- Home
- Courses
- Engineering
- Design & Analysis of Algorithms
Curriculum
- 1 Section
- 33 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Design & Analysis of Algorithms33
- 2.1Lecture 1: Overview
- 2.2Lecture 2: Framework for Algorithms Analysis
- 2.3Lecture 3: Algorithms Analysis Framework – II
- 2.4Lecture 4: Asymptotic Notation
- 2.5Lecture 5: Algorithm Design Techniques : Basics
- 2.6Lecture 6: Divide And Conquer – I
- 2.7Lecture 7: Divide And Conquer -II Median Finding
- 2.8Lecture 8: Divide And Conquer -III Surfing Lower Bounds
- 2.9Lecture 9: Divide And Conquer -IV Closest Pair
- 2.10Lecture 10: Greedy Algorithms – I
- 2.11Lecture 11: Greedy Algorithms – II
- 2.12Lecture 12: Greedy Algorithms – III
- 2.13Lecture 13: Greedy Algorithms – IV
- 2.14Lecture 14: Pattern Matching – I
- 2.15Lecture 15: Pattern Matching – II
- 2.16Lecture 16: Combinational Search and Optimization I
- 2.17Lecture 17: Combinational Search and Optimization II
- 2.18Lecture 18: Dynamic Programming
- 2.19Lecture 19: Longest Common Subsequences
- 2.20Lecture 20: Matric Chain Multiplication
- 2.21Lecture 21: Scheduling with Startup and Holding Costs
- 2.22Lecture 22: Bipartite Maximum Matching
- 2.23Lecture 23: Lower Bounds for Sorting
- 2.24Lecture 24: Element Distinctness Lower Bounds
- 2.25Lecture 25: NP-Completeness-I -Motivation
- 2.26Lecture 26: NP – Completeness- II
- 2.27Lecture 27: NP – Completeness- III
- 2.28Lecture 28: NP – Completeness- IV
- 2.29Lecture 29: NP – Completeness- V
- 2.30Lecture 30: NP – Completeness- VI
- 2.31Lecture 31: Approximation Algorithms
- 2.32Lecture 32: Approximation Algorithms
- 2.33Lecture 33: Approximation Algorithms for NP