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Lecture - 1 Overview of the course

Lecture - 2 Framework for Algorithms Analysis

Lecture - 3 Algorithms Analysis Framework - II

Lecture - 4 Asymptotic Notation

Lecture -5 Algorithm Design Techniques : Basics

Lecture -6 Divide And Conquer-I

Lecture -7 Divide And Conquer -II Median Finding

Lecture -8 Divide And Conquer -III Surfing Lower Bounds

Lecture -9 Divide And Conquer -IV Closest Pair

Lecture -10 Greedy Algorithms -I

Lecture - 11 Greedy Algorithms - II

Lecture - 12 Greedy Algorithms - III

Lecture - 13 Greedy Algorithms - IV

Lecture - 14 Pattern Matching - I

Lecture - 15 Pattern Matching - II

Lecture -16 Combinational Search and Optimization I

Lecture - 17 Combinational Search and Optimization II

Lecture -18 Dynamic Programming

Lecture 19 Longest Common Subsequences

Lecture -20 Matric Chain Multiplication

Lecture - 21 Scheduling with Startup and Holding Costs

Lecture - 22 Average case Analysis of Quicksort

Lecture - 23 Bipartite Maximum Matching

Lecture - 24 Lower Bounds for Sorting

Lecture -25 Element Distinctness Lower Bounds

Lecture -26 NP-Completeness-I -Motivation

Lecture - 27 NP - Compliteness - II

Lecture - 28 NP-Completeness - III

Lecture - 29 NP-Completeness - IV

Lecture - 30 NP-Completeness - V

Lecture - 31 NP-Completeness - VI

Lecture - 32 Approximation Algorithms

Lecture - 33 Approximation Algorithms

Lecture - 34 Approximation Algorithms for NP

Description:

Instructor: Prof. Abhiram Ranade, Department of Computer Science, IIT Bombay. This course covers lessons on divide and conquer, greedy algorithm, pattern matching, dynamic programming and approximation algorithms. The main goal of this course teaches you to design algorithms that are fast. In this course, you will study well-defined design techniques through lots of exercises. We hope that at the end of the course you will be able to solve algorithm design problems that you may encounter later in your life.

Design & Analysis of Algorithms

NPTEL

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#Computer Science #Algorithms and Data Structures #Algorithm Design #Algorithms #Algorithm Analysis #Asymptotic Notation #Computational Complexity #Greedy Algorithms #Dynamic programming #Computational Complexity Theory #NP-completeness #Divide-and-Conquer #Approximation Algorithms

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