Master The Graph Theory Algorithms
Master The Graph Theory Algorithms
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Intermediate
3 Students -
8 hours, 34 minutes
Learning Outcome
- Storage and representation of graphs (networks) on a computer
- Breadth first search algorithm
- Various tree algorithms including: the height or a tree, finding the center of a tree, rooting a tree, and etc…
- Topological sort algorithm
- Bellman Ford’s algorithm
- Finding bridges/articulation points
- Travelling salesman problem (TSP)
Description
Learn how to apply graph theory to solve problems and take your career to the next level with complex specialist skills!
This course is the perfect introduction to graph theory for those looking to establish a career in the field of computer science. It explores how graphs are used in data science in detail, covering common graph theory problems, famous graph traversal algorithms, and much more, with step-by-step guidance on how to store and represent graphs on a computer.
If you are looking to become a data scientist, computer programmer, or analytical chemist, then this course is the perfect stepping stone to a successful career in these fields. The Graph Theory Algorithms course is a fully accredited online qualification ideal for data science graduates.
Why People Love and Enrol the Graph Theory Algorithms Course from One Education
- Eligibility for a CPD-accredited certificate on successful completion of Introduction to Data Analytics with Tableau Course
- Learning materials of our Introduction to Data Analytics with Tableau course contains engaging voiceover and visual elements for your comfort
- Freedom to study at your own pace
- 24/7 access to the Introduction to Data Analytics with Tableau course materials for 12 months
- Full Tutor support on weekdays (Monday – Friday)
Course Design
The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.
You are taught through a combination of
- Video lessons
- Online study materials
Will I receive a certificate of completion?
Upon successful completion, you will qualify for the UK and internationally-recognised certification and you can choose to make your achievement formal by obtaining your PDF Certificate at a cost of £9 and Hard Copy Certificate for £15.
Why study this course
Whether you’re an existing practitioner or aspiring professional, this course will enhance your expertise and boost your CV with key skills and an accredited qualification attesting to your knowledge.
The Master The Graph Theory Algorithms is open to all, with no formal entry requirements. All you need is a passion for learning, a good understanding of the English language, numeracy and IT, and to be over the age of 16.
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 | ||
| Assignment | |||
| Assignment – Graph Theory Algorithms | 00:00:00 | ||
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