Duration : 11.5 hours
What you’ll learn
- Competitive Programming
- Algorithms
- Data Structures
- Programming
- Merge Sort, QuickSort, Count Sort, Bucket Sort
- Linear Search, Binary Search, QuickSelect, Two Pointer Technique
- Stacks, Queues, Hash Tables, Hash Sets, Heap-Based Structures, Binary Search Tree-Based Data Structures, Coordinate Compression, Custom Comparators
- Hash Functions, Collisions, Rabin-Karp, Sliding Window Technique
- Greedy Algorithms
- Iterative Complete Search, Backtracking, Permutations, Subsets, Pruning
- Divide and Conquer, Binary Search the Answer, the Bisection Method
- Dynamic Programming: Competitive Approach, Top-Down and Bottom-Up DP, Space Optimisation, Prefix Sums, Backtracking to Find Solutions
- Graph Representation: Adjacency Lists, Adjacency Matrices, Edge Lists, Weighted and Unweighted Graphs
- Graph Exploration: Breadth-First Search (BFS), Depth-First Search (DFS), Connected Components, Multi-Source BFS
- Directed Graphs and Cycles: Topological Sort, Strongly Connected Components, BFS for Single-Source Shortest Paths
- Shortest Paths: Dijkstra, Floyd-Warshall’s, Bellman-Ford and Negative-Weight Cycles, Arbitrages and the Logarithm Trick
- Trees: Special Properties, Faster Shortest Paths, Diameter, Minimum Spanning Trees
- Union-Find Disjoint Sets: Optimised Implementation, Kruskal’s Algorithm, Minimum Spanning Tree Variants
- Strings: Dynamic Programming on Strings, Longest Common Subsequence, Edit Distance, Longest Palindromic Substring, Tries, Suffix Tries
- Game Theory: States and Transitions, Minimax for Optimal Game Playing, Dynamic Programming To Recover Optimal Strategies
- Approaching Interactive Problems
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