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++

## Cycles

A **cycle** is similar to a path, except that its first and last nodes are identical. In other words, a cycle is like a path that loops back into itself.

The following example graph shows the cycle $a \to c \to d \to a$ marked in blue.

# Cycles

A **cycle** is similar to a path, except that its first and last nodes are identical. In other words, a cycle is like a path that loops back into itself.

The following example graph shows the cycle $a \to c \to d \to a$ marked in blue.

Study further graph theory concepts, such as cycles and connectivity.

Introduction

Graph Representations

Graph Traversal

Shortest Paths

Spanning Trees

Flow Problems

Conclusion

Appendix

Graph Terminology II

Cycles