Description

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

Requirements

   Basic programming knowledge
   Algorithmic techniques knowledge is preferred (recursion, backtracking, dynamic programming…)
   Data structures knowledge is preferred (hash table, queue, stack, set, heap…)

Last Updated 2/2023