
Explore the fascinating world of Graph Theory Algorithms, where logic and problem-solving converge to tackle some of the most complex challenges in mathematics and computer science. This course takes you step-by-step through critical aspects of graph theory, whether you’re intrigued by how networks function or looking to deepen your understanding of algorithms. From foundational concepts like Depth First Search and Breadth First Search to advanced topics such as Dijkstra’s Shortest Path Algorithm and the Travelling Salesman Problem, you’ll dive into an extensive range of strategies designed to solve graph-related problems. Master Graph Theory Algorithms by engaging with essential techniques, exploring the dynamics of trees and topological sorting, and navigating through shortest paths, network flows, and spanning trees. With an emphasis on theoretical knowledge, this course ensures that your grasp of Graph Theory Algorithms will be both comprehensive and enduring, empowering you to apply these concepts to a wide range of abstract challenges.
Learning Outcomes
After studying the course materials of the Graph Theory Algorithms there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99. Original Hard Copy certificates need to be ordered at an additional cost of £8.
This Graph Theory Algorithms does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Graph Theory Algorithms was made by professionals and it is compatible with all PC’s, Mac’s, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.
Module 01: Introduction | |||
Introduction | 00:14:00 | ||
Module 02: Common Problem | |||
Common Problem | 00:10:00 | ||
Module 03: Depth First Search | |||
Depth First Search | 00:11:00 | ||
Module 04: Breadth First Search | |||
Breadth First Search | 00:10:00 | ||
Module 05: Breadth First Search Shortest Path on a Grid | |||
Breadth First Search Shortest Path on a Grid | 00:19:00 | ||
Module 06: Trees | |||
Storage and Representation of Trees | 00:10:00 | ||
Beginner Tree Algorithms | 00:10:00 | ||
Rooting Tree | 00:05:00 | ||
Center(s) of a Tree | 00:06:00 | ||
Isomorphisms in Trees | 00:11:00 | ||
Isomorphisms in Trees Source Code | 00:10:00 | ||
Lowest Common Ancestor | 00:11:00 | ||
Module 07: Topological Sort | |||
Topological Sort | 00:14:00 | ||
Shortest and Longest Paths on DAGs | 00:10:00 | ||
Khan’s Algorithm | 00:13:00 | ||
Module 08: Dijkstra | |||
Dijkstra’s Shortest Path Algorithm | 00:25:00 | ||
Dijkstra’s Shortest Path Algorithm Source Code | 00:09:00 | ||
Module 09: Bellman-Ford Algorithm | |||
Bellman-Ford Algorithm | 00:15:00 | ||
Module 10: Floyd-Warshall Algorithm | |||
Floyd-Warshall Algorithm | 00:16:00 | ||
Floyd-Warshall Algorithm Source Code | 00:09:00 | ||
Module 11: Bridge and Algorithm Points | |||
Algorithm to Find Bridges and Articulation Points | 00:20:00 | ||
Algorithm to Find Bridges and Articulation Points Source Code | 00:09:00 | ||
Module 12: Tarjan Algorithm | |||
Tarjan’s Algorithm for Finding Strongly Connected Components | 00:17:00 | ||
Tarjan’s Algorithm for Finding Strongly Connected Components Source Code | 00:07:00 | ||
Module 13: Travelling Salesman Problem (TSP) | |||
Travelling Salesman Problem (TSP) with Dynamic Programming | 00:21:00 | ||
Travelling Salesman Problem (TSP) with Dynamic Programming Source Code | 00:14:00 | ||
Module 14: Eulerian Paths and Circuits | |||
Existence of Eulerian Paths and Circuit | 00:10:00 | ||
Finding Eulerian Paths and Circuits | 00:16:00 | ||
Eulerian Paths Source Code | 00:08:00 | ||
Module 15: Prim’s Minimum Spanning Tree Algorithm | |||
Prim’s Minimum Spanning Tree Algorithm (Lazy Version) | 00:15:00 | ||
Prim’s Minimum Spanning Tree Algorithm ( Eager Version) | 00:15:00 | ||
Prim’s Minimum Spanning Tree Algorithm Source Code ( Eager Version) | 00:09:00 | ||
Module 16: Network Flow | |||
Max Flow Ford-Fulkerson Method | 00:13:00 | ||
Max Flow Ford-Fulkerson Method Source Code | 00:17:00 | ||
Network Flow: Unweighted Bipartite Graph Matching | 00:11:00 | ||
Network Flow: Mice and Owls | 00:08:00 | ||
Network Flow: Elementary Math | 00:11:00 | ||
Network Flow: Edmond-Karp Algorithm Source Code | 00:06:00 | ||
Network Flow: Edmond-Karp Algorithm Source Code | 00:10:00 | ||
Network Flow: Capacity Scaling | 00:10:00 | ||
Network Flow: Capacity Scaling Source Code | 00:06:00 | ||
Network Flow: Dinic’s Algorithm | 00:12:00 | ||
Network Flow: Dinic’s Algorithm Source Code | 00:09:00 |
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