Library/Programming, Data Structures and Algorithms using Python (IIT Madras)/Lesson 63 of 84

Grid Paths

25:00
IIT Madras - B.S. Degree Programme
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Course Contents

  1. 1Introduction to Jupyter Notebooks and Google Colab15:17
  2. 2Implementing Python Code: Part 18:47
  3. 3Python Recap I9:58
  4. 4Python Recap II19:52
  5. 5Python Recap III13:04
  6. 6Exception Handling16:38
  7. 7Classes and Objects18:43
  8. 8Implementing Python Code: Part 27:04
  9. 9Timing Our Code5:43
  10. 10Implementing Python Code: Part 36:09
  11. 11Why Efficiency Matters20:56
  12. 12Implementing Python Code: Part 45:01
  13. 13Analysis of Algorithms35:05
  14. 14Comparing Orders of Magnitude24:01
  15. 15Calculating Complexity: Examples18:09
  16. 16Searching in a List11:11
  17. 17Selection Sort15:43
  18. 18Insertion Sort15:15
  19. 19Merge Sort12:43
  20. 20Analysis of Merge Sort9:50
  21. 21Implementing Searching and Sorting Algorithms10:14
  22. 22Quicksort17:58
  23. 23Analysis of Quicksort10:19
  24. 24Implementing Quicksort3:57
  25. 25Concluding Remarks on Sorting Algorithms6:42
  26. 26Lists vs Arrays (Theory)17:19
  27. 27Designing a Flexible List and Its Operations19:29
  28. 28How Lists Are Implemented in Python18:19
  29. 29How Dictionaries Are Implemented in Python15:26
  30. 30Lists vs Arrays (Implementation)14:12
  31. 31Introduction to Graphs24:57
  32. 32Representing Graphs18:05
  33. 33Breadth First Search (BFS)33:53
  34. 34Depth First Search (DFS)17:19
  35. 35Applications of BFS and DFS31:34
  36. 36Introduction to Directed Acyclic Graphs (DAGs)8:18
  37. 37Topological Sorting20:19
  38. 38Longest Path in DAGs10:17
  39. 39Shortest Paths in Weighted Graphs9:00
  40. 40Single-Source Shortest Paths: Dijkstra's Algorithm24:17
  41. 41Shortest Paths with Negative Weights: Bellman-Ford Algorithm18:22
  42. 42All-Pairs Shortest Paths: Floyd-Warshall Algorithm24:01
  43. 43Minimum Cost Spanning Trees8:57
  44. 44Spanning Trees: Prim's Algorithm23:53
  45. 45Spanning Trees: Kruskal's Algorithm23:36
  46. 46Union-Find Data Structure29:50
  47. 47Priority Queues18:45
  48. 48Heaps39:20
  49. 49Using Heaps in Algorithms28:07
  50. 50Search Trees37:45
  51. 51Balanced Search Trees45:53
  52. 52Greedy Algorithms: Interval Scheduling35:01
  53. 53Greedy Algorithms: Minimizing Lateness29:10
  54. 54Greedy Algorithms: Huffman Coding42:19
  55. 55Divide and Conquer: Counting Inversions25:26
  56. 56Divide and Conquer: Closest Pair of Points29:30
  57. 57Divide and Conquer: Integer Multiplication28:28
  58. 58Divide and Conquer: Recursion Trees19:55
  59. 59Divide and Conquer: Quick Select27:28
  60. 60Implementing Quick Select and Fast Select8:28
  61. 61Dynamic Programming19:00
  62. 62Memoization21:32
  63. 63Grid Paths25:00
  64. 64Common Subwords and Subsequences27:11
  65. 65Edit Distance26:08
  66. 66Matrix Multiplication29:21
  67. 67String Matching11:55
  68. 68String Matching: Boyer-Moore Algorithm15:52
  69. 69String Matching: Rabin-Karp Algorithm16:53
  70. 70String Matching Using Automata17:11
  71. 71String Matching: Knuth-Morris-Pratt Algorithm18:56
  72. 72String Matching: Tries34:18
  73. 73String Matching: Regular Expressions27:42
  74. 74Linear Programming27:57
  75. 75Linear Programming: Production Planning19:52
  76. 76Linear Programming: Bandwidth Allocation11:59
  77. 77Network Flows24:41
  78. 78Reductions14:39
  79. 79Intractability: Checking Algorithms27:22
  80. 80Intractability: P and NP17:13
  81. 81Revision: Weeks 1 to 315:53
  82. 82Revision: Weeks 4 to 619:34
  83. 83Revision: Weeks 7 to 923:25
  84. 84Revision: Weeks 10 to 1120:20
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