Chapter 1 - Introduction
Chapter 2 - Algorithm Efficiency
Chapter 3 - Brute Force and Exhaustive Search
Chapter 4 - Decrease-and-Conquer
Chapter 5 - Divide-and-Conquer
Chapter 6 - Transform-and-Conquer
Intro Video
Chapter 7 - Space and Time Trade-Offs
Chapter 8 - Dynamic Programming
Chapter 9 - Greedy Technique
Chapter 10 - Iterative Improvement
Chapter 11 - Limitations of Algorithm Power
Chapter 12 - Coping with the Limitations
Extra
Lecture Notes
- Chapter 01 Intro
- Chapter 01 Problem Solving
- Chapter 01 Problem Solving datastructures cont
- Chapter 02 Big O
- Chapter 02 Big O
- Chapter 02 Hanoi Tower
- Chapter 02 Fib and Stirling
- Chapter 02 Fib and Restricted Hanoi
- Chapter 03 BruitForce, Selection, Bubble Sort
- Chapter 03 ExhaustiveSearch, CyclicHanoi, ConvexHull, W07
- Chapter 03 ExhaustiveSearch, CyclicHanoi
- Chapter 03 ExhaustiveSearch, CyclicHanoiHelp
- Chapter 03 DFS, BFS
- Chapter 04 Insertion Sort
- Chapter 04 ShellSort, DAG, Topological
- Chapter 04 BinSearch, Fake Coin, Russian Peasant
- Chapter 04 Quick Select
- Chapter 05 Master Therom and QuickSort
- Chapter 06 Tran Conc, Guass
- Chapter 06 AVL
- Chapter 06 2 3 Trees
- Chapter 06 Heap Sort
- Chapter 07 Sorting By Comp
- Chapter 07 Horsepool
- Chapter 07 Boyer_Hashing_DoHashinbByHand_AddDeleteAlgorithmForClosedHashing
- Chapter 07 BTree
- Chapter 08 DP CoinRobot
- Chapter 08 Knapsack OptimalBinarySearh
- Chapter 08 Warshall Floyd
- Chapter 09 Greedy MST Prim
- Chapter 09 Greedy Kruskal UnionFind
- Chapter 09 Greedy Dijkstra Huffman
- Chapter 10 ItImp Simplex
- Chapter 10 ItImp MaxFlow
- Chapter 10 ItImp Byparttite
- Chapter 11 LowerBounds, DecisionTrees
- Chapter 11 NP
- Chapter 12 Coping with Limitations