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Content in this video:
00:00 (Chapter0: About this video)

02:10 (Chapter1 Introduction): Algorithms, Analysing Algorithms, Efficiency of an Algorithm, Time and Space Complexity, Asymptotic notations: BigOh, TimeSpace tradeoff Complexity of Algorithms, Growth of Functions, Performance Measurements.

1:20:55 (Chapter2 Sorting and Order Statistics): Concept of Searching, Sequential search, Index Sequential Search, Binary Search Shell Sort, Quick Sort, Merge Sort, Heap Sort, Comparison of Sorting Algorithms, Sorting in Linear Time. Sequential search, Binary Search, Comparison and Analysis Internal Sorting: Insertion Sort, Selection, Bubble Sort, Quick Sort, Two Way Merge Sort, Heap Sort, Radix Sort, Practical consideration for Internal Sorting.

3:14:59 (Chapter3 Divide and Conquer): with Examples Such as Sorting, Matrix Multiplication, Convex Hull and Searching.

3:40:22 (Chapter4 Greedy Methods): with Examples Such as Optimal Reliability Allocation, Knapsack, Huffman algorithm

4:36:05 (Chapter5 Minimum Spanning Trees): Prim’s and Kruskal’s Algorithms

5:00:25 (Chapter6 Single Source Shortest Paths): Dijkstra’s and Bellman Ford Algorithms.

5:25:25 (Chapter7 Dynamic Programming): with Examples Such as Knapsack. All Pair Shortest Paths – Warshal’s and Floyd’s Algorithms, Resource Allocation Problem. Backtracking, Branch and Bound with Examples Such as Travelling Salesman Problem, Graph Coloring, nQueen Problem, Hamiltonian Cycles and Sum of Subsets.

6:52:40 (Chapter8 Advanced Data Structures): RedBlack Trees, B – Trees, Binomial Heaps, Fibonacci Heaps, Tries, Skip List, Introduction to Activity Networks Connected Component.

8:36:05 (Chapter9 Selected Topics): Fast Fourier Transform, String Matching, Theory of NPCompleteness, Approximation Algorithms and Randomized Algorithms