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Massachusetts Institute of Technology
via MIT OpenCourseWare
1. Course Overview, Interval Scheduling.2. Divide & Conquer: Convex Hull, Median Finding.R1. Matrix Multiplication and the Master Theorem.3. Divide & Conquer: FFT.R2. 2-3 Trees and B-Trees.4. Divide & Conquer: van Emde Boas Trees.5. Amortization: Amortized Analysis.6. Randomization: Matrix Multiply, Quicksort.R4. Randomized Select and Randomized Quicksort.7. Randomization: Skip Lists.8. Randomization: Universal & Perfect Hashing.R5. Dynamic Programming.9. Augmentation: Range Trees.10. Dynamic Programming: Advanced DP.11. Dynamic Programming: All-Pairs Shortest Paths.12. Greedy Algorithms: Minimum Spanning Tree.R6. Greedy Algorithms.13. Incremental Improvement: Max Flow, Min Cut.14. Incremental Improvement: Matching.R7. Network Flow and Matching.15. Linear Programming: LP, reductions, Simplex.16. Complexity: P, NP, NP-completeness, Reductions.R8. NP-Complete Problems.17. Complexity: Approximation Algorithms.18. Complexity: Fixed-Parameter Algorithms.R9. Approximation Algorithms: Traveling Salesman Problem.19. Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees.20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees.R10. Distributed Algorithms.21. Cryptography: Hash Functions.22. Cryptography: Encryption.R11. Cryptography: More Primitives.23. Cache-Oblivious Algorithms: Medians & Matrices.24. Cache-Oblivious Algorithms: Searching & Sorting.
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