Computer Science: Graph Theory Algorithms

Description

This comprehensive course on Computer Science: Graph Theory Algorithms will deepen your understanding on this topic.

After successful completion of this course you can acquire the required skills in this sector. This Computer Science: Graph Theory Algorithms comes with accredited certification, which will enhance your CV and make you worthy in the job market.

So enrol in this course today to fast track your career ladder.

You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.

There is no experience or previous qualifications required for enrolment on this Computer Science: Graph Theory Algorithms. It is available to all students, of all academic backgrounds.

Our Computer Science: Graph Theory Algorithms is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.

There is no time limit for completing this course, it can be studied in your own time at your own pace.

Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc.

17 sections • 44 lectures • 08:37:00 total length

•Promo: 00:03:00

•Introduction: 00:14:00

•Common Problem: 00:10:00

•Depth First Search: 00:11:00

•Breadth First Search: 00:08:00

•Breadth First Search Shortest Path on a Grid: 00:17:00

•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: 00:17:00

•Topological Sort: 00:14:00

•Shortest and Longest Paths on DAGs: 00:10:00

•Khan's Algorithm: 00:13:00

•Dijkstra's Shortest Path Algorithm: 00:25:00

•Dijkstra's Shortest Path Algorithm Source Code: 00:09:00

•Bellman-Ford Algorithm: 00:15:00

•Floyd-Warshall Algorithm: 00:16:00

•Floyd-Warshall Algorithm Source Code: 00:09:00

•Algorithm to Find Bridges and Articulation Points: 00:20:00

•Algorithm to Find Bridges and Articulation Points Source Code: 00:09:00

•Tarjan's Algorithm for Finding Strongly Connected Components: 00:17:00

•Tarjan's Algorithm for Finding Strongly Connected Components Source Code: 00:07:00

•Travelling Salesman Problem (TSP) with Dynamic Programming: 00:21:00

•Travelling Salesman Problem (TSP) with Dynamic Programming Source Code: 00:14:00

•Existence of Eulerian Paths and Circuit: 00:10:00

•Finding Eulerian Paths and Circuits: 00:16:00

•Eulerian Paths Source Code: 00:08:00

•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

•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: 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