Design and Analysis of Algorithms (M-I-T)

1. Course Overview, Interval Scheduling (M-I-T)

10. Dynamic Programming: Advanced DP (M-I-T)

11. Dynamic Programming: All-Pairs Shortest Paths (M-I-T)

12. Greedy Algorithms: Minimum Spanning Tree (M-I-T)

13. Incremental Improvement: Max Flow, Min Cut (M-I-T)

14. Incremental Improvement: Matching (M-I-T)

15. Linear Programming: LP, reductions, Simplex (M-I-T)

16. Complexity: P, NP, NP-completeness, Reductions (M-I-T)

R10. Distributed Algorithms (M-I-T)

R11. Cryptography: More Primitives (M-I-T)

17. Complexity: Approximation Algorithms (M-I-T)

R2. 2-3 Trees and B-Trees (M-I-T)

18. Complexity: Fixed-Parameter Algorithms (M-I-T)

19. Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees (M-I-T)

R4. Randomized Select and Randomized Quicksort (M-I-T)

2. Divide & Conquer: Convex Hull, Median Finding (M-I-T)

R5. Dynamic Programming (M-I-T)

20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees (M-I-T)

R6. Greedy Algorithms (M-I-T)

21. Cryptography: Hash Functions (M-I-T)

R7. Network Flow and Matching (M-I-T)

R8. NP-Complete Problems (M-I-T)

22. Cryptography: Encryption (M-I-T)

23. Cache-Oblivious Algorithms: Medians & Matrices (M-I-T)

R9. Approximation Algorithms: Traveling Salesman Problem (M-I-T)