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Graph Theory Algorithms
This course is tailored for curious minds, aspiring programmers, and problem solvers seeking to elevate their skills. Whether you’re preparing for coding interviews, enhancing your data analysis toolkit, or driven by a passion for algorithmic exploration, our Graph Theory Algorithms course is your gateway to mastering the art of problem-solving in a connected world.
In this Graph Theory Algorithms course, you will delve into the fundamental building blocks of graphs, including Undirected, Directed, Weighted, Complete graphs, and Rooted trees. We’ll equip you with the knowledge to tackle common graph problems such as finding the Shortest Path, assessing Connectivity, identifying Negative Cycles, and solving the Traveling Salesman Problem. Plus, you will explore the power of Depth First Search and Breadth First Search, essential tools in your algorithmic toolkit. Besides, in this Graph Theory Algorithms course, you will learn how to leverage these techniques to navigate grids and find the Shortest Path efficiently. Our course covers the art of Trees, from their storage and representation to beginner-friendly algorithms. In this course, you will discover the secrets of Rooting Trees and uncover the Center(s) of a Tree, essential insights for various applications.
As you move through the Graph Theory Algorithms course, we will guide you through advanced topics like Topological Sorting, Dijkstra’s Algorithm, the Bellman-Ford Algorithm, and the Floyd-Warshall Algorithm. Furthermore, this course will assist you in mastering the art of identifying bridges, articulating points and applying the Tarjan algorithm confidently. You will become familiar with Eulerian Paths and Circuits and learn how to construct a Minimum Spanning Tree using Prim’s Algorithm.
Ready to chart your path to algorithmic excellence? Enrol now and unlock the world of Graph Theory Algorithms today!
Why Choose Teachers Training
Some of our features are:
- This is a dedicated website for teaching
- 24/7 tutor support
- Interactive Content
- Affordable price
- Courses accredited by the UK’s top awarding bodies
- 100% online
- Flexible deadline
Entry Requirements
No formal entry requirements. You need to have:
- Passion for learning
- A good understanding of the English language
- Be motivated and hard-working
- Over the age of 16.
Certification
CPD Certification from The Teachers Training
Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish.
- You can get your digital certificate (PDF) for £4.99 only
- Hard copy certificates are also available, and you can get one for only £10.99
- You can get both PDF and Hard copy certificates for just £12.99!
The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs.
Course Curriculum
| 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 | 00:08:00 | ||
| Module 05: Breadth First Search Shortest Path on a Grid | |||
| Breadth First Search Shortest Path on a Grid | 00:17:00 | ||
| 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 | 00:17:00 | ||
| 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 | ||
Review
Adam Walters
“The course was comprehensive and easy to absorb. I recommend this course.”
Francesca Wong
I thought learning about graphs will be very dull, but this course proved me wrong. It was a delightful experience.
Shannon Davies
This is an excellent course. I liked how the modules were designed to be easy to understand.
Connor Wong
I must say this course has improved my skills a lot. Brilliant course!
Tom Baxter
I can’t believe how much I learned in such a short period of time. Thanks to the instructor!
Georgina Gordon
This course is brilliant. It helped me to understand how to read graphs and different graph theories. A great course for understanding data interpretation.
James Sinclair
I love how is it understandable and flexible this course is. I can learn whenever and wherever I want and take the tests when I am ready. It helped me to maintain my routine and get total control over my development. Highly recommended.
Gabriel Hill
I’m grateful for the opportunity to take part in such a fantastic course. Truly recommend!
Riley Barker
Thank you very much for illustrating graph theory algorithms in such a lovely way. Your simple lectures helped me overcome my fear of the topic’s complexities.
Cameron Dennis
I never thought I would like to learn mathematical representation so much. This course made the graphical representation and understanding graphs so easy. A great course for graph theories.