Graph theory algorithms visualized | Udemy


Graph theory algorithms visualized | Udemy
English | Size: 3.09 GB
Genre: eLearning

Unleash the power of graph theory with cutting-edge algorithms

What you’ll learn
Learn graphs terminology and representation
Learn graph traversal
Learn algorithms related to various graph theory topics (shortest paths, minimum spanning trees…)
Solve graph related coding interview problems

This Graph theory algorithms will teach students the fundamental concepts and algorithms of graph theory with real life examples and eye-appealing visualizations. The course will cover topics such as graph representation, graph traversal, topological sort, shortest paths, minimum spanning trees, graph coloring… With a total of more than 20 covered algorithms.

Discussed algorithms will be implemented in detail by using a programming language to give a better understanding for students. Captions, practice problems, quizzes, slides, and source code will also be here to make the learning experience way better.

By the end of the course, students will have a strong understanding of graph algorithms and be able to apply their knowledge to solve problems in computer science, mathematics, and beyond.

This course is ideal for students who are looking to pursue careers in computer science, mathematics, or related fields, as well as for professionals who want to expand their knowledge of graph theory algorithms.

Covered algorithms:

Graph traversal:

Depth-first search

Breadth-first search

Topological sorting:

Depth-first search based topological sort

Breadth-first search based topological sort (Kahn’s algorithm)

Shortest path:

Dijkstra’s algorithm

Bellman-Ford algorithm

Floyd-Warshall algorithm

Johnson’s algorithm

Shortest path for unweighted graphs algorithm

Shortest path for directed acyclic graphs (1st approach) algorithm

Shortest path for directed acyclic graphs (2nd approach) algorithm

Trees and minimum spanning trees:

Spanning tree algorithm

Graph to out-tree algorithm

Prim’s algorithm

Kruskal’s algorithm

Eulerian/Hamiltonian paths and cycles:

Hierholzer’s algorithm

Hamiltonian cycle backtracking algorithm

Graph coloring:

2-colorability algorithm

k-colorability backtracking algorithm

Greedy coloring algorithm

Welsh-Powell heuristic

DSatur heuristic

Who this course is for:
Computer science students
Data science beginners
Software development beginners

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