Competitive Programming
Notes to return to. Ideas to build on.
Course notes
- Getting Started with Competitive Programming
- Lecture 0 · Welcome and Initial Setup
- Lecture 1 · Ad hoc and Implementation
- Lecture 2 · M 2 (Reversort Engineering)
- Lecture 3 · M 03 (Numbers Game)
- Lecture 4 · M 4 (Will It Stop?)
- Lecture 5 · M 1 (Trouble Sort)
- Lecture 6 · M 2 (The Meeting Place Cannot be
- Lecture 7 · M 3 (Magic Ship)
- Lecture 8 · M 4 (Simple Skewness)
- Lecture 9 · M 1 (Pancake Flipping)
- Lecture 10 · M 2 (Islands War)
- Lecture 11 · M 3 (Stable Marriage-I)
- Lecture 12 · M 3 (Stable Marriage-II)
- Lecture 13 · M 4 (When Greedy Does Not Work - Coin Change)
- Lecture 14 · M 4 (When Greedy Does Not Work - Guarding a Museum)
- Lecture 15 · M 4 (When Greedy Does Not Work - Traveling Salesman)
- Lecture 16 · M 1 (An Introduction)
- Lecture 17 · M 1 (An Introduction-Part II)
- Lecture 18 · M 1 (An Introduction-Part III)
- Lecture 19 · M 2 (Destroying Array-I)
- Lecture 20 · M 2 (Destroying Array-II)
- Lecture 21 · M 3 (War-I)
- Lecture 22 · M 3 (War-II)
- Lecture 23 · M 3 (War-III)
- Lecture 24 · M 1 (Graph Traversals)
- Lecture 25 · M 1 (BFS and DFS)
- Lecture 26 · M 2 (Mahmoud and Ehab and the bipartiteness)
- Lecture 27 · M 3 (Cover It!)
- Lecture 28 · M 4 (Diamond Inheritance)
- Lecture 29 · M 1 (Dijkstra’s Algorithm)
- Lecture 30 · M 1 (Dijkstra’s Algorithm)
- Lecture 31 · M 1 (Dijkstra’s Algorithm-Sending Email)
- Lecture 32 · M 1 (Modified Dijkstra)
- Lecture 33 · M 2 (Wormholes [Bellman-Ford | Negative
- Lecture 34 · M 2 (Wormholes [Bellman-Ford | Negative
- Lecture 35 · M 3 (APSP [Floyd-Warshall] | Page Hopping)
- Lecture 36 · M 3 (APSP [Floyd-Warshall] | Page Hopping)
- Lecture 37 · M 1 (Blingor’s Network | Foundations
- Lecture 38 · M 1 (Prim’s Algorithm)
- Lecture 39 · M 1 (Kruskal’s Algorithm)
- Lecture 40 · M 2 (Cherries Mesh)
- Lecture 41 · M 3 (Hierarchy)
- Lecture 42 · M 4 (Island Hopping)
- Lecture 43 · M 1 (Introduction)
- Lecture 44 · M 1 (Ford-Fulkerson for Max Flow)
- Lecture 45 · M 1 (Implementing Edmonds-Karp)
- Lecture 46 · M 2 (Maximum Matching via MaxFlow)
- Lecture 47 · Sport Elimination via MaxFlow
- Lecture 48 · MaxFlow-MinCut Duality
- Lecture 49 · Police Chase
- Lecture 50 · Minimum Vertex Cover via Max Flow | SAM I AM (UVA 11419)
- Lecture 51 · Memoization | Frogs 1 (AtCoder Educational DP Contest)
- Lecture 52 · Introduction | Frogs 1 (AtCoder Educational DP Contest)
- Lecture 53 · Bottom-Up DP | Dice Combinations (CSES Problem Set)