NOC:Introduction to Algorithms and Analysis

Lecture 1 - Insertion sort

Lecture 2 - Analysis of Insertion Sort

Lecture 3 - Asymptotic Analysis

Lecture 4 - Recurrence of Merge Sort

Lecture 5 - Substitution Method

Lecture 6 - The Master Method

Lecture 7 - Divide-and-Conquer

Lecture 8 - Divide-and-Conquer (Continued...)

Lecture 9 - Straseen's Algorithms

Lecture 10 - QuickSort

Lecture 11 - Analysis of Quicksort

Lecture 12 - Randomized Quicksort

Lecture 13 - Heap

Lecture 14 - Heap Sort

Lecture 15 - Decision Tree

Lecture 16 - Linear time Sorting

Lecture 17 - Radix Sort and Bucket Sort

Lecture 18 - Order Statistics

Lecture 19 - Randomised Order Statistics

Lecture 20 - Worst case linear time order statistics

Lecture 21 - Hash Function

Lecture 22 - Open Addressing

Lecture 23 - Universal Hashing

Lecture 24 - Perfect Hashing

Lecture 25 - Binary Search Tree (BST) Sort

Lecture 26 - Randomly build BST

Lecture 27 - Red Black Tree

Lecture 28 - Red Black Tree (Continued...)

Lecture 29 - Augmentation of data structure

Lecture 30 - Interval trees

Lecture 31 - Fixed universe successor

Lecture 32 - Van Emde Boas data structure

Lecture 33 - Amortized analysis

Lecture 34 - Computational Geometry

Lecture 35 - Computational Geometry (Continued...)

Lecture 36 - Dynamic Programming

Lecture 37 - Longest common subsequence

Lecture 38 - Graphs

Lecture 39 - Prim's Algorithms

Lecture 40 - Graph Search

Lecture 41

Lecture 42

Lecture 43

Lecture 44

Lecture 45

Lecture 46

Lecture 47

Lecture 48

Lecture 49

Lecture 50

Lecture 51

Lecture 52 - Union-Find

Lecture 53 - Augmented disjoint set data structure

Lecture 54 - Network flow

Lecture 55 - Network Flow (Continued...)

Lecture 56 - Network Flow (Continued...)

Lecture 57 - More on Dynamic Programming

Lecture 58 - More on Dynamic Programming (Continued...)

Lecture 59 - Computational Complexity

Lecture 60 - Computational Complexity (Continued...)