Introduces computational complexity, P and EXP, polynomial versus exponential time, decision problems, and examples such as chess and negative-weight-cycle detection.
Save to open this file
MIT 6.006: Introduction to Algorithms
All
- 01-Algorithms and Computation
01-Algorithms and Computation
- 02-Data Structures and Dynamic Arrays
- 03-Sets and Sorting
- 04-Hashing
- 05-Linear Sorting
- 06-Binary Trees, Part 1
- 07-Binary Trees, Part 2: AVL
- 08-Binary Heaps
- 09-Breadth-First Search
- 10-Depth-First Search
- 11-Weighted Shortest Paths
- 12-Bellman-Ford
- 13-Dijkstra
- 14-APSP and Johnson
- 15-Dynamic Programming, Part 1: SRTBOT, Fib, DAGs, Bowling
- 16-Dynamic Programming, Part 2: LCS, LIS, Coins
- 17-Dynamic Programming, Part 3: APSP, Parens, Piano
- 18-Dynamic Programming, Part 4: Rods, Subset Sum, Pseudopolynomial
- 19-Complexity
- 20-Course Review