Graph Theory Algorithms
A complete overview of graph theory algorithms in computer science and mathematics.
Updated on Apr, 2024
Language - English
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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