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Graph Theory Algorithms

A complete overview of graph theory algorithms in computer science and mathematics.

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

  • 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

  • Exposure to computer science fundamentals (e.g: data structures, recursion, data types, classes, OOP)
  • Some prior programming knowledge
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Curriculum

  • Graph Theory Introduction
    14:24
    Preview
  • Problems in Graph Theory
    09:59
    Preview
  • Depth First Search algorithm
    10:39
    Preview
  • Breadth First Search algorithm
    07:45
  • Breadth First Search grid shortest path
    16:50
  • Dijkstra's shortest path algorithm
    24:31
  • Dijkstra's shortest path algorithm | source code
    09:11
  • Topological sort algorithm
    14:04
  • Shortest/longest path on a Directed Acyclic Graph (DAG)
    10:14
  • Bellman-Ford algorithm
    15:16
  • Floyd-Warshall all pairs shortest path algorithm
    15:55
  • Floyd-Warshall all pairs shortest path algorithm | source code
    09:28
  • Bridges & Articulation points
    20:16
  • Bridges & Articulation points | source code
    09:22
  • Tarjan's strongly connected components algorithm
    17:00
  • Tarjan's strongly connected components algorithm | source code
    07:11
  • Travelling Salesman problem
    20:48
  • Travelling Salesman problem | source code
    13:32
  • Existence of Eulerian path and circuits
    09:40
  • Eulerian path algorithm
    15:34
  • Eulerian path source code
    08:17
  • Max Flow Ford Fulkerson | Network Flow
    13:05
  • Max Flow Ford Fulkerson | source code
    17:28
  • Unweighted bipartite matching | Network flow
    11:21
  • Mice and Owls | Network Flow
    08:27
  • Elementary Math | Network Flow
    10:44
  • Edmonds Karp | Network Flow
    09:31
  • Edmonds Karp | Network Flow | Source Code
    05:47
  • Capacity Scaling | Network Flow
    10:09
  • Capacity Scaling | Network Flow | Source Code
    06:23
  • Dinic's Algorithm | Network Flow
    11:39
  • Dinic's Algorithm | Network Flow | Source Code
    09:26
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  • anmol yadav
    anmol yadav

Graph Theory Algorithms
This Course Includes
  • 6.5 hours
  • 32 Lectures
  • Completion Certificate
  • Lifetime Access

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