Cache Optimization Techniques (Contd.) Main Memory Organization Main Memory Optimizations Virtual Memory Virtual Memory (Contd.) Virtual Machines Storage Technology Storage Technology (Contd.) Case Studies Case Studies (Contd.) Case Studies (Contd.) Multithreading and Multiprocessing Simultanoues Multithreading Symmetric Multiprocessors Distributed Memory Multiprocessors Cluster, Grid and Cloud Computing
106105034	Computer Science and Engineering	Low Power VLSI Circuits & Systems	Prof. Ajit Pal	Video	IIT Kharagpur	Select Introduction & Course Outline MOS Transistors - I MOS Transistors - II MOS Transistors - III MOS Transistors - IV MOS Inverters - I MOS Inverters - II MOS Inverters - III MOS Inverters - IV Static CMOS Circuits - I Static CMOS Circuits -II MOS Dynamic Circuits -I MOS Dynamic Circuits -II Pass Transistor Logic Circuits - I Pass Transistor Logic Circuits - II MOS Memories Finite State Machines Switching Power Dissipation Tutorial - I Dynamic Power Dissipation Leakage Power Dissipation Supply Voltage Scaling - I Supply Voltage Scaling - II Supply Voltage Scaling - III Supply Voltage Scaling - IV Tutorial - II Minimizing Switched Capacitance - I Minimizing Switched Capacitance - II Minimizing Switched Capacitance - III Minimizing Switched Capacitance - IV Minimizing Switched Capacitance - V Minimizing Leakage Power - I Minimizing Leakage Power - II Minimizing Leakage Power - III Variation Tolerant Design Adiabatic Logic Circuits Battery-Driven System Design CAD Tools for Low Power Tutorial - III Course Summary
106105036	Computer Science and Engineering	Real Time Systems	Prof. Rajib Mall	Video	IIT Kharagpur	Select Introduction Real - Time System Characteristics Few Basic Issues Modelling Timing Constraints Modelling Timing Constraints (Contd.) Basics of Real - Time Task Scheduling Cyclic Scheduler Event - Driven Scheduling Rate Monotonic Scheduler RMA Scheduling : Further Issues Deadline Monotonic Scheduling and Other Issues Few Issues in Use of RMA Resource Sharing Among Real-Time Tasks Highest Locker and Priority Ceiling Protocols An Analysis of Priority Ceiling Protocol Handling Task Dependencies Real-Time Task Scheduling on Multiprocessors and Distributed Systems Real-Time Task Scheduling on Multiprocessors and Distributed Systems (Contd.) Clock Synchronization in Distributed Real-Time Systems Internal Clock Synchronization in Presence of Byzantine Clocks A Few Basic Issues in Real-Time Operating Systems Tutorial - I A Few Basic Issues in Real-Time Operating Systems (Contd.) Unix and Windows as RTOS Real - Time POSIX Real - Time POSIX (Contd.) Open Source and Commercial RTOS Open Source and Commercial RTOS (Contd.) Benchmarking Real - Time Computer & Operating Systems Benchmarking Real - Time Computer & Operating Systems (Contd.) Real - Time Communications Few Basic Issues in Real - Time Communications Review of Computer Networking Real - Time Communication in a LAN Real - Time Communication in a LAN (Contd.) Performance of Two Real -Time Communication Protocols Real - Time Communication over Packet Switched Networks Real - Time Communication over Packet Switched Networks (Contd.) Real - Time Communication over Packet Switched Networks (Contd.) Real - Time Databases
106105077	Computer Science and Engineering	Artificial Intelligence	Prof. Anupam Basu	Video	IIT Kharagpur	Select Introduction to Artificial Intelligence Intelligent Agents State Space Search Uninformed Search Informed Search Informed Search - 2 Two Players Games - I Two Players Games - II Constraint Satisfaction Problems - 1 Constraint Satisfaction Problems 2 Knowledge Representation and Logic Interface in Propositional Logic First Order Logic Reasoning Using First Order Logic Resolution in FOPL Rule Based System Rule Based Systems II Semantic Net Reasoning in Semantic Net Frames Planning - 1 Planning - 2 Planning - 3 Planning - 4 Rule Based Expert System Reasoning with Uncertainty - I Reasoning with Uncertainty - II Reasoning with Uncertainty III Reasoning with Uncertainty - IV Fuzzy Reasoning - I Fuzzy Reasoning - II Introduction to Learning - I Introduction to Learning - II Rule Induction and Decision Trees - I Rule Induction and Decision Trees - II Learning Using neural Networks - I Learning Using Neural Networks - II Probabilistic Learning Natural Language Processing - I Natural Language Processing II
106105078	Computer Science and Engineering	Artificial Intelligence	Prof. S. Sarkar	Web	IIT Kharagpur	Select Introduction to AI Introduction to Agent Introduction to State Space Search Version two Uninformed Search Informed Search Strategies-I Informed Search Strategies-II Adversarial Search Two agent games : alpha beta pruning Constraint satisfaction problems - I Constraint satisfaction problems - II Propositional Logic Propositional Logic inference rules First Order Logic - I First Order Logic - II Inference in FOL - I Inference in FOL - II Rule based Systems - I Rule based Systems - II Semantic nets Frames - I Frames II Logic based planning Planning systems Planning algorithm - I Planning algorithm - II Reasoning with Uncertain information Probabilistic Inference Bayes Networks A Basic Idea of Inferencing with Bayes Networks Other Paradigms of Uncertain Reasoning Fuzzy Set Representation Fuzzy Reasoning - Continued Learning : Introduction Learning From Observations Rule Induction and Decision Tree - I Rule Induction and Decision Tree - II Learning and Neural Networks - I Neural Networks - II Neural Networks - III Issues in NLP Parsing
106105079	Computer Science and Engineering	Artificial Intelligence(Prof.P.Dasgupta)	Prof. P. Dasgupta	Video	IIT Kharagpur	Select Introduction to Artificial Intelligence Problem Solving by Search Searching with Costs Informed State Space Search Heuristic Search: A* and Beyond Problem Reduction Search: AND/OR Graphs Searching Game Trees Knowledge Based Systems: Logic and Deduction First Order Logic Inference in First Order Logic Resolution - Refutation Proofs Resolution Refutation Proofs Logic Programming : Prolog Prolog Programming Prolog: Exercising Control Additional Topics Introduction to Planning Partial Order Planning GraphPLAN and SATPlan SATPlan Reasoning under uncertainty Bayesian Networks Reasoning with Bayes Networks Reasoning with Bayes networks (Contd.) Reasoning under uncertainty: Issues Learning : Decision Trees Learning : Neural Networks Back Propagation Learning
106105080	Computer Science and Engineering	Computer Networks	Prof. Ajit Pal	Web	IIT Kharagpur	Select Introduction and Course Outline Layered Network Architecture Data and Signal Transmission Media Transmission Impairments and Channel Capacity Transmission of Digital Signal Analog Data to Analog Signal Digital Data, Analog Signals Multiplexing of Signals Interfacing to the media and synchronization Error Detection and Correction Flow Control and Error Control HDLC Switching Techniques: Circuit Switching Switching Techniques: Circuit Switching Synchronous Optical Network (SONET) X.25 Frame Relay Asynchronous Transfer Mode Switching (ATM) Network Topology Medium Access Control (MAC) Techniques IEEE CSMS/CD based LANs IEEE Ring LANs High Speed LANs ? Token Ring Based High Speed LANs ? CSMA/CD based Wireless LANs Bluetooth Cellular Telephone Networks Satellite Networks Internetworking Devices Internet Protocol (IP) Transport and Application Layer Protocols Basics of Routing RIP ? Routing Information Protocol Open Shortest Path First (OSPF) Border Gateway Protocol (BGP) Congestion Control Cryptography Secured Communication Firewalls
106105081	Computer Science and Engineering	Computer Networks	Prof. Sujoy Ghosh	Video	IIT Kharagpur	Select Emergence of Networks & Reference Models Network Topology Physical Medium - I Physical Medium - II Multiplexing (Sharing a Medium) Telecom Networks Switches - I Pocket Switches SONET/SDH Fiber Optic Components Routing and Wavelength Assignment Protection and Restoration Multiple Access Token Based Mac Data Link Protocols Error Control Stop & Wait Protocol Satellite Communication Ethernet - CSMA/CD Modern Ethernet Local Internetworking Cellular Networks Wireless Network ATM : Asynchronous Transfer Mode ATM Signaling, Routing and LAN Emulation Introduction to Routing RIP - Distance Vector Routing IP version 4 IP Version 6 & Mobile IP UDP & Client Server TCP IP Multicasting DHCP and ICMP DNS & Directory Congestion Control QOS & Multimedia Network Management Security FTP - SMTP HTTP
106105082	Computer Science and Engineering	Data Communication	Prof. Ajit Pal	Video	IIT Kharagpur	Select Introduction and Course Outline - Data Communication Layered Architecture Data and Signal Transmission Impairments and Channel Capacity Guided Transmission Media Unguided Media Transmission of Digital Signal - I Transmission of Digital Signal - II Transmission of Analog Signal - I Transmission of Analog Signal - II Multiplexing Multiplexing Multiplexing Applications - I Multiplexing Applications - II Interfacing to the Media Error Detection and Correction Flow and Error Control Data Link Control Switching Techniques Circuit Switching Switching Techniques Packet Switching Routing - I Routing - II Congestion Control X.25 and Frame Relay ATM Medium Access Control - I Medium Access Control - II Medium Access Control - III IEEE 802 LANs High Speed LANs Wireless LANs Cellular Telephone Systems Satellite Communications Internet and Internetworking TCP/IP - I TCP/IP - II Multimedia Networks Audio and Video Compression Multimedia Services Secured Communication - I Secured Communication - II
106105083	Computer Science and Engineering	Electronic Design Automation	Prof. Indranil Sengupta	Video	IIT Kharagpur	Select Introduction Verilog: Part - I Verilog: Part - II Verilog: Part - III Verilog: Part - IV Verilog: Part - V Verilog: Part - VI Synthesis: Part - I Synthesis: Part - II Synthesis: Part - III Synthesis: Part - IV Synthesis: Part - V Synthesis: Part - VI Synthesis: Part - VII Backend Design: Part - I Backend Design: Part - II Backend Design: Part - III Backend Design: Part - IV Backend Design Part - V Backend Design Part - VI Backend Design Part - VII Backend Design Part - VIII Backend Design Part - IX Backend Design Part - X Backend Design Part - XI Backend Design Part - XII Backend Design Part - XIII Backend Design Part - XIV Backend Design Part - XV Testing Part - I Testing Part - II Testing Part - III Testing Part - IV Testing Part - V Testing Part - VI
106105084	Computer Science and Engineering	Internet Technology	Prof. Indranil Sengupta	Video	IIT Kharagpur	Select Introduction To Internet Review Of Network Technologies TCP/IP - Part-1 TCP/IP-Part-II TCP/IP-Part-III IP Subnetting and Addressing Internet Routing Protocol Part -I Internet Routing Protocol- Part-II Client Server Concepts DNS,Telnet,Ftp Electronic Mail World Wide Web Part-I World Wide Web - Part-II HTML-Part-I HTML-Part-II HTML-Part-III Extensible Markup Language (XML) Html Forms Image Maps CGI Scripts Other Technologies PERL Part-I PERL - Part II PERL-Part III PERL-Part IV Javascript -Part :I Javascript Examples (Continued) Using Cookies Java Applets -Part:I Java Applets - Part:2 Client-Server Programming In Java Intranet, Extranet,Firewall Basic Cryptographic Concepts Part - I Basic Cryptographic Concepts Part - II Basic Cryptographic Concepts Part - III Electronic Commerce Streaming Multimedia Applications Internet Telephony Search Engine And Web Crawler - Part-I Search Engine And Web Crawlers: Part-II Course Summary And Conclusion
106105085	Computer Science and Engineering	Programming and Data Structure	Dr. P.P.Chakraborty	Video	IIT Kharagpur	Select Introduction C Programming - I C Programming - II C Programming - III Data Structuring: Case Study - I Data Structuring: Case Study - II Data Structuring: Case Study - III Problem Decomposition By Recursion - I Problem Decomposition By Recursion - II Problem Decomposition By Recursion - III Merge sort And Quick sort Characters And Strings Arrays: Addresses And Contents Structures - I Structures - II Dynamic Allocation Part - I Linked Lists - I Complexity (Efficiency) of Algorithms Asymptotic Growth Functions Asymptotic Analysis of Algorithms Data Structuring Search Trees Search Trees - II Search Trees - III 2-3 Trees Algorithm Design - I Algorithm Design - II Algorithm Design - III Graphs - I Graphs - II Graphs - III Conclusions
106105086	Computer Science and Engineering	Real Time Systems	Prof. Rajib Mall	Web	IIT Kharagpur	Select Introduction Real-Time Task Scheduling Handling Resource Sharing and Dependencies Among Real-Time Tasks Scheduling Real-Time Tasks in Multiprocessor and Distributed Systems Commercial Real-Time Operating Systems Real-Time Communication Real-Time Databases
106105087	Computer Science and Engineering	Software Engineering	Prof. Rajib Mall	Web	IIT Kharagpur	Select Basic Issues in Software Engineering Structured Programming Basics of Software Life Cycle and Waterfall Model Prototyping and Spiral Life Cycle Models Basic concepts in Requirements Analysis and Specification Formal Requirements Specification Algebraic Specification Basic Concepts in Software Design An Overview of Current Design Approaches Data Flow Diagrams DFD Model of a System Structured Design Structured Design Basic Ideas on UML Use Case Model Class and Interaction diagrams Activity and State Chart Diagram Design Patterns Domain Modeling Basic Concepts in User Interface Design Types of User Interfaces Component-Based GUI Development Code Review Black-Box Testing White-Box Testing Debugging, Integration and System Testing Project Planning and Project Estimation Techniques COCOMO Model Staffing Level Estimation and Scheduling Organization and Team Structures Risk Management and Software Configuration Management Software Reliability Issues Statistical Testing and Software Quality Management ISO 9000 SEI CMM Characteristics of Software Maintenance Basic Ideas on CASE Tools Different Characteristics of CASE Tools Basic Ideas on Software Reuse Reuse Approach Basic Ideas on Client-Server Software Development and Client-Server Architecture CORBA and COM/DCOM
106105150	Computer Science and Engineering	NOC:Software Testing	Prof. Rajib Mall	Video	IIT Kharagpur	Select Lecture 04 : Basic Concepts in Testing (Contd.) Lecture 05 : Unit Testing Lecture 14: Dataflow and Mutation Testing Lecture 13: Path Testing Lecture 6: Equivalence and BV Testing Lecture 7: Special Value Testing Lecture 8: Combinatorial Testing Lecture 9: Pairwise Testing Lecture 10: White Box Testing Lecture 11: MC/DC Testing Lecture 12: MC/DC Testing (Contd.) Lecture 02 : Levels of Testing Lecture 01 : Introduction Lecture 15: Mutation Testing Lecture 16: Integration Testing Lecture 17: System Testing Lecture 18: Regression Testing Lecture 19: Testing Object-Oriented Program - Part 1 Lecture 20: Testing Object-Oriented Program - Part 2 Lecture 03 : Basic Concepts in Testing
106105151	Computer Science and Engineering	NOC:Programming in C++	Prof. Partha Pratim Das	Video	IIT Kharagpur	Select Module 40 : Closing Comments (Lecture 56) Module 28 : Dynamic Binding (Polymorphism) : Part III (Lecture 43) Module 29 : Dynamic Binding (Polymorphism) Part IV (Lecture 44) Module 30 : Dynamic Binding (Polymorphism) : Part V (Lecture 45) Module 31: Virtual Function Table (Lecture 46) Module 32: Type casting and cast operators : Part I (Lecture 47) Module 33: Type casting and cast operators : Part II (Lecture 48) Module 34: Type casting and cast operators : Part III (Lecture 49) Module 16: Static Members (Lecture 31) Module 17: friend Function and friend Class (Lecture 32) Module 18: Overloading Operator for User Defined Types: Part - I (Lecture 33) Module 19: Overloading Operator for User Defined Types: Part - II (Lecture 34) Module 20: Namespace (Lecture 35) Module 21: Inheirtnace : Part I (Lecture 36) Module 22: Inheritance : Part II (Lecture 37) Module 23: Inheritance : Part III (Lecture 38) Module 24: Inheritance : Part IV (Lecture 39) Module 25: Inheritance : Part V (Lecture 40) Module 26 : Dynamic Binding : Part I (Lecture 41) Module 27: Dynamic Binding (Polymorphism) : Part II (Lecture 42) Module 01: Recap of C (Lecture 02) Module 02: Programs with IO and Loop (Lecture 04) Module 01: Recap of C (Lecture -03) Module 06: Constants and Inline Functions(Lecture 08) Module 05: Stack and its Applications (Lecture 07) Module 06: Constants and Inline Functions (Contd.) (Lecture 09) Module 07 : Reference and Pointer ( Lecture 10) Module 07: Reference and Pointer (Contd.) ( Lecture 11) Module 08: Default Parameters and Function Overloading (Contd.) (Lecture 13) Module 09: Operator Overloading (Contd.) (Lecture 16) Module 10: Dynamic Memory Management (Lecture 17) Module 10: Dynamic Memory Management (Contd.) (Lecture 18) Module 38 : Template (Function Template) : Part I (Lecture 54) Module 14: Copy Constructor and Copy Assignment Operator (Contd.) (Lecture 27) Module 14: Copy Constructor and Copy Assignment Operator (Contd.) (Lecture 28) Module 15: Const-ness (Lecture 29) Module 15 : Const-ness (Contd.) (Lecture 30) Module 13: Constructors, Destructors and Object Lifetime (Contd.) (Lecture 25) Module 14: Copy Constructor and Copy Assignment Operator (Lecture 26) Module 1: Recap of C (Lecture 01) Module 35: Multiple Inheritance (Lecture 50) Module 39 : Template (Function Template) : Part II (Lecture 55) Module 37 : Exceptions (Error Handling in C) : Part II (Lecture 53) Module 36: Exceptions (Error Handling in C) : Part I (Lecture 52) Module 35: Multiple Inheritance (Contd.) (Lecture 51) Module 09: Operator Overloading (lecture 15) Module 08: Default Parameters and Function Overloading (Contd.) (Lecture 14) Module 08: Default Parameters and Function Overloading (Lecture 12) Module 03: Arrays and Strings (Lecture 05) Module 04 : Sorting and Searching (Lecture 06) Module 11: Classes and Objects (Lecture 19) Module 11 Classes and Objects (Contd.) (Lecture 20) Module 12: Access Specifiers (Lecture 21) Module 12 : Access Specifiers (Contd.) (lecture 22) Module 13 : Constructors, Destructors and Object Lifetime (Lecture 23) Module 13: Constructors, Destructors and Object Lifetime (Contd.) (Lecture 24)
106105152	Computer Science and Engineering	NOC:Introduction to Machine Learning	Prof. S. Sarkar	Video	IIT Kharagpur	Select Lecture 18: Bayesian Learning Lecture 17: Tutorial III Lecture 16: Python Exercise on kNN and PCA Lecture 15: Collaborative Filtering Lecture 14: Feature Extraction Lecture 13: Feature Selection Lecture 24: Introduction Support Vector Machine Lecture 25: SVM : The Dual Formulation Lecture 04: Evaluation and Cross-Validation Lecture 37: Sample Complexity : Finite Hypothesis Space Lecture 26: SVM : Maximum Margin with Noise Lecture 28: SVM : Solution to the Dual Problem Lecture 29: Python Exercise on SVM Lecture 30: Introduction Lecture 31: Multilayer Neural Network Lecture 32 : Neural Network and Backpropagation Algorithm Lecture 03: Hypothesis Space and Inductive Bias Lecture 33: Deep Neural Network Lecture 27: Nonlinear SVM and Kernel Function Lecture 22: Tutorial IV Lecture 21: Python Exercise on Naive Bayes Lecture 20 : Bayesian Network Lecture 19: Naive Bayes Lecture 12: k-Nearest Neighbour Lecture 36: Introduction to Computational Learning Theory Lecture 34: Python Exercise on Neural Network Lecture 35: Tutorial VI Lecture 38: VC Dimension Lecture 02: Different Types of Learning Lecture 23 : Logistic Regression Lecture 44: Python Exercise on kmeans clustering Lecture 39 : Introduction to Ensembles Lecture 40 : Bagging and Boosting Lecture 41 : Introduction to Clustering Lecture 42 : Kmeans Clustering Lecture 43: Agglomerative Hierarchical Clustering Tutorial I Tutorial II Lecture 9: Python Exercise on Decision Tree and Linear Regression Lecture 08 : Overfitting Lecture 05 : Linear Regression Lecture 06 : Introduction to Decision Trees Lecture 07 : Learning Decision Tree Lecture 01: Introduction
106105153	Computer Science and Engineering	NOC:Object-Oriented Analysis and Design	Prof. Partha Pratim Das	Video	IIT Kharagpur	Select Module 37 : State Machine Diagrams : Part II (Lecture 49) Module 36 : State Machine Diagrams : Part I (Lecture 48) Lecture 29: Identification of Classes, Objects and Relationship in LMS Lecture 04: Structure and Attributes of a Complex System Lecture 03: Complexity of Software (Contd.) Lecture 02 : Complexity of Software Module 29: Sequence Diagrams : Part 1 (Lecture 41) Module 08: Elements of Object Model (Major) : Abstraction and Encapsulation (Lecture 12) Module 15: How to Build Quality Classes and Objects (Lecture 26) Lecture 27: Tutorial : LMS Lecture 28: How to Identify Classes and Objects ? Module 13: Nature of a class : Interface and Implementation (Contd.) (Lecture 23) Module 14: Relationships among classes (Lecture 24) Module 14: Relationships among classes (Contd.) (Lecture 25) Module 12: Relationships among objects (Lecture 20) Module 12: Relationships among objects (Contd.) (Lecture 21) Module 13: Nature of a class: Interface and Implementation (Lecture 22) Module 11: Nature of an object : State, Behavior and Identity (Lecture 18) Module 11: Nature of an object: State, Behavior and Identity (Contd.) (Lecture 19) Module 10: Elements of the Object Model (Minor) : Typing, Concurrency and Persistence (Contd.) (Lecture 17) Module 10: Elements of the Object Model (Minor) : Typing, Concurrency and Persistence (Lecture 16) Module 09: Elements of the Object Model (Major) : Modularity and Hierarchy (Contd.) (Lecture 15) Module 08: Elements of Object Model (Major) : Abstraction and Encapsulation (Contd.)(Lecture 13) Lecture 05: Structure and Attributes of a Complex System (Contd.) Module 07: Foundations of the Object Model - OOA, OOD and OOP (Contd.) (Lecture 11) Module 25: Use-Case Diagrams : Part III (Lecture 37) Module 21: Overview of UML (Lecture 33) Module 22: SDLC Phases and UML Diagrams (Lecture 34) Module 23: Use-Case Diagrams : Part I (Lecture 35) Module 24: Use-Case Diagrams : Part II (Lecture 36) Lecture 32: Identification of Classes, Objects and Relationship in LMS (Contd.) Lecture 30: Identification of Classes, Objects and Relationship in LMS (Contd.) Module 26: Class Diagrams : Part 1 (Class, Property and Operation) (Lecture 38) Module 27 : Class Diagrams : Part 2 (Association, Weak and Strong Aggregation) (Lecture 39) Module 28: Class Diagrams : Part 3 (Generalization, Dependency and Constraints) (Lecture 40) Lecture 31: Identification of Classes, Objects and Relationship in LMS (Contd.) Module 35: Interaction Overview Diagram (Lecture 47) Module 34: Activity Diagrams : Part III (Lecture 46) Module 33: Activity Diagrams : Part II (Lecture 45) Module 32: Activity Diagrams : Part II (Lecture 44) Module 31 : Communication Diagram (Lecture 43) Module 30 : Sequence Diagrams : Part 2 (Lecture 42) Module 07: Foundations of the Object Model - OOA, OOD and OOP (Lecture 10) Module 09: Elements of the Object Model (Major) : Modularity and Hierarchy (Lecture 14) Module 06: Evolution of Object Models - Programming Languages and Paradigms (Lecture 09) Lecture 08: Bringing Order to Chaos (Contd.) Lecture 07 : Bringing Order to Chaos Lecture 06: Object-Oriented Analysis and Design Lecture 01: Challanges in Software Engineering Module 38 : State Machine Diagrams : Part III (Lecture 50) Module 39 : Various UML Diagrams (Lecture 51) Module 40 : Closing Comments (Lecture 52)
106105154	Computer Science and Engineering	NOC:Complex Network : Theory and Application	Prof. Animesh Mukherjee	Video	IIT Kharagpur	Select Lecture 20: Citation Analysis - III Lecture 21: Citation Analysis - IV Lecture 19: Citation Analysis - II Lecture 18: Citation Analysis - I Lecture 17: Community Analysis - VI Lecture 16: Community Analysis - V Lecture 15: Community Analysis - IV Lecture 14: Community Analysis - III Lecture 13: Community Analysis - II Lecture 12: Community Analysis - I Lecture 11: Social Network Principles - IV Lecture 10: Social Network Principles - III Lecture 9: Social Network Principles - II Lecture 8: Social Network Principles - I Lecture 7: Network Analysis - VI Lecture 6: Network Analysis - V Lecture 5: Network Analysis - IV Lecture 4: Network Analysis - III Lecture 3: Network Analysis - II Lecture 2: Network Analysis - I Lecture 1: Introduction
106105157	Computer Science and Engineering	Fundamental Algorithms:Design and Analysis	Prof.Sourav Mukhopadhyay	Video	IIT Kharagpur	Select Lecture 08: Order Statistics Lecture 12: Augmenting Data Structure Lecture 11: Red-Black Tree Lecture 10: Universal Hashing, BST Sort Lecture 09: Hashing Lecture 14: Van Emde Boas Data Structure Lecture 15: Dynamic Programming Lecture 16 : Graph Algorithm Lecture 05 : Heap Sort Lecture 06: Decision Tree Lecture 07: Linear Time Sorting Lecture 17 : BFS and DFS Lecture13: Computational Geometry Lecture 04: Quick Sort Lecture 03: Divide and Conquer Paradigm Lecture 02: Solving Recurrences Lecture 01 : Insertion Sort and Asymptotic Analysis Lecture 18 : Dijkstra Lecture 19 : Bellman Ford Lecture 20 : Floyd Marshall
106105158	Computer Science and Engineering	NOC:Natural Language Processing	Prof. Pawan Goyal	Video	IIT Kharagpur	Select Lecture 44 : Gibbs Sampling for LDA, Applications Lecture 45 : LDA Variants and Applications - I Lecture 28 : Transition Based Parsing : Formulation Lecture 29 : Transition Based Parsing : Learning Lecture 30 : MST-Based Dependency Parsing Lecture 22: Syntax - Introduction Lecture 24: Syntax - CKY, PCFGs Lecture 25: PCFGs - Inside-Outside Probabilities Lecture 26: Inside-Outside Probabilities Lecture 49 : Information Extraction - Introduction Lecture 50 : Relation Extraction Lecture 41 : Novel Word Sense detection Lecture 42 : Topic Models : Introduction Lecture 43 :Latent Dirichlet Allocation : Formulation Lecture 4: Empirical Laws Lecture 5: Text Processing: Basics Lecture 6: Spelling Correction: Edit Distance Lecture 7: Weighted Edit Distance, Other Variations Lecture 64 : Computing with Affective Lexicons Lecture 65 : Aspect - Based Sentiment Analysis Lecture 48 : Entity Linking - II Lecture 39 : Word Sense Disambiguation - I Lecture 58 : Tutorial III Lecture 55 : Text Classification - I Lecture 56 : Text Classification - II Lecture 54 : Summarization Evaluation Lecture 53 : Optimization based Approaches for Summarization Lecture 52 : Text Summarization - LEXRANK Lecture 34: Distributional Semantics : Applications, Structured Models Lecture 63 : Learning Affective Lexicons Lecture 62 : Sentiment Analysis - Affective Lexicons Lecture 61 : Sentiment Analysis - Introduction Lecture 60 : Tutorial V Lecture 59 : Tutorial IV Lecture 57 : Tutorial II Lecture 47 : Entity Linking - I Lecture 40 : Word Sense Disambiguation - II Lecture 32: Distributional Semantics - Introduction Lecture 27: Dependency Grammars and Parsing - Introduction Lecture 15: Introduction to POS Tagging Lecture 1: Introduction to the Course Lecture 46:LDA Variants and Applications - II Lecture 16: Hidden Markov Models for POS Tagging Lecture 17: Viterbi Decoding for HMM, Parameter Learning Lecture 18: Baum Welch Algorithm Lecture 19: Maximum Entropy Models - I Lecture 20: Maximum Entropy Models - II Lecture 21: Conditional Random Fields Lecture 9 : N-Gram Language Models Lecture 10: Evaluation of Language Models, Basic Smoothing Lecture 11: Tutorial I Lecture 12: Language Modeling: Advanced Smoothing Models Lecture 13: Computational Morphology Lecture 14: Finite - State Methods for Morphology Lecture 38: Lexical Semantics - Wordnet Lecture 36 : Word Embeddings - Part II Lecture 31: MST-Based Dependency Parsing : Learning Lecture 35: Word Embeddings - Part I Lecture 33: Distributional Models of Semantics Lecture 8: Noisy Channel Model for Spelling Correction Lecture 2: What Do We Do in NLP Lecture 3: Why is NLP hard Lecture 23: Syntax - Parsing I Lecture 37: Lexical Semantics Lecture 51 : Distant Supervision
106105159	Computer Science and Engineering	NOC:Embedded Systems Design	Prof. Anupam Basu	Video	IIT Kharagpur	Select Lecture 30 : Priority Inversion and Priority Inheritance Protocol Lecture 49 : Formal Verification Lecture 48 : Simulation Lecture 46 : Optimization - I Lecture 44 : Digital Camera - Iterative Design Lecture 45 : HW-SW Partitioning Lecture 35 : Statecharts (Contd.) Lecture 36 : Program State Machines Lecture 2: Processors Lecture 3: General Purpose and ASIPs Processor Lecture 4: Designing a Single Purpose Processor Lecture 5: Optimization Issues Lecture 6: Introduction to FPFA Lecture 7: FPGA Contd. Lecture 8: Behaviour Synthesis on FPGA using VHDL Lecture 9: Tutorial - I Lecture 10: Tutorial - II Lecture 11: Tutorial - III Lecture 12: Tutorial - IV Lecture 13: Sensors and Signals Lecture 14: Discretization of Signals and A/D Converter Lecture 15: Quantization Noise, SNR and D/A Converter Lecture 16: Arduino Uno Lecture 17: Arduino Uno (Contd.), Serial Communication and Timer Lecture 41 : Hardware Synthesis - II Lecture 39 : Data Flow Model - II Lecture 40 : Hardware Synthesis - I Lecture 47 : Optimization - II Lecture 43 : Digital Camera Design Lecture 42 : Scheduling Lecture 34 : Statechart and Statemate Semantics Lecture 21: Power Aware Embedded System - II Lecture 18: Controller Design using Arduino Lecture 1: Introduction Lecture 23: Parallel Operations and VLIW Lecture 24: Code Efficiency Lecture 25: DSP Application and Address Generation Unit Lecture 26: Real Time O.S - I Lecture 22: SD and DD Algorithm Lecture 33 : FSM and Statechart Lecture 19: Tutorial - V Lecture 20:Power Aware Embedded System - I Lecture 29 : EDF Algorithm and Resource Constraint Issue Lecture 28: RMS Algorithm Lecture 37 : SDL Lecture 38 : Data Flow Model - I Lecture 27: Real Time O.S - II Lecture 31 : Modeling and Specification - I Lecture 32 : Modeling and Specification - II
106105160	Computer Science and Engineering	NOC:Wireless Ad Hoc and Sensor Networks	Prof. Sudip Misra	Video	IIT Kharagpur	Select Lecture 36 : Underwater Sensor Networks- Part- IV Lecture 35: Underwater Sensor Networks- Part- III Lecture 10: Routing in MANETs- Part- III Lecture 8: Routing in MANETs- Part- I Lecture 29: Routing in Wireless Sensor Networks- Part- I Lecture 30: Routing in Wireless Sensor Networks- Part- II Lecture 31: Congestion and Flow Control- Part- I Lecture 32: Congestion and Flow Control- Part- II Lecture 16: Opportunistic Mobile Networks- Part- II Lecture 17: Opportunistic Mobile Networks- Part- III Lecture 18: UAV Networks- Part- I Lecture 19: UAV Networks- Part- II Lecture 20: UAV Networks- Part- III Lecture 21: Introducation: Wireless Sensor Networks- Part- I Lecture 22: Introducation: Wireless Sensor Networks- Part- II Lecture 33: Underwater Sensor Networks- Part- I Lecture 27: Medium Access Control in Wireless Networks- Part-I Lecture 23: WSN Coverage & Placement- Part-I Lecture 24: Topology Mangement in Wireless Sensor Network Lecture 25: Mobile Wireless Sensor Networks Lecture 26: Mobile Wireless Sensor Networks Lecture 7: MAC Protocols in MANETs- Part- II Lecture 11: Multicasting in MANETs Lecture 12: Mobility Models for MANETs Lecture 13: Transport Protocols for MANETs- Part- I Lecture 14: Transport Protocols for MANETs- Part- II Lecture 15: Opportunistic Mobile Networks- Part- I Lecture 5: Cooperation in Mobile Ad Hoc Networks- Part- II Lecture 9: Routing in MANETs- Part- II Lecture 6: MAC Protocols in MANETs- Part- I Lecture 4: Cooperation in Mobile Ad Hoc Networks- Part- I Lecture 3: Self-organizing Behaviour of Wireless Ad Hoc Networks Lecture 2: Introduction: Wireless Ad Hoc Networks- Part- II Lecture 34: Underwater Sensor Networks- Part- II Lecture 28: Medium Access Control in Wireless Networks- Part-II Lecture 1: Introduction: Wireless Ad Hoc Networks- Part- I Lecture 37 : Security of Wireless Sensor Networks- Part- I Lecture 38 : Security of Wireless Sensor Networks- Part- II Lecture 39 : Hardware Design of Sensor Node Lecture 40 : Real Life Deployment of WSN
106105161	Computer Science and Engineering	NOC:VLSI Physical Design	Prof. Indranil Sengupta	Video	IIT Kharagpur	Select Lecture 41: Performance-Driven Design Flow Lecture 45 : Design Rule Check Lecture 46 : Layout Compaction (Part 1) Lecture 47 : Layout Compaction (Part 2) Lecture 48 : Lecture 8: Floorplanning Lecture 9: "Floorplanning Algorithms Lecture 15: Grid Routing (Part 1) Lecture 20 : Detailed Routing (Part 1) Lecture 21: Detailed Routing (Part 2) Lecture 22: Detailed Routing (Part 3) Lecture 63 : Algorithmic Level Techniques for Low Power Design Lecture 61 : Gate Level Design for Low Power (Part 2) Lecture 60 : Gate Level Design for Low Power (Part 1) Lecture 56: Built-in Self-Test (Part 1) Lecture 55: Boundary Scan Standard Lecture 54: Design for Testability Lecture 53 : Test Pattern Generation Lecture 52 : Lecture 35: Time Closure (Part 4) Lecture 51 : Lecture 43 :Interconnect Modeling (Part 1) Lecture 44 : Interconnect Modeling (Part 2) Lecture 27: CLOCK NETWORK SYNTHESIS (PART 1) Lecture 11: Placement (Part 1) Lecture 12: Placement (Part 2) Lecture 13: Placement (Part 3) Lecture 14: Placement (Part 4) Lecture 39: Physical Synthesis (Part 1) Lecture 40 : Physical Synthesis (Part 2) Lecture 25 : Clock Design (Part 2) Lecture 29: CLOCK NETWORK SYNTHESIS (PART 3) Lecture 64 : Summarization of the Course Lecture 37: Timing Driven Placement Lecture 36: Time Closure (Part 5) Lecture 34: Time Closure (Part 3) Lecture 32: Time Closure (Part 1) Lecture 31: POWER AND GROUND ROUTING Lecture 30: CLOCK NETWORK SYNTHESIS (PART 4) Lecture 33: Time Closure (Part 2) Lecture 28: CLOCK NETWORK SYNTHESIS (PART 2) Lecture 19: Global Routing (Part 2) Lecture 10: Pin Assignment Lecture 1: Introduction Lecture 2: Design Representation Lecture 3: VLSI Design Styles (Part 1) Lecture 4: VLSI Design Styles (Part 2) Lecture 5: VLSI Physical Design Automation (Part 1) Lecture 6: VLSI Physical Design Automation (Part 2) Lecture 7: Partitioning Lecture 49 : Lecture 38: Timing Driven Routing Lecture 50 : Lecture 59 : Techniques to Reduce Power Lecture 58 : Low Power VLSI Design Lecture 57: Built-in Self-Test (Part 2) Lecture 62 : Other Low Power Design Techniques Lecture 26 : Clock Design (Part 3) Lecture 24 : Clock Design (Part 1) Lecture 16: Grid Routing (Part 2) Lecture 17: Grid Routing (Part 3) Lecture 23 : Detailed Routing (Part 4) Lecture 18: Global Routing (Part 1) Lecture 42 : Miscellaneous Approaches to Timing Optimization
106105162	Computer Science and Engineering	NOC:Cryptography And Network Security	Prof. Sourav Mukhopadhyay	Video	IIT Kharagpur	Select Lecture 38 : Key Management. Lecture 45 : More on Key Exchange Protocol Lecture 22: Advanced Encryption Standard (AES) (Contd.) Lecture 23: Introduction to Public Key Cryptosystem, Diffie-Hellman Key Exchange. Lecture 24: Knapsack Cryptosystem. Lecture 25: RSA Cryptosystem Lecture 26: More on RSA Lecture 41 : Universal Hashing. Lecture 7: DES (Contd.). Lecture 8: Triple DES and Modes of Operation. Lecture 53 : Shamir's secret sharing and BE Lecture 51 : Cryptanalysis on Stream Cipher Lecture 50 : Linear Cryptanalysis Lecture 35: Jacobi Symbol (Contd.) Lecture 36: Message Authentication. Lecture 32: Chinese Remainder Theorem Lecture 47 : Time- Memory Trade- off Attack Lecture 43 : Secure Hash Algorithm (SHA). Lecture 42 : Cryptographic Hash Function Lecture 40 : Hash Function Lecture 44 : Digital Signature Standard (DSS) Lecture 34: Legendre and Jacobi Symbol Lecture 54 : Identity based Encryption (IBE) Lecture 55 : Attribute based Encryption (ABE) Lecture 10: Pseudorandom Sequence Lecture 11: LFSR based Stream Cipher Lecture 12: Mathematical background. Lecture 13: Abstract algebra (contd.) Lecture 14: Number Theory Lecture 15: Modular Inverse. Lecture 46 : Cryptanalysis Lecture 29: Elliptic Curve over the Reals Lecture 28: ElGamal Cryptosystem. Lecture 27: Primarily Testing Lecture 16: Modular Inverse Lecture 17: Extended Euclid Algorithm Lecture 18: Fermat's Little Theorem, Eular PhiFunction Lecture 19: Eular's theorem, Quadratic Residue Lecture 20: Polynomial Arithmetic. Lecture 21: Advanced Encryption Standard (AES) Lecture 3: Cryptanalysis on Substitution Cipher (Frequency Analysis ). Lecture 4: Play Fair Cipher. Lecture 5: Block Cipher Lecture 6: Data Encryption Standard (DES). Lecture 2: Classical Cryptosystem. Lecture 9: Stream Cipher. Lecture 52 : Modern Stream Ciphers Lecture 49 : More on Differential Cryptanalysis Lecture 48 : Time-Memory Trade-off Attack Lecture 39 : Key Exchange Lecture 37: Digital Signature. Lecture 33: Rabin Cryptosystem Lecture 31: Generalised ElGamal Public Key Cryptosystem Lecture 30: Elliptic curve Modulo a Prime. Lecture 1: Introduction to Cryptography. Lecture 56:Functional Encryption Lecture 57:Solving discrete log problem Lecture 58:Implementation Attacks Lecture 59:The Secure Sockets Layer Lecture 60:Pretty Good Privacy
106105163	Computer Science and Engineering	NOC:Computer architecture and organization	Prof. Indranil Sengupta	Video	IIT Kharagpur	Select Lecture 5 : Instruction Set Architecture Lecture 4 : Software and Architecture Types Lecture 3 : Memory Addressing and Languages Lecture 2 : Basic Operation of a Computer Lecture 1 : Evolution of Computer Systems Lecture 9 : MIPS32 Instruction Set Lecture 37 : DESIGN OF DIVIDERS Lecture 36 : DESIGN OF MULTIPLIERS (PART 2) Lecture 35 : DESIGN OF MULTIPLIERS (PART 1) Lecture 34 : DESIGN OF ADDERS (PART 2) Lecture 33 : DESIGN OF ADDERS (PART 1) Lecture 32 : IMPROVING CACHE PERFORMANCE Lecture 31 : CACHE MEMORY (PART 2) Lecture 30 : CACHE MEMORY (PART 1) Lecture 29 : MEMORY HIERARCHY DESIGN (PART 2) Lecture 28 : MEMORY HIERARCHY DESIGN (PART 1) Lecture 25 : ASYNCHRONOUS DRAM Lecture 21 : MIPS IMPLEMENTATION (PART 1) Lecture 19 : DESIGN OF CONTROL UNIT (PART 3) Lecture 18 :DESIGN OF CONTROL UNIT (PART 2) Lecture 17 : DESIGN OF CONTROL UNIT (PART 1) Lecture 16 : AMADAHL’S LAW (PART 2) Lecture 14 : SUMMARIZING PERFORMANCE RESULTS Lecture 12 : MEASURING CPU PERFORMANCE Lecture 11 : SPIM – A MIPS32 SIMULATOR Lecture 24 : STATIC AND DYNAMIC RAM Lecture 15 : AMADAHL’S LAW (PART 1) Lecture 6 : Number Representation Lecture 10 MIPS Programming Examples Lecture 27 :MEMORY INTERFACING AND ADDRESSING Lecture 26 : SYNCHRONOUS DRAM Lecture 23 : PROCESSOR MEMORY INTERACTION Lecture 20 : DESIGN OF CONTROL UNIT (PART 4) Lecture 13 : CHOICE OF BENCHMARKS Lecture 48 : DIRECT MEMORY ACCESS Lecture 49 : SOME EXAMPLE DEVICE INTERFACING Lecture 50: EXERCISES ON I/O TRANSFER Lecture 51 : BUS STANDARDS Lecture 52 : BUS STANDARDS Lecture 53: PIPELINING THE MIPS32 DATA PATH Lecture 54: MIPS PIPELINE (Contd.) Lecture 55: PIPELINE HAZARDS (PART 1) Lecture 56: PIPELINE HAZARDS (PART 2) Lecture 57: PIPELINE HAZARDS (PART 3) Lecture 58: PIPELINE HAZARDS (PART 4) Lecture 47 : INTERRUPT HANDLING (PART 2) Lecture 46 : INTERRUPT HANDLING (PART 1) Lecture 45 : DATA TRANSFER TECHNIQUES Lecture 44 : INPUT-OUTPUT ORGANIZATION Lecture 43 : SECONDARY STORAGE DEVICES Lecture 42 : ARITHMETIC PIPELINE Lecture 41 : PIPELINE SCHEDULING Lecture 40 : BASIC PIPELINING CONCEPTS Lecture 39 : FLOATING-POINT ARITHMETIC Lecture 38 : FLOATING-POINT NUMBERS Lecture 7 : Instruction Format and Addressing Modes Lecture 8 : CISC and RISC Architecture Lecture 59 : MULTICYCLE OPERATIONS IN MIPS32 Lecture 60 : EXPLOITING INSTRUCTION LEVEL PARALLELISM Lecture 61 : VECTOR PROCESSORS Lecture 62: MULTI-CORE PROCESSORS Lecture 63 : SOME CASE STUDIES Lecture 64 : SUMMARIZATION OF THE COURSE
106105164	Computer Science and Engineering	NOC:Introduction to algorithms and analysis	Prof. Sourav Mukhopadhyay	Video	IIT Kharagpur	Select Lecture 56 : Network Flow (cont...) Lecture 59 : Computational Complexity Lecture 60 : Computational Complexity (cont...) Lecture 58 : More on Dynamic Programming (cont...) Lecture 52: Union-Find Lecture 53: Augmented disjoint set data structure Lecture 57 : More on Dynamic Programming Lecture 54: Network flow Lecture 48 Lecture 49 Lecture 50 Lecture 51: Disjoint set data structure Lecture 44 Lecture 45 Lecture 46 Lecture 41 Lecture 42 Lecture 39 : Prim's Algorithms Lecture 40 : Graph Search Lecture 38 : Graphs Lecture 26 : Randomly build BST Lecture 27 : Red Black Tree Lecture 28 : Red Black Tree (Contd.) Lecture 29 : Augmentation of data structure Lecture 30 : Interval trees Lecture 31 : Fixed universe successor Lecture 32 : Van Emde Boas data structure Lecture 33 : Amortized analysis Lecture 34 : Computational Geometry Lecture 25 : Binary Search Tree (BST) Sort Lecture 24 : Perfect Hashing Lecture 5 : Substitution Method Lecture 6 : The Master Method Lecture 2 : Analysis of Insertion Sort Lecture 3 : Asymptotic Analysis Lecture 4 : Recurrence of Merge Sort Lecture 43 Lecture 37 : Longest common subsequence Lecture 55 Network Flow (contd...) Lecture 47 Lecture 35 : Computational Geometry (cont....) Lecture 23 : Universal Hashing Lecture 22 : Open Addressing Lecture 21 : Hash Function Lecture 20 : Worst case linear time order statistics Lecture 19 : Randomised Order Statistics Lecture 16 : Linear time Sorting Lecture 18 : Order Statistics Lecture 17 : Radix Sort & Bucket Sort Lecture 14 : Heap Sort Lecture 15 : Decision Tree Lecture 13 : Heap Lecture 12 : Randomized Quicksort Lecture 10 : QuickSort Lecture 11 : Analysis of Quicksort. Lecture 7 : Divide-and-Conquer Lecture 8 : Divide-and-Conquer (Contd.) Lecture 9 : Straseen's Algorithms Lecture 1 : Insertion sort Lecture 36 : Dynamic Programming
106105165	Computer Science and Engineering	NOC:Hardware modeling using verilog	Prof. Indranil Sengupta	Video	IIT Kharagpur	Select Lecture 19:BLOCKING / NON-BLOCKING ASSIGNMENTS (PART 4) Lecture 15: PROCEDURAL ASSIGNMENT (EXAMPLES) Lecture 36: SWITCH LEVEL MODDELING (PART 2) Lecture 36: SWITCH LEVEL MODDELING (PART 2) Lecture 36: SWITCH LEVEL MODDELING (PART 2) Lecture 35: SWITCH LEVEL MODELING (PART 1) Lecture 35: SWITCH LEVEL MODELING (PART 1) Lecture 35: SWITCH LEVEL MODELING (PART 1) Lecture 34: PIPELINE MODELING (PART 2) Lecture 34: PIPELINE MODELING (PART 2) Lecture 34: PIPELINE MODELING (PART 2) Lecture 33: PIPELINE MODELING (PART 1) Lecture 33: PIPELINE MODELING (PART 1) Lecture 33: PIPELINE MODELING (PART 1) Lecture 32: BASIC PIPELINING CONCEPTS Lecture 32: BASIC PIPELINING CONCEPTS Lecture 32: BASIC PIPELINING CONCEPTS Lecture 31: MODELING REGISTER BANKS Lecture 31: MODELING REGISTER BANKS Lecture 31: MODELING REGISTER BANKS Lecture 30: MODELING MEMORY Lecture 30: MODELING MEMORY Lecture 30: MODELING MEMORY Lecture 29 : SOME RECOMMENDED PRACTICES Lecture 28 : SYNTHESIZABLE VERILOG Lecture 27: DATAPATH AND CONTROLLER DESIGN (PART 3) Lecture 26 : DATAPATH AND CONTROLLER DESIGN (PART 2) Lecture 25 : DATAPATH AND CONTROLLER DESIGN (PART 1) Lecture 7: VERILOG LANGUAGE FEATURES (PART 2) Lecture 24 : MODELING FINITE STATE MACHINES (Contd.) Lecture 23 : MODELING FINITE STATE MACHINES Lecture 22 : WRITING VERILOG TEST BENCHES Lecture 21 : VERILOG TEST BENCH Lecture 20:USER DEFINED PRIMITIVES Lecture 17:BLOCKING / NON-BLOCKING ASSIGNMENTS (PART 2) Lecture 18:BLOCKING / NON-BLOCKING ASSIGNMENTS (PART 3) Lecture 17: BLOCKING / NON-BLOCKING ASSIGNMENTS (PART 2) Lecture 14: PROCEDURAL ASSIGNMENT (Contd.) Lecture 13: PROCEDURAL ASSIGNMENT Lecture 12: VERILOG DESCRIPTION STYLES Lecture 10:VERILOG MODELING EXAMPLES Lecture 11: VERILOG MODELING EXAMPLES (Contd) Lecture 8: VERILOG LANGUAGE FEATURES (PART 3) Lecture 9: VERILOG OPERATORS Lecture 6: VERILOG LANGUAGE FEATURES (PART 1) Lecture 5: Lecture 1: Lecture 2: Lecture 3: Lecture 4 : Lecture 37 : PIPELINE IMPLEMENTATION OF A PROCESSOR (PART 1) Lecture 38 : PIPELINE IMPLEMENTATION OF A PROCESSOR (PART 2) Lecture 39 : PIPELINE IMPLEMENTATION OF A PROCESSOR (PART 3) Lecture 40 : VERILOG MODELING OF THE PROCESSOR (PART 1) Lecture 41 : VERILOG MODELING OF THE PROCESSOR (PART 1)
106105166	Computer Science and Engineering	NOC:Introduction to internet of things	Prof. Sudip Misra	Video	IIT Kharagpur	Select Lecture 1 : Introduction to IoT- Part-I Lecture 7 : Basics of IoT Networking-Part- III Lecture 8 : Basics of IoT Networking- Part-IV Lecture 9 : Connectivity Technologies- Part-I Lecture 10 : Connectivity Technologies- Part-II Lecture 11: Lecture 12: Lecture 13: Lecture 14: Lecture 15: Lecture 16: Lecture 17: Lecture 18: Lecture 19 : Lecture 20 : Lecture 21: Lecture 22: Lecture 23: Lecture 24: Lecture 25: Lecture 26 : Introduction to Python Programming- I Lecture 27 : Introduction to Python Programming- II Lecture 4 : Actuation Lecture 5 : Basics of IoT Networking- Part- I Lecture 34: Lecture 35 : Lecture 29 : Introduction to Raspberry Pi- II Lecture 30 : Implementation of IoT with Raspberry Pi- I Lecture 6 : Basics of IoT Networking-Part II Lecture 31 Lecture 32: Lecture 28 : Introduction to Raspberry Pi- I Lecture 3: Sensing Lecture 2 : Introduction to IoT- Part-II Lecture 33: Lecture 46 : Smart Cities and Smart Homes- I Lecture 47 : Smart Cities and Smart Homes- II Lecture 48 : Smart Cities and Smart Homes- III Lecture 49 : Connected Vehicles- I Lecture 50 : Connected Vehicles- II Lecture 51: Smart Grid- I Lecture 52: Smart Grid- II Lecture 53: Industrial Internet of Things- I Lecture 54: Industrial Internet of Things- II Lecture 55: Data Handling and Analytics- I Lecture 56: Data Handling and Analytics- II Lecture 56: Data Handling and Analytics- II Lecture 56: Data Handling and Analytics- II Lecture 57: Case Study: Agriculture Lecture 57: Case Study: Agriculture Lecture 57: Case Study: Agriculture Lecture 58: Case Study: Healthcare Lecture 58: Case Study: Healthcare Lecture 58: Case Study: Healthcare Lecture 59: Case Study: Activity Monitoring - I Lecture 59: Case Study: Activity Monitoring - I Lecture 59: Case Study: Activity Monitoring - I Lecture 60: Case Study: Activity Monitoring - II Lecture 60: Case Study: Activity Monitoring - II Lecture 60: Case Study: Activity Monitoring - II Lecture 45 : Fog Computing- II Lecture 44 : Fog Computing- I Lecture 43 : Sensor-Cloud- II Lecture 42 : Sensor-Cloud- I Lecture 41 : Cloud Computing- Practical Lecture 40 : Cloud Computing- Case Studies Lecture 39 : Cloud Computing-Service Management and Security Lecture 38 : Cloud Computing-Service Model Lecture 37 : Cloud Computing-Fundamental Lecture 36 : Software Defined IoT Networking- II
106105167	Computer Science and Engineering	NOC:Cloud computing	Prof. Soumya Kanti Ghosh	Video	IIT Kharagpur	Select Lecture 16 Lecture 8 Lecture 21 : SLA-Tutorial Lecture 35:Use Case-Geo-spatial Cloud Lecture 35:Use Case-Geo-spatial Cloud Lecture 34: Fog Computing-II Lecture 34: Fog Computing-II Lecture 33: Fog Computing-I Lecture 33: Fog Computing-I Lecture 32: Mobile Cloud Computing -II Lecture 32: Mobile Cloud Computing -II Lecture 31: Mobile Cloud Computing -I Lecture 31: Mobile Cloud Computing -I Lecture 30; Cloud Computing: Broker for Cloud Marketplace Lecture 29: Cloud Computing: Security Issues in Collaborative SaaS Cloud Lecture 28: Cloud Computing: Security III Lecture 27: Cloud Computing: Security II Lecture 26: Cloud Computing: Security I Lecture 25 : ResourceMgmt-II Lecture 23 : MapReduce-Tutorial Lecture 24 : ResourceMgmt-I Lecture 22 : Cloudonomics-Tutorial Lecture 17: Lecture 18: Lecture 19: Lecture 20: Lecture 9 Lecture 10 Lecture 11: Lecture 12: Lecture 13 : lecture 14 : Lecture 15 : Lecture 5: Lecture 6 Lecture 7 Lecture 1: Lecture 2: Lecture 3: Lecture 4: Lecture 36 : Introduction to DOCKER Container Lecture 37 : Green Cloud Lecture 38 : Sensor Cloud Computing Lecture 39 : IoT Cloud Lecture 40 : Course Summary and Research Areas Lecture 36 : Introduction to DOCKER Container Lecture 37 : Green Cloud Lecture 38 : Sensor Cloud Computing Lecture 39 : IoT Cloud Lecture 40 : Course Summary and Research Areas
106106046	Computer Science and Engineering	Pattern Recognition	Prof. Sukhendu Das	Video	IIT Madras	Select Principles of Pattern Recognition I (Introduction and Uses) Principles of Pattern Recognition II (Mathematics) Principles of Pattern Recognition III (Classification and Bayes Decision Rule) Clustering vs. Classification Relevant Basics of Linear Algebra, Vector Spaces Eigen Value and Eigen Vectors Vector Spaces Rank of Matrix and SVD Types of Errors Examples of Bayes Decision Rule Normal Distribution and Parameter Estimation Training Set, Test Set Standardization, Normalization, Clustering and Metric Space Normal Distribution and Decision Boundaries I Normal Distribution and Decision Boundaries II Bayes Theorem Linear Discriminant Function and Perceptron Perceptron Learning and Decision Boundaries Linear and Non-Linear Decision Boundaries K-NN Classifier Principal Component Analysis (PCA) Fisher’s LDA Gaussian Mixture Model (GMM) Assignments Basics of Clustering, Similarity/Dissimilarity Measures, Clustering Criteria. K-Means Algorithm and Hierarchical Clustering K-Medoids and DBSCAN Feature Selection : Problem statement and Uses Feature Selection : Branch and Bound Algorithm Feature Selection : Sequential Forward and Backward Selection Cauchy Schwartz Inequality Feature Selection Criteria Function: Probabilistic Separability Based Feature Selection Criteria Function: Interclass Distance Based Principal Components Comparison Between Performance of Classifiers Basics of Statistics, Covariance, and their Properties Data Condensation, Feature Clustering, Data Visualization Probability Density Estimation Visualization and Aggregation Support Vector Machine (SVM) FCM and Soft-Computing Techniques Examples of Uses or Application of Pattern Recognition; And When to do clustering Examples of Real-Life Dataset
106106048	Computer Science and Engineering	Performance Evaluation of Computer Systems	Prof. Krishna Moorthy Sivalingam	Video	IIT Madras	Select Introduction to performance evaluation of computer systems How to avoid common mistakes Selection of techniques and metrics Case study: Selection of techniques and metrics Random Variables and probability distributions Probability distributions-I Probability distributions-II Probability distributions-III Stochastic process Markov Chain Slotted Aloha protocol model and discrete-time birth death process Continuous time Markov chain and queuing theory-I Queuing theory – I (Continued) Queuing theory-II Queuing theory-III Queuing theory-IV Queuing theory-V Queuing theory-VI Queuing networks-I Queuing networks-II Slotted Aloha Markov model Simulations-I Simulations-II Simulations-III Operational laws-I Operational laws-II Open and closed queuing networks Approximate MVA Convolution algorithm-I Convolution algorithm-II Load-dependent service centers Hierarchical decomposition Balanced Job Bounds Confidence interval for propotions and introduction to experimental design 2k factorial design 2k r factorial design and 2k-p fractional factorial design Programming aspects of discrete-event simulations-I Programming aspects of discrete-event simulations-II Discrete-event simulations-III PetriNets-I PetriNets-II PetriNets-III
106106049	Computer Science and Engineering	Theory of Automata, Formal Languages and Computation	Prof. Kamala Krithivasan	Video	IIT Madras	Select GRAMMARS AND NATURAL LANGUAGE PROCESSING GRAMMARS AND LANGUAGES GENERATED GRAMMARS AND LANGUAGES GENERATED (Contd) AMBIGUITY IN CFG SIMPLICATION OF CFG REMOVAL OF UNIT PRODUCTIONS , CHOMSKY NORMAL FORM FOR CFG GREIBACH NORMAL FORM FOR CFG FINAL STATE AUTOMATA NON DETERMINISTIC FSA NON DETERMINISTIC FSA (Contd) NON DETERMINISTIC FSA WITH E(Epsilon)- MOVES EQUIVALENCE BETWEEN FSA AND TYPE 3 GRAMMARS REGULAR EXPRESSIONS , REGULAR EXPRESSIONS TO NFSA DFSA TO REGULAR EXPRESSIONS PROBLEMS AND SOLUTIONS-I PUMPING LEMMAS FOR REGULAR SETS AND CFL MYHILL - NERODE THEOREM MINIMIZATION OF DFSA FSA WITH OUTPUT MOORE AND MEALY MACHINES PUSHDOWN AUTOMATA PUSHDOWN AUTOMATA , EQUIVALENCE BETWEEN ACCEPTANCE BY EMPTY STORE AND ACCEPTANCE BY FINAL STATE PUSHDOWN AUTOMATA CFG TO PDA PUSHDOWN AUTOMATA PDA TO CFG PROBLEMS AND SOLUTIONS-II PROBLEMS AND SOLUTIONS - III TURING MACHINES TURING MACHINES (Contd) TURING MACHINE AS ACCEPTOR , TECHNIQUES FOR TM CONSTRUCTION GENERALIZED VERSIONS OF TURING MACHINES TURING MACHINE AS A GENERATING DEVICE RECURSIVE SETS , RECURSIVELY INNUMERABLE SETS , ENCODING OF TM , HALTING PROBLEM PROBLEMS AND INSTANCES , UNIVERSAL TM , DECIDABILITY RICE'S THEOREM , LINEAR BOUNDED AUTOMATA , PROPERTIES OF TM POST'S CORRESPONDENCE PROBLEMS POST'S CORRESPONDENCE PROBLEMS (Contd), TIME AND TAPE COMPLEXITY OT TM NP - COMPLETE PROBLEMS , COOK'S THEOREM NP - COMPLETE PROBLEMS (Contd) REGULATED REWRITING L - SYSTEMS GRAMMAR SYSTEMS DNA COMPUTING MEMBRANE COMPUTING
106106088	Computer Science and Engineering	CAD for VLSI Design I	Prof. Shankar Balachandran	Web	IIT Madras	Select Evolution of CAD Tools Importance of Design Automation Basic Transistor Fundamentals Gate Level Modeling Higher Levels of Modeling Types of CAD Tools Verilog Quick Starter Introduction to Simulators Verilog Syntax Verilog - Operators and expressions Hierarchical Design and methodology Delay modeling Delay Modeling (contd) Blocking and Non Blocking Assignments Behavioural Modeling Verilog Tasks and Functions Memory Modeling Advanced Delay Modeling Advanced Delay Modeling (Contd) Verilog Tricks Introduction to Logic Synthesis Logic Synthesis (Contd) Logic Synthesis (Contd) Synthesis: Assignment Statements Synthesis: Arithmetic Operators Synthesis: Bit Selects Synthesis: Conditional Statements Synthesis: Case Statements Synthesis: Case Statements (Contd) Synthesis: Loops Synthesis: Local & Integer Variables Synthesis: Flip Flops with preset / clear Synthesis: Blocking Vs Non Blocking Assignments Synthesis: Unknowns and High Impedance Optimization in Synthesis Optimization in Synthesis (Contd) Introduction to Reconfigurable Computing Introduction to FPGAs Introduction to FPGAs (Contd) The Altera Quartus Flow
106106089	Computer Science and Engineering	CAD for VLSI Design II	Prof. Shankar Balachandran	Web	IIT Madras	Select Transistor Theory Introduction to MOSFET CMOS Transistor Fundamentals Transistor Theory (Contd) CMOS Transistor Theory - Delay Issues CMOS Transistor Theory - Delay Issues (Contd) CMOS Transistor Theory - Delay Models Delay Elements in CMOS Circuits Delay Elements in CMOS Circuits (Contd) Estimating Delays in a circuit, Issues in Dynamic and Staic Timing analysis Synthesis Synthesis - Synthesizable and Non Synthesizable constructs Synthesis - Logic Optimization, Resource Sharing Synthesis - Logic Optimization, Resource Sharing (Contd) Flip Flop and Latch optimaztion Introduction to Logical Effort Multistage Logic Networks Logical effort - Optimizing performance Logical Effort and Gain based Synthesis Logical Effort and Gain based Synthesis (Contd)
106106090	Computer Science and Engineering	Computer Graphics	Prof. Sukhendu Das	Video	IIT Madras	Select Introduction CRT Display Devices CRT Display Devices (Contd) CRT Display Devices (Contd) CRT Display Devices (Contd) Transformations in 2D Transformations in 2D (Contd) Three Dimensional Graphics Three Dimensional Graphics (Contd) Three Dimensional Graphics (Contd) Projection Transformations And Viewing Pipeline 3D Viewing - Projection Transformations And Viewing Pipeline Scan Converting Lines, Circles And Ellipses Scan Converting Lines, Circles And Ellipses (Contd) Scan Converting Lines, Circles And Ellipses (Contd) Scan Converting Lines, Circles And Ellipses (Contd) Scan Converting Lines, Circles And Ellipses (Contd) Polyfill- Scan Conversion Of A Polygon Scan Conversion Of A Polygon (Contd) Clipping - Lines And Polygons Clipping Lines And Polygons Clipping Lines Solid Modelling Solid Modelling Solid Modelling- (Contd) Visible Surface Detection Visible Surface Detection- (Contd) Visible Surface Detection- (Contd) Visible Surface Detection- (Contd) Visible Surface Detection- (Contd) Visible Surface Detection (Contd) Visible Surface Detection (Contd) Illumination And Shading Illumination And Shading (Contd) Illumination And Shading (Contd) Curve Representation Curve Representation (Contd) Curves And Surface Representation Graphics Programming Using Open GL Graphics Programming Using Open GL (Contd) Advanced Topics: Anti Aliasing,Color,Soft Objects,Animation,Visual Effects,System Architectures Digital Image Processing Image Compression-Jpeg-Enhancements Digital Image Processing (Contd)
106106091	Computer Science and Engineering	Computer Networks	Prof. Hema A Murthy	Web	IIT Madras	Select Introduction on Computer Networks Data Sharing Packetised File Transmission Layering Performance Metrics Basic Building blocks Modulation Physical Media Transmission DLL Framing Error Detection Error Control / Reliable Transmission Stop and Wait Analysis Sliding Window SW Analysis Medium Access sublayer Aloha Ethernet Ethernet Collision Free Protocol ATM Token bus Token ring FDDI FDDI Analysis Wireless LAN Bridge and Switches Connectionless Networks Network Layer IP Packets / Fragmentation Router Forwarding Congestion control networks Routing Algorithm - DV Virtual Networks Routing Algorithm - LSR CIDR / BGP Transport Layer TCP Connection Management TCP Protocol TCP Miscellaneous Application Layer Protocols SNMP SMTP Network Security
106106092	Computer Science and Engineering	Computer Organization	Prof. S. Raman	Video	IIT Madras	Select Introduction To Computing Introduction To System : Software Introduction To System : Hardware Processor Activities Processor As a State Machine Data Path Architecture Data Path Controller : Micro Programmed State Machine Design Controller Design: Microprogrammed and Hardwired Controller Design (Contd) Typical Micro Instructions Addressing Modes Problem Exercise Problem Exercise Introduction to memory system CPU - Memory Interaction Cache Organization Cache Organization Virtual Memory Virtual Memory Performance Calculation Segmentation Address Translation and Protection Programmed I/O Interrupt Driven I/O DMA : Direct Memory Access Device Service Routines Evolution Of I/O I/O Devices I/O Devices - Contd Buses Buses Contd Conclusion
106106093	Computer Science and Engineering	Database Design	Prof. D. Janaki Ram	Video	IIT Madras	Select Introduction to Database Management System Conceptual Designs Conceptual Designs Relational Model Relational Model Structured Query Language Structured Query Language II ER Model to Relational Mapping Functional Dependencies and Normal Form ER Model to Relational Model Mapping Storage Structures Indexing Techniques Single Level Indexing Techniques Multi-Level Constraints and Triggers Query Processing and Optimization Query Processing and Optimization II Query Processing and Optimization - III Transaction Processing Concepts Transaction Processing and Database Manager Foundation for Concurrency Control Concurrency Control Part - I Concurrency Control Part - 2 Concurrency Control Part - 3 Concurrency Control Part - 4 Distributed Transaction Models Basic 2-Phase and 3-phase commit protocol Concurrency Control for Distributed Transaction Introduction to Transaction Recovery Recovery Mechanisms II Recovery Mechanisms III Introduction to Data Warehousing and OLAP Introduction to Data Warehousing and OLAP Case Study : MYSQL Case Study ORACLE and Microsoft Access Data Mining and Knowledge Discovery Data Mining and Knowledge Discovery Part II Object Oriented Databases Object Oriented Databases II XML - Introductory Concepts XML Advanced Concepts XML Databases Case Study - Part One Database Design Case Study - Part 2 Database Design
106106094	Computer Science and Engineering	Discrete Mathematical Structures	Prof. Kamala Krithivasan	Video	IIT Madras	Select Propositional Logic Propositional Logic (Contd.) Predicates & Quantifiers Predicates & Quantifiers (Contd.) Logical Inference Resolution Principles & Application to PROLOG Methods of Proof Normal Forms Proving programs correct (Contd.) Sets Induction Set Operations On Strings Relations Graphs Graphs (Continued) Trees Trees And Graphs Special Properties Of Relations Closure Of Relations Closure Properties Of Relations Order Relations Order Relations And Equivalence Relations Equivalence Relations And Partitions Functions Functions (Continued) Functions (Continued) Pigeonhole Principle Permutations And Combinations Permutations And Combinations (Continued) Generating Functions Generating Functions (Continued) Recurrence Relations Recurrence Relations (Continued) Recurrence Relations (Continued) Algebras Algebras (Continued) Algebras (Continued) Finite State Automaton Finite State Automaton (Continued) Lattices
106106095	Computer Science and Engineering	Introduction to Database Systems and Design	Prof. P.Sreenivasa Kumar	Web	IIT Madras	Select Introduction to database Systems Entity Relationship Model Relational Model Tuple Relational Calculus The SQL Standard File Organizing and Indexing Database design and Normal forms
106106097	Computer Science and Engineering	Principles of Communication	Prof. Hema A Murthy	Web	IIT Madras	Select Introduction to Principles of Communication Signal Spaces Signal Spaces Continued Fourier Series Properties of Fourier Transform Some Examples: Continuous Fourier Transform Continuous Fourier Transforms of Periodic functions Sampling Theorem Discrete Time Signals Z Transforms Properties of Z Transform Examples of Z Transform Basics of Probability Theory and Random Processes Random Process Random Process - Some examples Random Process - Some examples Random Process through a linear filter Bandwidth Amplitude Modulation - Double Side Band- Supressed Carrier SSB - VSB Modulation Angle Modulation Noise Analysis AM, FM Digital Modulation Uncertainity, Information and Entropy Information Theory and Source Coding Mutual Information Source coding Channel Coding Error Control Coding Appendix- Miscellaneous
106106107	Computer Science and Engineering	Distributed Computing Systems	Prof. Ananthanarayana V.S	Web	IIT Madras	Select Basic Concepts Distributed Coordination Process Synchronization Interprocess Communication Distributed Deadlocks load Balancing
106106112	Computer Science and Engineering	Parallel Algorithms	Dr. N. Sairam	Web	IIT Madras	Select Need for Parallel computers Parallel Algorithm Models Performance Analysis Introduction to Processor Arrays Matrix Multiplication using Mesh Networks Matrix Multiplication using Hypercube Networks Block Matrix Multiplication Parallel Query Processing The 15 puzzle Problem Parallel Discrete Event Simulation Image Dithering Dense LU Factorization Enumeration Sort Odd Even Transposition Sort Parallel Merge Sort Hyper Quick Sort Searching in a Sorted Sequence in Parallel Searching on a random sequence in parallel Sequential Selection Algorithm Parallel Selection algorithm Graph Coloring Minimal Spanning Tree Shortest Path Algorithm
106106126	Computer Science and Engineering	Artificial Intelligence	Prof. Deepak Khemani	Video	IIT Madras	Select 1. Artificial Intelligence: Introduction 2. Introduction to AI 3. AI Introduction: Philosophy 4. AI Introduction 5. Introduction: Philosophy 6. State Space Search - Introduction 7. Search - DFS and BFS 8. Search DFID 9. Heuristic Search 10. Hill climbing 11. Solution Space Search,Beam Search 12. TSP Greedy Methods 13. Tabu Search 14. Optimization - I (Simulated Annealing) 15. Optimization II (Genetic Algorithms) 16. Population based methods for Optimization 17. Population Based Methods II 18. Branch and Bound, Dijkstra's Algorithm 19. A* Algorithm 20. Admissibility of A* 21. A* Monotone Property, Iterative Deeping A* 22. Recursive Best First Search, Sequence Allignment 23. Pruning the Open and Closed lists 24. Problem Decomposition with Goal Trees 25. AO* Algorithm 26. Game Playing 27. Game Playing- Minimax Search 28. Game Playing - AlphaBeta 29. Game Playing-SSS * 30. Rule Based Systems 31. Inference Engines 32. Rete Algorithm 33. Planning 34. Planning FSSP, BSSP 35. Goal Stack Planning. Sussman's Anomaly 36. Non-linear planning 37. Plan Space Planning 38. GraphPlan 39. Constraint Satisfaction Problems 40. CSP continued 41. Knowledge-based systems 42. Knowledge-based Systems, PL 43. Propositional Logic 44. Resolution Refutation for PL 45. First-order Logic (FOL) 46. Reasoning in FOL 47. Backward chaining 48. Resolution for FOL
106106127	Computer Science and Engineering	NOC:Programming, Data Structures and Algorithms	Dr. N S. Narayanaswamy	Video	IIT Madras	Select Introduction to Computers and Programming Writing your first program Variables, Operators and Expressions Variable declarations, more operators and precedence Input and Output Statements Conditionals Loops Video Solution to Digital Root Programming Assignment Introduction to arrays Working with 1D arrays Find prime numbers Debugging demo Multi-dimensional arrays Pointers More on pointers Arrays and pointer arithmetic Introduction to Strings More on Strings Video Solution to Print Elements of a Matrix in Spiral Order Programming Assignment Introduction to functions More details on functions Arguments, variables and parameters Pass parameters by reference Recursive functions Running time of a program Computing time complexity Video Solution to Palindrome Checker Programming Assignment Algorithms and Powering Polynomial evaluation and multiplication Linear and Binary Search Analysis Analysis of minimum and maximum in an array Sorting I: Insertion, Merge Sorting II: Counting, Radix Finding i-th smallest number Video Solution to Sorting words Programming Assignment Structures More on structures Using structures and pointers to structures Dynamic memory allocation Linked Lists Brief introduction to C++: Classes and objects Data Structures: Abstract Data Type Lists Supplementary Lesson Video Solution to Implementing a Hash Table ADT Programming Assignment Stacks: Last In First Out Queues: First In First Out Trees Tree traversal Binary Search Trees Heaps Graphs and Representation Supplementary Lesson Video Solution to the Queue in a Hospital Programming Assignment Greedy Algorithms Dynamic Programming Matrix Chain Multiplication Dijkstra's Algorithm Boyer-Moore String Matching Algorithm File I/O Modular Programming
106106129	Computer Science and Engineering	NOC:Introduction to Information Security I	Prof. V. Kamakoti	Video	IIT Madras	Select Part0 - Introduction to the Course Part1 - Definition of Information Security Part2 - Information Security Terminologies Part3 - Goals of Information Security Part4 - Implementation Issues of the Goals of Information Security - I part5 - Implementation Issues of the Goals of Information Security - II Part6 - Control Mechanisms for Information Security - I Part 7 - Access Control - Administrative and Technical Part 8 - Passwords - Are they secure? - I Part 9 - Access Control - Administrative and Technical Part 10 - Passwords - Are they secure? - III Part 11 - Multifactor Authentication - Challenges Part 12 - Application Level Control and Information Security Planning Part 13 - Information Security - Policy, Standard and Practice Part 14 - Policies governing Issues, Roles and Responsibilities Part 15 - Managing changes in Information Security Policies Part 16 - Spheres of Information Security Part 01 - Protecting your Personal Computer - I part 02 - Protecting your Personal Computer - II Part 03 - Protecting your Personal Computer - III Part 04 - Cloud Computing (Basic Definitions) - I Part 05 - Cloud Computing (Deployment) - II Part 06 - Cloud Computing (Security Issues) - III Part 07 - Cloud Computing (Trust and Risk) - IV Part 08 - Cloud Computing (Security and Privacy Issues) - V Part 09 - Cloud Computing (Security and Privacy Issues) - VI Part 10 - Cloud Computing (Application and Data level security) - VII Part 11 - Cloud Computing (Summary) - VIII Part 12 - Standard I Part 13 - Standard II Part 14 - Standard III Module 3 - Part 01 Module 3 - Part 02 Module 3 - Part 03 Module 3 - Part 04 Module 3 - Part 05 Module 3 - Part 06 Module 3 - Part 07 Module 3 - Part 08 Module 3 - Part 09 Module 4 - Part 01 module 4 - Part 02 Module 4 - Part 03 Module 4 - Part 04 Module 4 - Part 05 Module 4 - Part 06 Module 4 - Part 07 Module 4 - Part 08 Module 4 - Part 09 Module 4 - Part 10 Module 5 - Part 01 Module 5 - Part 02 Module 5 - Part 03 Module 5 - Part 04 Module 5 - Part 05 Module 5 - Part 06 Module 5 - Part 07 Module 6 - Part 01 Module 6 - Part 02 Module 6 - Part 03 Module 6 - Part 04 Module 6 - Part 05 Module 6 - Part 06 Module 6 - Part 07 Module 6 - Part 08
106106130	Computer Science and Engineering	NOC:Programming and Data structures (PDS)	Dr. N S. Narayanaswamy	Video	IIT Madras	Select Video Lecture - A Simple C Program for Sorting Video Lecture- Review of Structures, Pointers, and Functions Video Lecture - Recursion Video Lecture-Abstract Data Types-Data + Methods. Video Lecture-List Data Type Video Lecture - Access and update methods Video Lecture:Doubly Linked List Data Type Video Lecture-Doubly Linked Lists and Arrays Video Lecture - ADT Stacks Video Lecture:Checking of Balanced Parenthesis Video Lecture:Infix and Postfix expressions and Expression evaluation Queue ADT Definition and Implementation Merging using Queue ADT and Queue types Tree ADT and Traversals Binary Tree ADT and traversals Tree Applications Binary Search Trees Heaps
106106131	Computer Science and Engineering	NOC:Design and Analysis of Algorithms	Prof. Madhavan Mukund	Video	IIT Madras	Select Course Outline Example: Air Travel Example: Xerox shop Example: Document similarity Introduction and motivation Input size, worst case, average case Quantifying efficiency: O( ), Omega( ), Theta( ) Examples: Analysis of iterative and recursive algorithms Arrays and lists Searching in an array Selection Sort Insertion sort Merge sort Merge sort - analysis Quicksort Quicksort - analysis Sorting - Concluding remarks Introduction to graphs Representing graphs Breadth first search (BFS) Depth first search (DFS) Applications of BFS and DFS Directed acylic graphs: topological sort Directed acylic graphs: longest paths Single source shortest paths: Dijkstras algorithm Dijkstras algorithm: analysis Negative edge weights: Bellman-Ford algorithm All pairs shortest paths Minimum Cost Spanning Trees Prims Algorithm Kruskals algorithm Union-Find using arrays Union-Find using pointers Priority queues Heaps Heaps: Updating values, sorting Counting inversions Closest pair of points Binary Search Trees Balanced search trees Interval scheduling Scheduling with deadlines: minimizing lateness Huffman codes Introduction to dynamic programming Memoization Grid Paths Common subwords and subsequences Edit distance Matrix multiplication Linear Programming LP modelling: Production Planning LP modelling: Bandwidth allocation Network Flows Reductions Checking Algorithms P and NP
106106133	Computer Science and Engineering	NOC:2016: Programming, Data structures and Algorithms	Prof. Hema A Murthy	Video	IIT Madras	Select Introduction to Computers and Programming Writing your first program Variables, Operators and Expressions Variable declarations, more operators and precedence Input and Output Statements Conditionals Loops Introduction to arrays Working with 1D arrays Find prime numbers Debugging demo Multi-dimensional arrays Pointers More on pointers Arrays and pointer arithmetic Introduction to Strings More on Strings Introduction to functions More details on functions Arguments, variables and parameters Pass parameters by reference Recursive Functions C control structures, functional specification of programs Complexity Analysis using Sum and Product Rule Complexity Analysis of Recursive Functions Algorithms and Powering Polynomial evaluation and multiplication Linear and Binary Search Analysis Analysis of minimum and maximum in an array Sorting I: Insertion, Merge Sorting II: Counting, Radix Finding i-th smallest number Structures More on Structures Using structures and pointers to structures Dynamic memory allocation Linked List Brief introduction to C++: Classes and objects Abstract Data Types More on ADT Stacks : Last In First Out Queues: First In First Trees Tree Traversal Binary Search Heaps Graphs and Representations Greedy Algorithms Dynamic Programming Matrix Chain Multiplication Hash Tables Graph Algorithms: Dijkstras Algorithm and Prims Algorithm Graph Traversals : BFS,DFS and Articulation Points File I/O Modular Programming
106106134	Computer Science and Engineering	NOC:Computer Architecture(Course sponsored by Aricent)	Prof.Madhu Mutyam	Video	IIT Madras	Select Introduction to Computer Architecture Quantitative Principles of Computer Design Instruction Set Principles-Part 1 Instruction Set Principles-Part 2 Instruction Set Principles-Part 3 Cache Memory Hierarchy - Part 1 Cache Memory Hierarchy - Part 2 Cache Memory Hierarchy - Part 3 Cache Memory Hierarchy - Part 4 Main Memory Design - Part 1 Main Memory Design - Part 2 Main Memory Design - Part 3 Fundamentals of Pipelining - Part 1 Fundamentals of Pipelining - Part 2 Fundamentals of Pipelining - Part 3 Fundamentals of Pipelining - Part 4 Fundamentals of Pipelining - Part 5 Scalar to Superscalar pipeline Instruction Dependencies Compiler optimizations for Exposing ILP Advanced Branch Prediction Techniques - Part 1 Advanced Branch Prediction Techniques - Part 2 Superscalar Organization Register Renaming Tomasulo Algorithm Dynamic Execution Core Multi threading Multicore Processor Architecture Cache Coherence Cache Coherence Protocol Design Synchronization Memory Consistency - Part 1 Memory Consistency - Part 2
106106136	Computer Science and Engineering	NOC:Model Checking	Prof. B. Srivathsan	Video	IIT Madras	Select Course Overview Module 1: Modeling code behaviour Module 2: Modeling hardware circuits Module 3: Modeling data-dependent programs Module 4: Modeling concurrent systems Summary Module 1: Model checking tools Module 2: Simple models in NuSMV Module 3: Hardware verification using NuSMV Module 4: Modeling concurrent systems in NuSMV Summary. Module 1: A problem in concurrency Module 2: What is a property? Module 3: Invariants Module 4: Safety properties Module 5: Liveness properties Summary.. Module 1: Road map Module 2: A gentle introduction to automata Module 3: Simple properties of finite automata Module 4: Safety properties described by automata Summary... Module 1: Specifying properties Module 2: Omega-regular expressions Module 3: Bchi automata Module 4: Simple properties of Bchi automata Summary.... Module 1: Overview Module 2: Omega-regular expressions to NBA Module 3: Checking emptiness of NBA Module 4: Generalized NBA Summary..... Concluding remarks Timed transition systems Summary ..... Module 3: Representing transition systems as OBDDs Module 2: Ordered BDDs Module 1: Introduction to BDDs Module 1: Introduction to LTL Module 2: Semantics of LTL Module 3: A puzzle Summary . Module 1: Automata based LTL model-checking Module 2: LTL to NBA Module 3: Automaton construction Summary .. Module 1: Tree view of a transition system Module 2: CTL* Module 3: CTL summary ... Module 1: Adequate CTL formulae Module 2: EX, EU, EG Module 3: Final algorithm Module 4: State-space explosion Summary ....
106106137	Computer Science and Engineering	NOC:Functional Programming in Haskell	Prof. S P Suresh	Video	IIT Madras	Select Functions Types Haskell Running Haskell programs Currying Examples Lists Functions on lists Characters and strings Tuples Computation as rewriting Polymorphism and higher-order functions Map and filter List comprehension Folding through a list Measuring efficiency Sorting Using infinite lists Conditional polymorphism Defining functions in ghci Input/Output Arrays User-defined datatypes Abstract datatypes Modules Recursive data types Binary search trees Balanced search trees
106106138	Computer Science and Engineering	Virtual Reality	Prof Steven LaValle	Video	IIT Madras	Select Course mechanics Goals and VR definitions Historical perspective Birds-eye view (general) Birds-eye view (general), contd Birds-eye view (hardware) Birds-eye view (software) Birds-eye view (sensation and perception) Geometric modeling Transforming models Matrix algebra and 2D rotations 3D rotations and yaw, pitch, and roll 3D rotations and yaw, pitch, and roll, contd Axis-angle representations Quaternions Converting and multiplying rotations Converting and multiplying rotations, contd Homogeneous transforms The chain of viewing transforms Eye transforms Eye transforms, contd Canonical view transform Viewport transform Viewport transform, contd Three interpretations of light Refraction Simple lenses Diopters Imaging properties of lenses Lens aberrations Optical system of eyes Photoreceptors Sufficient resolution for VR Light intensity Eye movements Eye movements, contd Eye movement issues for VR Neuroscience of vision Depth perception Depth perception, contd Motion perception Frame rates and displays Frame rates and displays contd Overview Orientation tracking Tilt drift correction Yaw drift correction Tracking with a camera Perspective n-point problem Filtering Lighthouse approach Visual Rendering-Overview Visual Rendering-overview, contd Shading models Rasterization Pixel shading VR-specific problems Distortion shading Post-rendering image warp Physics and physiology Auditory perception Auditory localization Rendering Spatialization and display Combining other senses Interfaces -overview Locomotion Manipulation System control Social interaction Evaluation of VR Systems
106106139	Computer Science and Engineering	NOC:Introduction to Machine Learning(Course sponsored by Aricent)	Dr. Balaraman Ravindran	Video	IIT Madras	Select A brief introduction to machine learning Supervised Learning Unsupervised Learning Reinforcement Learning Probability Basics - 1 Probability Basics - 2 Linear Algebra - 1 Linear Algebra - 2 Statistical Decision Theory - Regression Statistical Decision Theory - Classification Bias-Variance Linear Regression Multivariate Regression Subset Selection 1 Subset Selection 2 Shrinkage Methods Principal Components Regression Partial Least Squares Linear Classification Logistic Regression Linear Discriminant Analysis 1 Linear Discriminant Analysis 2 Linear Discriminant Analysis 3 Optimization Perceptron Learning SVM - Formulation SVM - Interpretation & Analysis SVMs for Linearly Non Separable Data SVM Kernels SVM - Hinge Loss Formulation Weka Tutorial Early Models Backpropogation I Backpropogation II Initialization, Training & Validation Maximum Likelihood Estimate Priors & MAP Estimate Bayesian Parameter Estimation Introduction Regression Trees Stopping Criteria & Pruning Loss Functions for Classification Categorical Attributes Multiway Splits Missing Values, Imputation & Surrogate Splits Instability, Smoothness & Repeated Subtrees Tutorial Evaluation Measures I Bootstrapping & Cross Validation 2 Class Evaluation Measures The ROC Curve Minimum Description Length & Exploratory Analysis Introduction to Hypothesis Testing Basic Concepts Sampling Distributions & the Z Test Student\'s t-test The Two Sample & Paired Sample t-tests Confidence Intervals Bagging, Committee Machines & Stacking Boosting Gradient Boosting Random Forest Naive Bayes Bayesian Networks Undirected Graphical Models - Introduction Undirected Graphical Models - Potential Functions Hidden Markov Models Variable Elimination Belief Propagation Partitional Clustering Hierarchical Clustering Threshold Graphs The BIRCH Algorithm The CURE Algorithm Density Based Clustering Gaussian Mixture Models Expectation Maximization Expectation Maximization Continued Spectral Clustering Learning Theory Frequent Itemset Mining The Apriori Property Introduction to Reinforcement Learning RL Framework and TD Learning Solution Methods & Applications Multi-class Classification
106106140	Computer Science and Engineering	NOC:Artificial Intelligence: Knowledge Representation and Reasoning	Prof. Deepak Khemani	Video	IIT Madras	Select Introduction Introduction to Knowledge Representation and Reasoning An Introduction to Formal Logics Propositional Logic: Language, Semantics and Reasoning Propositional Logic: Syntax and Truth Values Propositional Logic: Valid Arguments and Proof Systems Propositional Logic: Rules of Inference and Natural Deduction Propositional Logic: Axiomatic Systems and Hilbert Style Proofs Propositional Logic: The Tableau Method Propositional Logic: The Resolution Refutation Method Syntax Semantics Entailment and Models Proof Systems Forward Chaining Unification Forward Chaining Rule Based Systems The Rete Algorithm Rete Algorithm - Example Programming in a Rule Based Language The OPS5 Expert System Shell Skolemization Terminological Facts Properties and Categories Reification and Abstract Entities Resource Description Framework (RDF) The Event Calculus: Reasoning About Change Natural Language Semantics CD Theory CD Theory (contd) English to CD Theory Backward Chaining Logic Programming Prolog Search in Prolog Controlling Search The Cut Operator in Prolog Incompleteness The Resolution Method for FOL Clause Form FOL with Equality Complexity of Resolution Refutation Semantic Nets and Frames Scripts Applying Scripts Goals, Plans and Actions Plan Applier Mechanism Top Down and Bottom Up Reasoning Introduction Normalisation Structure Matching Structure Matching - Example Classification A-box reasoning DL: Extensions DL: ALC ALC examples Taxonomies and Inheritance Beliefs Inheritance Hierarchies: Introduction. Circumscription Circumscription (contd) Minimal Models Event Calculus Revisited Circumscription in EC Defaul Logic Autoepistemc Logic Epistemic Logic The Muddy Children Puzzle
106106141	Computer Science and Engineering	NOC:Information Security - II(Course sponsored by Aricent)	Prof. V. Kamakoti	Video	IIT Madras	Select Experimental Setup: Video Tutorial Need for Secure Systems Ignorance of A is Sin of B Function calls and Stacks Stack Smashing Virtual Machine Based Rootkits Security and Architecture: Introduction Structured Computer Organization Completed X86 ISA Part1 X86 ISA Part 2 X86 Protected Mode X86 Memory Segmentation Process Isolation using Segmentation Paging and Virtual Memory Task Switching and Interrupt Service Memory Segmentation Deep dive P1 Memory Segmentation Deep dive P2 Memory Segmentation Deep dive P3 - Week 4 Memory Segmentation Deep dive P4 - Week 4 Segmentation Recap - Week 4 Lab1 Part 1 - Week 4 Lab1 Part 2 - Week 4 Lab 1 Part 3 - Week4 ISR Recap - Week 5 Lab2 Part 1 - Week 5 Lab2 Part 2 - Week 5 Memory Management Recap - Week 5 Lab3 Part 1 - Week 5 Lab3 Part 2 - Week 5 Task Switch recap - Week 6 Lab4 Part 1 - Week 6 Lab4 Part 2 - Week 6 Lab4 Part 3 - Week 6 Lab4 Part 4 - Week 6 Introduction to Basic Cryptography - Week7 Public Key Cryptography - Week 7 Freescale ARM iMX6 Processor- Week 7 High Assurance Boot in iMX6 - Week 7 Case Study - Week 7 Basics of Networking - Week 8 Network Processor Vs General Purpose Processor - Week 8 Network Processor Architecture - Week 8
106106142	Computer Science and Engineering	NOC:Algorithms for Big Data	Prof. John Augustine	Video	IIT Madras	Select Lesson 4 - Graph streaming algorithms: Matching Lesson 5 - Graph streaming algorithms: Graph sparsification Lesson 1 - MapReduce Lesson 2 - Property testing framework Lesson 3 - Testing Connectivity Lesson 4 - Enforce & Test Introduction Lesson 1 - Estimating frequency moments Problem solving video - Cat And Mouse Problem solving video - Lollipop Graph Problem solving video - Random Walks on Linear Structures Lesson 3 - Graph streaming algorithms: Introduction Lesson 5 : Pairwise independence Lesson 3 : Chain hashing, SUHA, Power of Two choices Lesson 1 : Overview Lesson 9 - Approximate Median Lesson 8 - Reservoir Sampling Lesson 7 - Intro to Streaming, Morris Algorithm Lesson 5 - Celebrities Case Study Lesson 2 - SAT Problem Lesson 1 - Intro to Big Data Algorithms Lesson 4 - Application of Chebyshev's inequality Lesson 3 - Application of Chernoff bound Lesson 2 - Tail Bounds Lesson 1 - Bernoulli, Binomial, and Geometric distributions Lesson 7 - Randomized quicksort Lesson 6 - Random variables Lesson 4 - Karger's mincut algorithm Lesson 2 - Conditional probability Lesson 2 - Testing if a graph is bipartite (using random walks) Lesson 1 - Property testing and random walk algorithms Lesson 6 - Testing bipartiteness Lesson 1 - Universal hash functions Lesson 2 - Perfect hashing Lesson 3 - Count-min filter for heavy hitters in data streams Lesson 6 : Estimating expectation of continuous function Lesson 2 - K-Machine Model (aka Pregel Model) Lesson 5 - Testing if a graph is a biclique Problem solving video - Doubly Stochastic Transition Matrix Lesson 4 : Bloom filter Lesson 2 : Balls, bins, hashing Lesson 6 - Random Walks on Undirected Graphs Lesson 4 - Stationary Distribution of a Markov Chain Lesson 3 - Classification of States Problem solving video - Monty Hall problem Problem solving video - The rich get richer Lesson 5 - Analysis of Karger's mincut algorithm Lesson 3 - Example problems Lesson 1 - Basic definitions
106106143	Computer Science and Engineering	NOC:Reinforcement Learning	Dr. B. Ravindran	Video	IIT Madras	Select TD(0) Returns, Value Functions and MDPs REINFORCE Introduction to Immediate RL Policy Iteration Dynamic Programming Bellman Optimality Equation Cauchy Sequence and Green's Equation Banach Fixed Point Theorem Convergence Proof Lpi Convergence Value Iteration MDP Modelling Bellman Equation Tutorial 1-Probability basics2 Solving POMDP POMDP Introduction MAXQ Value Function Decomposition Option Discovery Hierarchical Abstract Machines MAXQ Options Learning with Options Semi Markov Decision Processes LSTD and LSTDQ LSPI and Fitted Q DQN and Fitted Q-Iteration Policy Gradient Approach Actor Critic and REINFORCE REINFORCE (cont'd) UCB 1 Concentration Bounds UCB 1 Theorem PAC Bounds Median Elimination Thompson Sampling Policy Search Monte Carlo RL Framework and applications Introduction to RL Tutorial 2-Linear algebra-2 Contextual Bandits Full RL Introduction Backward View of Eligibility Traces Eligibility Trace Control Thompson Sampling Recap Function Approximation Linear Parameterization State Aggregation Methods Function Approximation and Eligibility Traces Value function based methods Bandit Optimalities Eligibility Traces Afterstate Q-Learning TD(0) Control UCT Control in Monte Carlo Off Policy MC Policy Gradient with Function Approximation Hierarchical Reinforcement Learning Types of Optimality Tutorial 2-Linear algebra-1 Tutorial 1 - Probability Basics 1
106106144	Computer Science and Engineering	NOC:Introduction to Operating Systems	Prof. Chester Rebeiro	Video	IIT Madras	Select PC Booting PC Hardware From Programs to Processes Memory Management in xv6 Introduction Virtual Memory MMU Mapping Segmentation Preventing Buffer Overflow Attacks System Calls for Process Management Interrupts Interrupt Handling Software Interrupts and System calls CPU Context switching Software solutions for critical sections Bakery Algorithm Hardware Locks Mutexes Semaphores Dining Philosophers Problem Deadlocks Dealing with Deadlocks Threads Part 1 Threads Part 2 Operating system security Information Flow policies Scheduling in Linux Completely Fair Scheduling Inter Process Communication Synchronization Priority Based Scheduling Algorithms Introduction to OS Buffer Overflows Multi-Processor Scheduling CPU Scheduling Create Execute and Exit from Processes Week 3 Introduction Sharing the CPU Intro to the Course
106106145	Computer Science and Engineering	NOC:Programming, Data Structures and Algorithms in Python	Prof. Madhavan Mukund	Video	IIT Madras	Select Lecture 4: String functions Lecture 3: Handling files Lecture 2:Standard input and output Lecture 5:Formatting printed output Lecture 6: pass, del() and None Lecture 1: Backtracking, N queens Lecture 2: Global scope, nested functions Lecture 3: Generating permutations Lecture 4: Sets, stacks, queues Lecture 5: Priority queues and heaps Lecture 1: Abstract datatypes, classes and objects Lecture 2: Grid paths Lesson 3: Longest common subsequence Lecture 4: Matrix multiplication Lecture 5: Wrap-up, Python vs other languages Lecture 4: Downloading and installing Python Lecture 5: Tuples and dictionaries Lecture 1: Assignment statement, basic types - int, float, bool Lecture 6: Selection Sort Lecture 6: Examples Lecture 5: Functions Lecture 4: Control Flow Lecture 2: Strings Lecture 8: Recursion Lecture 1: Mergesort Lecture 2: Mergesort, analysis Lecture 3: Quicksort Lecture 4: Quicksort analysis Lecture 7: List Comprehension Lecture 1: Exception Handling Lecture 2: Classes and objects in Python Lecture 3: User defined lists Lecture 3: Euclid's algorithm for gcd Lecture 2: Improving naive gcd Lecture 1: Memoization and dynamic programming Lecture 4: Search trees Lecture 6: Function definitions Lecture 7: Insertion Sort Lecture 5: Efficiency Lecture 4: Arrays vs lists, binary search Lecture 3: Breaking out of a loop Lecture 2: Manipulating lists Lecture 1: More about range() Lecture 3: Lists Lecture 1: Algorithms and programming: simple gcd
106106146	Computer Science and Engineering	NOC:Privacy and Security in Online Social Networks	Prof. Ponnurangam Kumaraguru	Video	IIT Madras	Select Week-4.1 Privacy and Pictures on Online Social Media Tutorial 3 Part 1 Twitter API Week 3.1 Misinformation on Social Media Week 5.3 Policing and Online Social Media Week-5.1 Policing and Online Social Media Week-5.2 Policing and Online Social Media Week 9.1: Privacy in Location Based Social Networks Part 1 Week 8.2: Anonymous Networks Week 8.1: Profile Linking on Online Social Media Tutorial 5: Analyzing text using Python NLTK Week-7.3: Semantic attacks: Spear phishing Week-7.2: Nudges Week-7.1: Link Farming in Online Social Media Tutorial 4 Social Network Analysis Week 6.2 eCrime on Online Social Media Week 1.2 IntroToCourse Tutorial 1 Part 1 Ubuntu Week 1.3 Incidents Tutorial 1 Part 2 Python Week 2.1 OSM APIs and tools for data collection Tutorial 2 Part 1 Facebook API Week 3.2 Privacy and Social Media Week 9.2: Privacy in Location Based Social Networks Part 2 Tutorial 2 Part 2 Facebook API Week-2.2 Trust and Credibility on OSM Tutorial 6: Gephi Network Visualization Week 6.1: eCrime on Online Social Media Tutorial 3 Part 3 MongoDB Tutorial 3 Part 2 MySQL Week 1.1 Intro to Course Tutorial 7: Visualization - Highcharts Week 10.1: Beware of What You Share Inferring Home Location in Social Networks Week 10.2: On the dynamics of username change behavior on Twitter Week 10.3: Boston Marathon Analyzing Fake Content on Twitter
106106147	Computer Science and Engineering	NOC:Mobile Computing	Prof. Pushpendra Singh	Video	IIT Madras	Select Saving Data - I Saving Data - II Security and System Permissions Services Processes and threads Working with Fragments Working with Fragments - II Working with Fragments - III Application Fundamentals Java: Classes, Exceptions, Threads Java: Interfaces Java: Strings, OOP principles Java: Primitive Data Types, Strings, Loops, Conditional Statements RecyclerView, Adapter, ViewHolder Implicit Intents Fragment Basic Programming Example Fragments - II Debugging Intents - I Intents - II Observer Pattern RecyclerView, Adapter ViewPager Dialogues Fragments - Advanced Example Extending the application Activity Lifecycle I Activity Lifecycle II Activity LifeCycle III Adding Icon, Layout, Handling Rotation - I Adding Icon, Layouts, Handling Rotation - II Java Basics Fragments - I Introduction to Android Studio Your First App Deploying your App to a Phone Extending app - Buttons, Toast Android Development Environment User Interface
106106156	Computer Science and Engineering	NOC:Introduction to Modern Application Development	Tanmai Gopal	Video	IIT Madras	Select Module 16 - Introduction to Mobile Application Development Part 2 Module 17 - Introduction to Android Module P12 - Getting started with Android Application Development Module 15: Introduction to mobile apps Module P11: Introduction to authentication, hashing, curl & sessions Module 13: Authentication with HTTP Module 14: Understanding security, and some best practices for webapps Module 17: SQL & NoSQL systems Module P10: Module P10: Connecting your webapp to your database & SQL Injection Module 10: Database security, backup & recovery Module 11: Analytics & Views Module 9: Transactions & ACID properties Module P9: Introduction to SQL Module 8: Understanding database performance Module P8: Practical: Deeper exploration of a DBMS (column types and more) Module 6: Introduction to databases Module 7: Data modelling & constraints Module P7: Interacting with a DBMS Module P5: Introduction to client-side Javascript Module P6: Practical: APIs and mobile apps use web-servers Module P3: Practical: Building a webapp with nodejs and using git. Introduction to reverse proxies. Module P4: Module P4: Practical: Introduciton to server-side javascript and HTML/CSS Building a web-app Networks P1: Practical: Running your own web-server Protocols Module P2: Practical: SSH + Network experiments Introduction to the course Introduction to a web-app Introduction to a web-app Module P13 - Building Custom UI using XML and Logs Module P14 - Building a Blog App Module 18: Deploying an app to the Google Play Store Module 19: Introduction to iOS Module 19: The API Economy
106106157	Computer Science and Engineering	NOC:Information Security-3	Prof. V. Kamakoti	Video	IIT Madras	Select Operating System Introduction Storage Hierarchy , Exceptions, Interrupts and traps Review II Snort Review I Wireshark Security in Practise (contd.) Security in Practise Digital Signatures Public Key Cryptography Public Key Cryptography An Introduction Structure of a Network Network Core - Definition Network Access and Physical Media Structure of ISP and Packet Delays Network Protocol Layers Network Devices File Systems 1 File Systems-1 Unix Filesystem Unix Filesystem (Contd.) Linux : Basic Commands Linux : Basic Commands (Contd.) Linux : Users and Permissions Linux : I/O Redirection and Pipes Linux : Task Control Linux : Shell Environment Linux: Text Editors Linux : Compression / Archiving Linux: Print & Sync Commands Linux: File Comparison Basic Networking Administration Network Security- An Introduction Shell Script Variations Shell Pattern Matching Shell Case Statements Shell Co-routines Shell Signals and Traps Shell Subshell Shell Declarations Shell Examples 2 OS Management Services OS Security Issues Process And Threads Process Scheduling Scheduling Algorithm Process Synchronization Memory Management - 1 Shell Review Shell Comments and Variables Shell Variables Shell Arrays and Arithmetic Shell Condition and Relation Shell Examples Shell Functions Shell File Test Shell Loop Control Shell Introduction Filesystems and Devices Memory Management - 2
106106158	Computer Science and Engineering	NOC:AI:Constraint Satisfaction	Prof. Deepak Khemani	Video	IIT Madras	Select Constraint Satisfaction Problems CSP Examples: Map colouring, N-Queens, Classroom scheduling CSP Examples: Huffman-Clowes Labelling, Waltz Algorithm, Crosswords Model Based Diagnosis - An application of CSP Constraint Networks - An Introduction Binary Constraint Networks (BCN), Equivalent Networks Projection Networks Constraint Propagation Algorithms AC1 and AC3 Can we do better than AC3? Algorithm AC4 Generalized AC, Path-Consistency i-Consistency, Algorithm PC1 Algorithm PC2, Strong i-Consistency Directional Consistency and Graph Ordering Min-Width and Min-Induced-Width Ordering Directional Arc-Consistency and Tree CSPs Directional Path-Consistency and Directional i-Consistency Backtrack-Free search and Adaptive Consistency Adaptive Consistency: Bucket Elimination Search Methods for Solving CSPs Algorithm Backtracking Look-Ahead Methods in Search Look-Ahead Search: Examples Combining Search with Reasoning: Algorithm DPLL Algorithm Backmarking Dynamic Value Ordering, Dynamic Variable Ordering Look-Back Methods - Definitions Gaschnig’s Backjumping: The Culprit Variable Gaschnig’s Backjumping, Graph-Based Backjumping Graph-Based Backjumping: Internal and Relevant Dead-Ends Conflict-Directed Backjumping: Definitions Algorithm Conflict-Directed Backjumping Combining Look-Ahead and Look-Back: FC-CBJ Learning During Search Model Based Systems Model Based Diagnosis Truth Maintenance Systems Planning as Constraint Satisfaction Planning as Constraint Satisfaction (cont.) Planning as Satisfiability Wrapping Up and Further Study
106106166	Computer Science and Engineering	NOC:Computer Organization and Architecture	Prof. V. Kamakoti	Video	IIT Madras	Select Shared Memory Architecture, Cache Coherence Shared Memory Architecture, Cache Coherence Shared Memory Architecture, Cache Coherence Concurrent Programming in Hardware Concurrent Programming in Hardware Concurrent Programming in Hardware Concurrent Programming in Hardware-Part II Concurrent Programming in Hardware-Part II Concurrent Programming in Hardware-Part II Conclusion : Recent Trends in Computer Organization & Architecture Conclusion : Recent Trends in Computer Organization & Architecture Conclusion : Recent Trends in Computer Organization & Architecture Page Frame Allocation, Beledy's Anomaly Paging, Cache Cache Cache Organisation Cache - Cache Coherency, Dual Ported Cache Multilevel Caching, Multitasking Cache, Degree of Multiprogramming Shared Memory Architecture Shared Memory Architecture-Part I Virtually Indexed - Virtually Tagged and Physically Tagged Caches Pipelining Data Hazards Lab 2: Instruction Scheduling - Static and Dynamic Dynamic Instruction Scheduling Dynamic Instruction Scheduling (Contd..) Control Hazard, Branch Prediction Process Management Branch prediction Global Branch Prediction Structural Hazard, Architectural Enhancements Lab 3: Virtual Memory Locality of Reference, Demand paging Page Replacement Algorithm Multilevel Paging, Translational Lookaside Buffer Multilevel Paging Orthogonal ISA, C Constructs Mapping, Addressing Modes Atomic and Predicated Instructions Atomic and Predicated Instructions ( Contd.) General Purpose Registers Expanding opcodes Lab 4 : Task Switching ( Contd) Lab 4 : Task Switching ( Contd) Lab 4 : Task Switching ( Contd) Multilevel Paging-Part 1 Lab 2 : Segmentation-Part II Lab 2 : Segmentation Floating point - Precision and Accuracy Floating Point - Addition, Subtraction and Multiplication Instruction Set Architecture Fast Multiplier Circuit Fast Multiplier Circuit (Contd.) Programming using X86 ISA - Addressing Modes Programming using X86 ISA - Addressing Modes Introduction High Speed Circuit - Design Recursive Doubling High Speed Circuit Design - Fast Adder Circuits Lab 1 : Introduction Fast Adder Circuits (Contd.) Introduction to Pipelining Lab 2 : Segmentation-Part III Instruction Set Architecture (Continued)
106106167	Computer Science and Engineering	NOC:Introduction to Wireless and Cellular Communications	Prof. David Kovil Pillai	Video	IIT Madras	Select Statistical Characterization of Antenna Diversity, Optimal Diversity Combining Lecture 44 Lecture 43 Channel State Information, Optimum Power Allocation Capacity of fading Channels, Capacity with Outage Alamouti Scheme – Part II, Channel Capacity Array Gain, Diversity Gain, Alamouti Scheme BER in fading, Equal Gain Combining Lecture 39 Lecture 40 Lecture 41 Lecture 42 WSSUS – Classification of Fading Channels Shadowing, Outage, Multipath Rayleigh Fading and Statistical Characterization Introduction to Diversity, Antenna selection diversity Jakes’ Method properties Rayleigh Fading simulation - Clark and Gans Method, Jakes’ Method Practical Channel Models (ITU, COST), Computer generation of Rayleigh fading WSSUS – Characterization of Time Dispersive Fading Channels Doppler, Temporal Characteristics of Fading Channels WSSUS Part II, Coherence Time, Doppler Spectrum MGF Part II, WSSUS Model Ricean and Nakagami Fading, Moment Generating Function (MGF) BER in Fading - Part II, Ricean Fading Review of Lec 1-19 Coherent vs Differential Detection - Part II and BER in Fading Coherent versus Differential Detection Choice of Modulation Characterization of Multipath Fading Channels Properties of Rayleigh Distribution BER in Fading, Narrowband vs Wideband Channels Overview of Cellular Systems - Part 1 Overview of Cellular Systems - Part 2 Overview of Cellular Systems - Part 3 5G and other Wireless Technologies Basic Cellular Terminology Introduction to Antennas and Propagation Models Link budget, Fading margin, Outage Handoff & Mobility Handoff Part 2, Classification of Signal Variation Cellular Geometry & System Design Cellular System Capacity, Trunking Cellular Concept Cellular system design and analysis Lecture 52 Lecture 53 Lecture 54 Lecture 55 Rake Receiver for multipath channels Multiuser environment CDMA system Capacity CDMA Multiuser Detectors – Part 1 CDMA Multiuser Detectors – Part 2
106106168	Computer Science and Engineering	NOC:Distributed Systems	Dr. Rajiv Misra	Video	IIT Patna	Select Lecture 01 - Introduction to Distributed Systems Lecture 02 - Basic Algorithms in Message Passing System Lecture 03 - Leader Election in Rings Lecture 04 - Distributed Models of Computation, Causality & Logical Time Lecture 05 - Size of Vector Clock, Matrix Clocks, Virtual Time and Physical Clock Synchronization Lecture 06 - Global State and Snapshot Recording Algorithms Lecture 07 - Distributed Mutual Exclusion and Non-Token based Approaches Lecture 08 - Quorum Based Distributed Mutual Exclusion Approaches Lecture 9 - Token Based Distributed Mutual Exclusion Approaches Lecture 10 : Consensus and Agreement Algorithms Lecture 11 - Checkpointing & Rollback Recovery Lecture 12 - Deadlock Detection in Distributed Systems Lecture 13 - Distributed Shared Memory Lecture 14 - Distributed Minimum Spanning Tree Lecture 15 - Termination Detection in Distributed System Lecture 16 - Message Ordering and Group Communication Lecture 17 - Self-Stabilization Case Study 01 - Distributed Randomized Algorithms Case Study 02 - Peer-to-Peer Computing and Structured Overlay Network Case Study 03 - The Google File System (GFS) Case Study 04 - MapReduce Case Study 05 - HDFS Case Study 06 - Spark Case Study 07 - Distributed Algorithms for Sensor Networks Case Study 08 - Authentication in Distributed Systems Case Study 09 - Bitcoin: A Peer-to-Peer Electronic Cash System Case Study 10 - BlockChain Technology Lecture 08 - Quorum Based Distributed Mutual Exclusion Approaches Lecture 07 - Distributed Mutual Exclusion and Non-Token based Approaches Lecture 06 - Global State and Snapshot Recording Algorithms Lecture 05 - Size of Vector Clock, Matrix Clocks, Virtual Time and Physical Clock Synchronization
106106169	Computer Science and Engineering	NOC:Social Networks	Prof. Sudarshan Iyengar	Video	IIT Ropar	Select Modeling Diffusion The Base Code Coding the First Big Idea - Increasing the Payoff Coding the Second Big Idea - Key People Coding the Third Big Idea- Impact of Communities on Cascades Coding the Fourth Big Idea - Cascades and Clusters Impact of Commmunities on Diffusion Cascade and Clusters Knowledge, Thresholds and the Collective Action An Introduction to the Programming Screencast (Coding 4 major ideas) Implementing PageRank Using Points Distribution Method-2 Implementing PageRank Using Points Distribution Method-3 Implementing PageRank Using Points Distribution Method-4 Implementing PageRank Using Random Walk Method -1 Implementing PageRank Using Random Walk Method -2 DegreeRank versus PageRank We Follow Why do we Follow? Diffusion in Networks The Web Graph Collecting the Web Graph Equal Coin Distribution Random Coin Dropping Google Page Ranking Using Web Graph Forming two coalitions Forming two coalitions contd ENEMY'S ENEMY IS A FRIEND Characterizing the structure of balanced networks BALANCE THEOREM PROOF OF BALANCE THEOREM Introduction to positive and negative edges Outline of implemantation Creating graph, displaying it and counting unstable triangles Moving a network from an unstable to stable state Schelling Model Implementation-1(Introduction) Schelling Model Implementation-2 (Base Code) Schelling Model Implementation-3 (Visualization and Getting a list of boundary and internal nodes) Schelling Model Implementation-4 (Getting a list of unsatisfied nodes) Schelling Model Implementation-5 (Shifting the unsatisfied nodes and visualizing the final graph) CHAPTER - 5 POSITIVE AND NEGATIVE RELATIONSHIPS (INTRODUCTION) Fatman Evolutionary Model- The Base Code (Adding Social Foci) Fatman Evolutionary Model- Implementing Homophily Quantifying the Effect of Triadic Closure Fatman Evolutionary Model- Implementing Closures Fatman Evolutionary Model- Implementing Social Influence Fatman Evolutionary Model- Storing and analyzing longitudnal data Spatial Segregation: An Introduction Spatial Segregation: Simulation of the Schelling Model Spatial Segregation: Conclusion Betweenness Measures and Graph Partitioning Foci Closure and Membership Closure Introduction to Fatman Evolutionary model Fatman Evolutionary Model- The Base Code (Adding people) Selection and Social Influence Interplay between Selection and Social Influence Homophily - Definition and measurement Implementing PageRank Using Points Distribution Method-1 Strong and Weak Relationship - Summary Introduction to Homophily - Should you watch your company ? Visualising Communities using Gephi Tie Strength, Social Media and Passive Engagement Granovetter's Strength of weak ties Triads, clustering coefficient and neighborhood overlap Structure of weak ties, bridges, and local bridges Validation of Granovetter's experiment using cell phone data Embededness Structural Holes Social Capital Finding Communities in a graph (Brute Force Method) Datasets : How to Download? Datasets: Analysing Using Networkx Datasets: Analysing Using Gephi Introduction : Emergence of Connectedness Advanced Material : Emergence of Connectedness Programming Illustration : Emergence of Connectedness Social Network Datasets Datasets: Different Formats Marketing on Social Networks Introduction to Datasets Ingredients Network Searching in a Network Link Prediction The Contagions Google Page Rank Community Detection Using Girvan Newman Algorithm Summary to Datasets Synonymy Network Social Networks: The Challenge Modeling Diffusion (continued) Visualizing coalitions and the evolution Introduction Web Graph Importance of Acquaintances Introduction to Python-2 Introduction to Networkx-2 Introduction to Python-1 Introduction Answer to the puzzle Introduction to Networkx-1 Analyzing basic reproductive number 5 Analyzing basic reproductive number 4 Analyzing basic reproductive number 3 Analyzing basic reproductive number 2 Analysis of basic reproductive number in branching model (The problem statement) Percolation model Basic Reproductive Number Revisited for Complex Networks Comparison between SIR and SIS spreading models SIR and SIS spreading models Modeling epidemics on complex networks Basic Reproductive Number Simple Branching Process for Modeling Epidemics (contd..) Simple Branching Process for Modeling Epidemics Introduction to epidemics (contd..) Epidemics- An Introduction Rich Get Richer - The Long Tail Rich Get Richer - A Possible Reason Forced Versus Random Removal of Nodes (Attack Survivability) Implementing a Random Graph (Erdos- Renyi Model)-2 Implementing a Random Graph (Erdos- Renyi Model)-1 Implementing Rich-getting-richer Phenomenon (Barabasi-Albert Model)-2 Implementing Rich-getting-richer Phenomenon (Barabasi-Albert Model)-1 Summary So Far Rich Get Richer Phenomenon Detecting the Presence of Powerlaw Power Law emerges in WWW graphs Why do Normal Distributions Appear? Introduction to Powerlaw PageRank Explained PageRank as a Matrix Operation Convergence in Repeated Matrix Multiplication- The Details Addition of Two Vectors (Pre-requisite 2) Convergence in Repeated Matrix Multiplication (Pre-requisite 1) Matrix Multiplication (Pre-requisite 1) PageRank, conservation and convergence - Another example PageRank Revisited - Conservation and Convergence PageRank Revisited - Convergence in the Example PageRank Revisited - An example Hubs and Authorities Principle of Repeated Improvement (An example) Principle of Repeated Improvement (A story) Introduction to Hubs and Authorities (A Story) STRUCTURAL BALANCE Small World Effect - An Introduction Milgram's Experiment The Reason The Generative Model Decentralized Search - I Decentralized Search - II Decentralized Search - III Programming illustration- Small world networks : Introduction Base code Making homophily based edges Adding weak ties Plotting change in diameter Programming illustration- Myopic Search : Introduction Myopic Search Myopic Search comparision to optimal search Time Taken by Myopic Search PseudoCores : Introduction How to be Viral Who are the right key nodes? finding the right key nodes (the core) Coding K-Shell Decomposition Coding cascading Model Coding the importance of core nodes in cascading Pseudo core
106107155	Computer Science and Engineering	NOC:Introduction to Cryptology	Dr. Sugata Gangopadhyay	Video	IIT Roorkee	Select Efficien Computation of Jacobi Symbol Primality Testing:Solovay-Stassen Algorithm Iterated Hash Functions Lecture 05- Problem Discussion on Affine cipher and Perfect Secrecy Problem Discussionn Randomized Algorithm and its application on Preimage resistance and collision resistance Cryptographic hash function: Introduction Random Oracle model, Security of hash functions Problem Discussion on Jacobi Symbol Calculation and RSA Cryptosystem Primality testing: Miler-Rabin Algorithm, Legendre Symbol and Jacobi Symbol Complexity analysis of Euclidian Algorithm and RSA Cryptosystem square and multiply algorithm Public Key Cryptology Introduction RSA Cryptosystem Cryptanalysis and its Variants, Linear Attack Problem Discussion Substitution Permutation network, Fiestel Cipher S-Box Theory Product Cipher, Block Cipher, Modes of Operation for Block Cipher Lecture 03- Affine Cipher, Vigenere Cipher Lecture 04- Prefect secrecy, Application of Shift Cipher Lecture 02- Modular arithmetic, shift cipher Lecture 01-Introduction Caeser cipher
106108051	Computer Science and Engineering	Combinatorics	Dr. L. Sunil Chandran	Video	IISc Bangalore	Select Pigeon hole principle - (Part 1) Pigeon hole principle - (Part 2) Pigeon hole principle - (Part 3) Pigeon hole principle - (Part 4) Elementary concepts and basic counting principles Elementary concepts; Binomial theorem; Bijective proofs - Part (1) Bijective proofs – Part (2) Bijective proofs - Part (3); Properties of binomial coefficients; Combinatorial identities - Part (1) Combinatorial identities - Part (2); Permutations of multisets – Part (1) Permutations of multisets – Part (2) Multinomial Theorem, Combinations of Multisets – Part (1) Combinations of Multisets - Part (2) Combinations of Multisets – Part (3), Bounds for binomial coefficients Sterling’s Formula, Generalization of Binomial coefficients - Part (1) Generalization of Binomial coefficients - Part (2) Generalization of Binomial coefficients - Part (3); Double counting - Part (1) Double counting - Part (2) Hall’s Theorem for regular bipartite graphs; Inclusion exclusion principle - Part (1) Inclusion exclusion principle - Part (2) Inclusion exclusion principle - Part (3) Inclusion exclusion principle - Part (4) Inclusion exclusion principle - Part (5) Recurrence Relations - Part (1) Recurrence Relations - Part (2) Recurrence Relations - Part (3) Recurrence Relations - Part (4) Recurrence Relations - Part (5) Generating functions - Part (1) Generating functions - Part (2) Solving recurrence relations using generating functions - Part (1) Solving recurrence relations using generating functions - Part (2) Exponential generating functions - Part (1) Exponential generating functions - Part (2), Partition Number - Part (1) Partition Number - Part (2) Partition Number - Part (3) Partition Number - Part (4); Catalan Numbers - Part (1) Catalans Numbers - Part (2) Catalan Numbers - Part (3), Sterling numbers of the 2nd kind Difference Sequences Sterling Numbers Summary
106108052	Computer Science and Engineering	Compiler Design	Prof. Y.N. Srikanth	Video	IISc Bangalore	Select An Overview of a Compiler - Part 1 An Overview of a Compiler - Part 2 and Run-Time Environments - Part 1 An Overview of a Compiler Part 2 and Run-Time Environments - Part 1 Run-Time Environments - Part 2 Run-Time Environments - Part 3 and Local Optimizations - Part 1 Run-Time Environments Part 3 and Local Optimizations - Part 1 Local Optimizations - Part 2 and Code Generation Part 1 Local Optimizations - Part 2 and Code Generation - Part 1 Code Generation - Part 1 Code Generation - Part 2 Code Generation - Part 3 and Global Register Allocation - Part 1 Code Generation - Part 3 and Global Register Allocation Part 1 Global Register Allocation - Part 2 Global Register Allocation - Part 3 and Implementing Object-Oriented Languages - Part 1 Global Register Allocation - Part 3 and Implementing Object-Oriented Languages Part 1 Implementing Object-Oriented Languages - Part 2 and Introduction to Machine-Independent Optimizations - Part 1 Implementing Object-Oriented Languages - Part 2 and Introduction to Machine-Independent Optimizations Part 1 Introduction to Machine-Independent Optimizations - Part 2 and Data-Flow Analysis - Part 1 Introduction to Machine-Independent Optimizations - Part 2 and Data-Flow Analysis Part 1 Data-Flow Analysis - Part 2 Data-Flow Analysis - Part 3 and Control-Flow Analysis - Part 1 Data-Flow Analysis - Part 3 and Control-Flow Analysis Part 1 Control-Flow Analysis - Part 2 Machine-Independent Optimizations - Part 1 Machine-Independent Optimizations - Part 2 Machine-Independent Optimizations - Part 3 and Data-Flow Analysis: Theoretical Foundation - Part 1 Machine-Independent Optimizations - Part 3 and Data-Flow Analysis: Theoretical Foundation Part 1 Data-Flow Analysis: Theoretical Foundation - Part 2 and Partial Redundancy Elimination - Part 1 Data-Flow Analysis: Theoretical Foundation - Part 2 and Partial Redundancy Elimination Part 1 Partial Redundancy Elimination - Part 2 The Static Single Assignment Form: Construction and Application to Program Optimizations - Part 1 The Static Single Assignment Form: Construction and Application to Program Optimizations - Part 2 The Static Single Assignment Form: Construction and Application to Program Optimizations - Part 3 Automatic Parallelization - Part 1 Automatic Parallelization - Part 2 Automatic Parallelization - Part 3 Automatic Parallelization - Part 4 Instruction Scheduling - Part 1 Instruction Scheduling - Part 2 Instruction Scheduling - Part 3 Software Pipelining Energy-Aware Software Systems - Part 1 Energy-Aware Software Systems - Part 2 Energy-Aware Software Systems - Part 3 Energy-Aware Software Systems - Part 4 Just-In-Time Compilation and Optimizations for .NET CLR Garbage Collection Interprocedural Data-Flow Analysis Worst Case Execution Time - Part 1 Worst Case Execution Time - Part 2
106108054	Computer Science and Engineering	Graph Theory	Dr. L. Sunil Chandran	Video	IISc Bangalore	Select Introduction: Vertex cover and independent set Matchings: Konig’s theorem and Hall’s theorem More on Hall’s theorem and some applications Tutte’s theorem on existence of a perfect matching More on Tutte’s theorem More on Matchings Dominating set, path cover Gallai – Millgram theorem, Dilworth’s theorem Connectivity: 2-connected and 3- connected graphs Menger’s theorem More on connectivity: k- linkedness Minors, topological minors and more on k- linkedness Vertex coloring: Brooks theorem More on vertex coloring Edge coloring: Vizing’s theorem Proof of Vizing’s theorem, Introduction to planarity 5- coloring planar graphs, Kuratowsky’s theorem Proof of Kuratowsky’s theorem, List coloring List chromatic index Adjacency polynomial of a graph and combinatorial Nullstellensatz Chromatic polynomial, k - critical graphs Gallai-Roy theorem, Acyclic coloring, Hadwiger’s conjecture Perfect graphs: Examples Interval graphs, chordal graphs Proof of weak perfect graph theorem (WPGT) Second proof of WPGT, Some non-perfect graph classes More special classes of graphs Boxicity,Sphericity, Hamiltonian circuits More on Hamiltonicity: Chvatal’s theorem Chvatal’s theorem, toughness, Hamiltonicity and 4-color conjecture Network flows: Max flow mincut theorem More on network flows: Circulations Circulations and tensions More on circulations and tensions, flow number and Tutte’s flow conjectures Random graphs and probabilistic method: Preliminaries Probabilistic method: Markov’s inequality, Ramsey number Probabilistic method: Graphs of high girth and high chromatic number Probabilistic method: Second moment method, Lovasz local lemma Graph minors and Hadwiger’s conjecture More on graph minors, tree decompositions
106108055	Computer Science and Engineering	High Performance Computing	Prof. Mathew Jacob	Video	IISc Bangalore	Select Programs and Data Data Representation Registers and Memory Instructions, Addressing Modes A RISC Instruction Set A RISC Instruction Set (contd) Function Call and Return Function Call and Return (contd) Instruction Execution Instruction Execution (contd) Software organization System Calls Virtual memory Virtual memory (contd) Virtual Memory (cont) Process Process scheduling Process lifetime Interprocess communication Concurrent programming Pipelining Pipeline hazards Pipeline hazards (contd) Pipeline hazards (contd.) Cache memory Memory hierarchy Cache operation Cache operation (contd) Cache aware programming Cache aware programming (contd) More on cache Measuring time Program Profiling Secondary storage Files and disks Directories Protection and Performance Parallel architecture Cache coherence MPI programming MPI programming (contd)
106108056	Computer Science and Engineering	Numerical Optimization	Dr. Shirish K. Shevade	Video	IISc Bangalore	Select Introduction Mathematical Background Mathematical Background (contd) One Dimensional Optimization - Optimality Conditions One Dimensional Optimization (contd) Convex Sets Convex Sets (contd) Convex Functions Convex Functions (contd) Multi Dimensional Optimization - Optimality Conditions, Conceptual Algorithm Line Search Techniques Global Convergence Theorem Steepest Descent Method Classical Newton Method Trust Region and Quasi-Newton Methods Quasi-Newton Methods - Rank One Correction, DFP Method i) Quasi-Newton Methods - Broyden Family ii) Coordinate Descent Method Conjugate Directions Conjugate Gradient Method Constrained Optimization - Local and Global Solutions, Conceptual Algorithm Feasible and Descent Directions First Order KKT Conditions Constraint Qualifications Convex Programming Problem Second Order KKT Conditions Second Order KKT Conditions (contd) Weak and Strong Duality Geometric Interpretation Lagrangian Saddle Point and Wolfe Dual Linear Programming Problem Geometric Solution Basic Feasible Solution Optimality Conditions and Simplex Tableau Simplex Algorithm and Two-Phase Method Duality in Linear Programming Interior Point Methods - Affine Scaling Method Karmarkar\'s Method Lagrange Methods, Active Set Method Active Set Method (contd) Barrier and Penalty Methods, Augmented Lagrangian Method and Cutting Plane Method Summary
106108057	Computer Science and Engineering	Pattern Recognition	Prof. M. Narasimha Murty	Web	IISc Bangalore	Select Background Introduction Statistical Pattern Recognition Different Representation Schemes Tree-Based Representations Dissimilarity Measures Distance Between Pattern Collections Fisher’s Discriminant Principal Components as Features Branch and Bound Schemes Sequential Feature Selection Nearest Neighbour Classifier Soft Nearest Neighbour Classifiers Efficient Nearest Neighbour Classifier Ordered Partitions Minimal Distance Classifier Condensed Nearest Neighbour Classifier Modified Condensed Nearest Neighbour Classifier Bayes Classifier Naive Bayes Classifier Bayesian Belief Networks Introduction to Decision Trees Construction of Decision Trees Axis-Parallel and Oblique Decision Trees Learning Decision Trees Introduction to Discriminant Functions Characterization of the Decision Boundary Learning the Discriminant Function Introduction to Support Vector Machines Training Support Vector Machines What is Clustering? Representation of Patterns and Clusters Clustering Process Clustering Algorithms Incremental Clustering Divide-and-Conquer Clustering Introduction to Combining Classifiers AdaBoost for Classification Schemes for Combining Classifiers Combination of Homogeneous Classifiers Document Processing Document Classification and Retrieval
106108058	Computer Science and Engineering	Storage Systems	Dr. K. Gopinath	Video	IISc Bangalore	Select Overview Storage, Processing, Networking Naming and Storing Storage Filesystems Access Architecture, Hard Disks SCSI Fibre Channel Protocol (FCP) FCP, 10Gb Ethernet, iSCSI, TCP NFS, NFSv2 NFSv2, NFSv3, NFSv4, CIFS USB Storage Tiering Mobile/Personal/Organizational - type Storage Parallel/Cloud/Web-scale Storage Long-term Storage Storage interfaces User-Memory-CPU interactions Spinlock, Concurrency Block Layer design FAT, TFAT, F2FS, LFS, FTL Data Structures Abstractions Link & Write Operations ZFS RAID in Filesystems RAID-Z, NetApp RAID4, Flash Filesystems Reliability Performance Security CAP Theorem POSIX/NFS/S3/Zookeeper, ACID Vs. BASE Consistency & Commit problems Paxos Group Communication problem Message Ordering Ordering Models Orderings in Filesystems Semantics of highly scalable filesystems GFS GFS Model GFS functions and operations GFS problems, BigTable Lessons to learn
106108098	Computer Science and Engineering	Data Communications	Prof. H.S. Jamadagni	Web	IISc Bangalore	Select Digital Communication Systems ISDN AsymetricDigital Subscriber Line Communication Systems DSL Q.931 Message format modelling of basic and supplementary
106108099	Computer Science and Engineering	Digital Systems	Prof. N.J. Rao	Web	IISc Bangalore	Select Number Systems and Codes Boolean Algebra and Logic Functions Logic Families Combinational Functions Analysis of Sequential Circuits Designing with Sequential MSIs PLDs Design of Digital Systems
106108100	Computer Science and Engineering	Microprocessors and Microcontrollers	Prof. Krishna Kumar	Web	IISc Bangalore	Select General definitions of mini & micro computers,Overview of 8085 & 8086microprocessor Description of Instructions,Assembly directives,Assembly programs with algorithms Interfacing with RAMs,ROMs and with peripheral ICS and Key boards Architecture of 8087,interfacing with 8086.Data types,instructions and programming Overview of architecture of 8051 microcontroller & overview of architecture of 8096 16 bit controller Description of Instructions,Assembly directives,Assembly programs with algorithms Interfacing with LEDs,ADCs and with DACs Introduction to 80386 and 80486
106108101	Computer Science and Engineering	Operating Systems	Prof. P.C.P. Bhatt	Web	IISc Bangalore	Select Introduction to Operating System File Systems and Management Process and Process Management Memory Management Input Output (IO) Management Resource Sharing and Management Interprocess communication Real time Operating Systems and Microkernels OS and Security Unix Primer Search and Sort Tools AWK Tool in Unix Shell Scripts in UNIX Unix Kernel Architecture Make Tool In UNIX Some Other Tools in UNIX Source Code Control System in UNIX X Windows in UNIX System Administration in UNIX More on LINUX
106108102	Computer Science and Engineering	System Analysis and Design	Prof. V. Rajaraman	Video	IISc Bangalore	Select Lecture 1 Lecture 2 Lecture 3 Lecture 4 Lecture 5 Lecture 6 Lecture 7 Lecture 8 Lecture 9 Lecture 10 Lecture 11 Lecture 12 Lecture 13 Lecture 14 Lecture 15 Lecture 16 Lecture 17 Lecture 18 Lecture 19 Lecture 20 Lecture 21 Lecture 22 Lecture 23 Lecture 24 Lecture 25 Lecture 26 Lecture 27 Lecture 28 Lecture 29 Lecture 30 Lecture 31 Lecture 32 Lecture 33 Lecture 34 Lecture 35 Lecture 36 Lecture 37 Lecture 38 Lecture 39 Lecture 40
106108103	Computer Science and Engineering	System Analysis and Design	Prof. V. Rajaraman	Web	IISc Bangalore	Select Data and Information Systems Analysis and Design Life Cycle Information gathering Feasibility analysis Data Flow Diagrams Process Specification Data input methods Logical Database Design Object oriented systems modeling Designing outputs Document on Web Control ? audit and security of information systems Electronic Commerce Case Tools
106108113	Computer Science and Engineering	Principles of Compiler Design	Prof. Y.N. Srikanth	Video	IISc Bangalore	Select An Overview of a Compiler Lexical Analysis - Part 1 Lexical Analysis - Part 2 Lexical Analysis - Part 3 Syntax Analysis: Context-free Grammars, Pushdown Automata and Parsing Part - 1 Syntax Analysis: Context-free Grammars, Pushdown Automata and Parsing Part - 2 Syntax Analysis: Context-free Grammars, Pushdown Automata and Parsing Part - 3 Syntax Analysis: Context-free Grammars, Pushdown Automata and Parsing Part - 4 Syntax Analysis: Context-free Grammars, Pushdown Automata and Parsing Part - 5 Syntax Analysis: Context-free Grammars, Pushdown Automata and Parsing Part - 6 Syntax Analysis: Context-free Grammars, Pushdown Automata and Parsing Part - 7 Semantic Analysis with Attribute Grammars Part 1 Semantic Analysis with Attribute Grammars Part 2 Semantic Analysis with Attribute Grammars Part 3 Semantic Analysis with Attribute Grammars Part 4 Semantic Analysis with Attribute Grammars Part 5 Intermediate code generation Part 1 Intermediate code generation Part 2 Intermediate code generation Part 3 Intermediate code generation Part 4 (first half of lecture) Run-time environments - 1 (second half of lecture) Run-time environments - 2 Run-time environments - 3 Run-time environments - 4 (first half of lecture) Control-Flow Graph and Local Optimizations - Part 1 (second half of lecture) Control-Flow Graph and Local Optimizations - Part 2 (first half of lecture) Machine code generation - 1 (second half of lecture) Machine code generation - 2 Machine code generation - 3 Machine code generation - 4 (first half of lecture), Implementing object-oriented languages 1 (second half of lecture) Implementing object-oriented languages 2 (first half of lecture) Global register allocation - 1 (second half of lecture) Global register allocation - 2 Global register allocation - 3 Introduction to Machine-Independent Optimizations - 1 Introduction to Machine-Independent Optimizations - 2 Introduction to Machine-Independent Optimizations - 3 Introduction to Machine-Independent Optimizations - 4 Introduction to Machine-Independent Optimizations - 5 Introduction to Machine-Independent Optimizations - 6 Introduction to Machine-Independent Optimizations - 7 (first half of lecture) Instruction Scheduling and Software Pipelining - 1 (second half of lecture) Instruction Scheduling and Software Pipelining - 2 Instruction Scheduling and Software Pipelining - 3 (first part of lecture) Automatic parallelization - 1 (second half of lecture) Automatic parallelization - 2