We plan to conduct the lectures in the following manner:
- Before every lecture, links to pre-recorded videos for the material to be covered during the lecture will be shared..
- You are encouraged to see these pre-recorded videos before coming to the lecture.
- During the lecture, the instructor will go over the pre-recorded material, conduct discussions, and answer questions from students on the material.
- The video links of the respective lectures and the slides will also be shared after the lecture.
- Please note that as per zoom policy, all zoom lecture recordings will be auto-deleted within one month from the recording date.

Week Topics Slides/Videos Lecture recordings Reading
Week-01
(30 Mar - 03 Apr)
01. Introduction: Analysing algorithms
02. Graph Algorithms: Why graphs?
03. Graph Algorithms: Graph representations
04. Graph Algorithms: Reachability
05. Graph Algorithms: Undirected connectivity
01. [PDF] [Youtube]
02. [PDF] [Youtube]
03. [PDF] [Youtube]
04. [PDF] [Youtube]
05. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Chapter 0,
Section 3.1, 3.2
Week-02
(06 Apr - 10 Apr)
06,07. Graph Algorithms: DFS
08. Graph Algorithms: DFS
06,07. [PDF] [Youtube]
08. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Section 3.2, 3.3, 3.4.
Week-03
(13 Apr - 17 Apr)
09. Graph Algorithms: Max bandwidth
10. Graph Algorithms: BFS
11. Graph Algorithms: Dijkstra
12. Graph Algorithms: Dijkstra Running Time
09. [PDF] [Youtube]
10. [PDF] [Youtube]
11. [PDF] [Youtube]
12. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue
Chapter 4,
Section 4.1, 4.2, 4.3, 4.4, 4.5
Week-04
(20 Apr - 24 Apr)
13. Greedy Algorithms: Overview
14. Greedy Algorithms: Scheduling Problem
15. Greedy Algorithms: Another Scheduling Problem
13. [PDF] [Youtube]
14. [PDF] [Youtube]
15. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Chapter 5: Greedy Algorithms
Chapter 9: Approximation Algorithms
Week-05
(27 Apr - 01 May)
16. Greedy Algorithms: Proof Strategies
17. Greedy Algorithms: Kruskal's MST Algorithm
18. Greedy Algos: Data Structs for Disjoint Sets
19. (optional) Greedy Algos: Amortized Analysis
20. (optional) Approximation: Introduction
16. [PDF] [Youtube]
17. [PDF] [Youtube]
18. [PDF] [Youtube]
19. [PDF] [Youtube]
20. [PDF] [Youtube1]
[Youtube2]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Chapter 5: Greedy Algorithms
Chapter 9: Approximation Algorithms
Week-06
(04 May - 08 May)
21. D&C: Multiplication
22. D&C: Master Theorem
23. D&C: Sorting and Selection
24. D&C: More examples
21. [PDF] [Youtube]
22. [PDF] [Youtube]
23. [PDF] [Youtube]
24. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Chapter 2: Divide and Conquer
Week-07
(11 May - 15 May)
25. Intro to Dynamic Programming: Back-Tracking
25. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed
8123 Tue Thu
Chapter 2: Divide and Conquer
Chapter 9: Back-Tracking
Week-08
(18 May - 22 May)
26. Dynamic Programming I
27. Dynamic Programming II
28. Dynamic Programming: String Algorithms
26. [PDF] [Youtube]
27. [PDF] [Youtube1]
[Youtube2]
28. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Chapter 6: Dynamic Programming
Chapter 4: Dynamic Programming (Bellman-Ford)
Week-09
(25 May - 29 May)
29. Dynamic Programming: Shortest Paths
29. [PDF] [Youtube]
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Chapter 6: Dynamic Programming
Chapter 4: Dynamic Programming (Bellman-Ford)
Chapter 7: Network Flow / Linear Programming
Week-10
(01 Jun - 05 Jun)
30. Network Flow
31. NP-Completeness
30. [PDF] [Youtube]
31. [PDF] OPTIONAL
8121 Mon Wed Fri
8122 Mon Wed Fri
8123 Tue Thu
Chapter 7: Network Flow / Linear Programming
Chapter 8: NP-Completeness