Introduction to algorithms and analysis Training

1 / Lecture 1 : Insertion sort

2 / Lecture 2 : Analysis of Insertion Sort

3 / Lecture 3 : Asymptotic Analysis

4 / Lecture 4 : Recurrence of Merge Sort

5 / Lecture 5 : Substitution Method

6 / Lecture 6 : The Master Method

7 / Lecture 7 : Divide-and-Conquer

8 / Lecture 8 : Divide-and-Conquer (Contd.)

9 / Lecture 9 : Straseen’s Algorithms

10 / Lecture 10 : QuickSort

11 / Lecture 11 : Analysis of Quicksort.

12 / Lecture 12 : Randomized Quicksort

13 / Lecture 13 : Heap

14 / Lecture 14 : Heap Sort

15 / Lecture 15 : Decision Tree

16 / Lecture 16 : Linear time Sorting

17 / Lecture 17 : Radix Sort & Bucket Sort

18 / Lecture 18 : Order Statistics

19 / Lecture 19 : Randomised Order Statistics

20 / Lecture 20 : Worst case linear time order statistics

21 / Lecture 21 : Hash Function

22 / Lecture 22 : Open Addressing

23 / Lecture 23 : Universal Hashing

24 / Lecture 24 : Perfect Hashing

25 / Lecture 25 : Binary Search Tree (BST) Sort

26 / Lecture 26 : Randomly build BST

27 / Lecture 27 : Red Black Tree

28 / Lecture 28 : Red Black Tree (Contd.)

29 / Lecture 29 : Augmentation of data structure

30 / Lecture 30 : Interval trees

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36 / Lecture 36 : Dynamic Programming

37 / Lecture 37 : Longest common subsequence

38 / Lecture 38 : Graphs

39 / Lecture 39 : Prim’s Algorithms

40 / Lecture 40 : Graph Search

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42 / Lecture 42

43 / Lecture 43

44 / Lecture 44

45 / Lecture 45

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