Explore the basics of graph theory, learn to represent graphs in C++, and master essential algorithms like DFS and Dijkstra to solve complex optimization problems, including matching and network flow.

Graph algorithms are the core of many real-world applications of computer science,  such as automotive navigation or routing in computer networks. They’re also a common subject in coding interviews at top-tier tech companies.
 
In this course, we’ll learn about the basic concepts of graph theory and how to represent graphs as data structures in code. We’ll study essential graph algorithms such as depth-first search or Dijkstra's algorithm to traverse graphs and find shortest paths. Finally, we’ll learn to solve more complex optimization problems on graphs, such as matching and network flow problems.

Learn Graph Algorithms in C++

Which graph representation requires less memory for storing sparse graphs?

Which graph representation requires less memory for storing sparse graphs?

A and B both offer comparable performance.

You have implemented an algorithm on weighted graphs that frequently needs to update the weight of arbitrary edges $(u, v)$. 

Which graph representation will be more time-efficient for running your algorithm? 

You have implemented an algorithm on weighted graphs that frequently needs to update the weight of arbitrary edges <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="false">(</mo><mi>u</mi><mo separator="true">,</mo><mi>v</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(u, v)</annotation></semantics></math>(u,v).
Which graph representation will be more time-efficient for running your algorithm?

Introduction

Graph Representations

Graph Traversal

Shortest Paths

Spanning Trees

Flow Problems

Conclusion

Appendix

Quiz: Graph Representations