Graph Theory Algorithms
A complete overview of graph theory algorithms in computer science and mathematics.
Teaching & Academics,Engineering,Algorithms
Lectures -33
Duration -6.5 hours
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Course Description
This course provides a complete introduction to Graph Theory algorithms in computer science.
Topics covered in these videos include: how to store and represent graphs on a computer; common graph theory problems seen in the wild; famous graph traversal algorithms (DFS & BFS); Dijkstra's shortest path algorithm (both the lazy and eager version); what a topological sort is, how to find one, and places it's used; learning about detecting negative cycles and finding shortest paths with the Bellman-Ford and Floyd-Warshall algorithms; discovering bridges and articulation points in graphs; understanding and detecting strongly connected components with Tarjan's algorithm, and finally solving the travelling salesman problem with dynamic programming.
Who this course is for:
- Anybody ready for a deep dive into graph theory
Goals
What will you learn in this course:
- Storage and representation of graphs (networks) on a computer
- Common graph theory problems
- Breadth first search algorithm
- Depth first search algorithm
- Dijkstra's algorithm
- Topological sort algorithm
- Shortest/longest path on a acyclic graph
- Bellman Ford's algorithm
- Floyd-Warshall all pairs shortest path algorithm
- Finding bridges/articulation points
- Finding strongly connected components (Tarjan's)
- Travelling salesman problem (TSP)
Prerequisites
What are the prerequisites for this course?
- Exposure to computer science fundamentals (e.g: data structures, recursion, data types, classes, OOP)
- Some prior programming knowledge
Curriculum
Check out the detailed breakdown of what’s inside the course
Graph Theory Algorithms
32 Lectures
- Graph Theory Introduction 14:24 14:24
- Problems in Graph Theory 09:59 09:59
- Depth First Search algorithm 10:39 10:39
- Breadth First Search algorithm 07:45 07:45
- Breadth First Search grid shortest path 16:50 16:50
- Dijkstra's shortest path algorithm 24:31 24:31
- Dijkstra's shortest path algorithm | source code 09:11 09:11
- Topological sort algorithm 14:04 14:04
- Shortest/longest path on a Directed Acyclic Graph (DAG) 10:14 10:14
- Bellman-Ford algorithm 15:16 15:16
- Floyd-Warshall all pairs shortest path algorithm 15:55 15:55
- Floyd-Warshall all pairs shortest path algorithm | source code 09:28 09:28
- Bridges & Articulation points 20:16 20:16
- Bridges & Articulation points | source code 09:22 09:22
- Tarjan's strongly connected components algorithm 17:00 17:00
- Tarjan's strongly connected components algorithm | source code 07:11 07:11
- Travelling Salesman problem 20:48 20:48
- Travelling Salesman problem | source code 13:32 13:32
- Existence of Eulerian path and circuits 09:40 09:40
- Eulerian path algorithm 15:34 15:34
- Eulerian path source code 08:17 08:17
- Max Flow Ford Fulkerson | Network Flow 13:05 13:05
- Max Flow Ford Fulkerson | source code 17:28 17:28
- Unweighted bipartite matching | Network flow 11:21 11:21
- Mice and Owls | Network Flow 08:27 08:27
- Elementary Math | Network Flow 10:44 10:44
- Edmonds Karp | Network Flow 09:31 09:31
- Edmonds Karp | Network Flow | Source Code 05:47 05:47
- Capacity Scaling | Network Flow 10:09 10:09
- Capacity Scaling | Network Flow | Source Code 06:23 06:23
- Dinic's Algorithm | Network Flow 11:39 11:39
- Dinic's Algorithm | Network Flow | Source Code 09:26 09:26
Instructor Details
William Fiset
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