1 1. Algorithms and Computation 1 Lecture 1: Algorithmic Thinking, Peak Finding 2 2. Data Structures and Dynamic Arrays 2 Lecture 2: Models of Computation, Document Distance 3 Introduction to Algorithms - Problem Session 1: Asymptotic Behavior of Functions and Double-ended... 3 Lecture 3: Insertion Sort, Merge Sort 4 3. Sets and Sorting 4 Lecture 4: Heaps and Heap Sort 5 4. Hashing 5 Lecture 5: Binary Search Trees, BST Sort 6 Problem Session 2 (MIT 6.006 Introduction to Algorithms, Spring 2020) 6 Lecture 6: AVL Trees, AVL Sort 7 5. Linear Sorting 7 Lecture 7: Counting Sort, Radix Sort, Lower Bounds for Sorting 8 Problem Session 3 8 Lecture 8: Hashing with Chaining 9 6. Binary Trees, Part 1 9 Lecture 9: Table Doubling, Karp-Rabin 10 7. Binary Trees, Part 2: AVL 10 Lecture 10: Open Addressing, Cryptographic Hashing 11 Problem Session 4 11 Lecture 11: Integer Arithmetic, Karatsuba Multiplication 12 8. Binary Heaps 12 Lecture 12: Square Roots, Newton's Method 13 9. Breadth-First Search 13 Lecture 13: Breadth-First Search (BFS) 14 Quiz 1 review 14 Lecture 14: Depth-First Search (DFS), Topological Sort 15 10. Depth-First Search 15 Lecture 15: Single-Source Shortest Paths Problem 16 11. Weighted Shortest Paths 16 Lecture 16: Dijkstra 17 Problem Session 5 17 Lecture 17: Bellman-Ford 18 12. Bellman-Ford 18 Lecture 18: Speeding up Dijkstra 19 13. Dijkstra 19 Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths 20 Problem Session 7 20 Lecture 20: Dynamic Programming II: Text Justification, Blackjack 21 14. APSP and Johnson 21 Lecture 21: Dynamic Programming III: Parenthesization, Edit Distance, Knapsack 22 Quiz 2 Review 22 Lecture 22: Dynamic Programming IV: Guitar Fingering, Tetris, Super Mario Bros. 23 15. Dynamic Programming, Part 1: SRTBOT, Fib, DAGs, Bowling 23 Lecture 23: Computational Complexity 24 16. Dynamic Programming, Part 2: LCS, LIS, Coins 24 Lecture 24: Topics in Algorithms Research 25 Problem Session 8 25 Recitation 1: Asymptotic Complexity, Peak Finding 26 17. Dynamic Programming, Part 3: APSP, Parens, Piano 26 Recitation 2: Python Cost Model, Document Distance 27 18. Dynamic Programming, Part 4: Rods, Subset Sum, Pseudopolynomial 27 Recitation 3: Document Distance, Insertion and Merge Sort 28 19. Complexity 28 Recitation 5: Recursion Trees, Binary Search Trees 29 Problem Session 9 29 Recitation 6: AVL Trees 30 Quiz 3 Review 30 Recitation 7: Comparison Sort, Counting and Radix Sort 31 20. Course Review 31 Recitation 8: Simulation Algorithms 32 21. Algorithms—Next Steps 32 Recitation 9: Rolling Hashes, Amortized Analysis 33 Recitation 9b: DNA Sequence Matching 34 Recitation 10: Quiz 1 Review 35 Recitation 11: Principles of Algorithm Design 36 Recitation 12: Karatsuba Multiplication, Newton's Method 37 Recitation 13: Breadth-First Search (BFS) 38 Recitation 14: Depth-First Search (DFS) 39 R15. Shortest Paths 40 Recitation 16: Rubik's Cube, StarCraft Zero 41 Recitation 18: Quiz 2 Review 42 Recitation 19: Dynamic Programming: Crazy Eights, Shortest Path 43 Recitation 20: Dynamic Programming: Blackjack 44 Recitation 22: Dynamic Programming: Dance Dance Revolution 45 Recitation 21: Dynamic Programming: Knapsack Problem 46 Recitation 23: Computational Complexity 47 Recitation 24: Final Exam Review