AI-powered learning
Save this course
Learn Graph Algorithms in C++
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.
4.5
42 Lessons
5h
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- Learn how graphs can be represented as data structures
- Traverse graphs using search algorithms
- Find the shortest paths in graphs
- Find maximum matchings
- Solve flow problems
- Compute minimum spanning trees
Learning Roadmap
1.
Introduction
Introduction
Get familiar with fundamental graph concepts, key terminology, and algorithm efficiency analysis.
2.
Graph Representations
Graph Representations
Discover the logic behind graph representations, including adjacency matrices, adjacency lists, and their comparisons.
3.
Graph Traversal
Graph Traversal
9 Lessons
9 Lessons
Work your way through DFS and BFS implementations, topological sort, SCCs, and bipartite graphs.
4.
Shortest Paths
Shortest Paths
7 Lessons
7 Lessons
Break down complex ideas on shortest path algorithms and their implementation techniques.
5.
Spanning Trees
Spanning Trees
5 Lessons
5 Lessons
Deepen your knowledge of minimum spanning trees, Kruskal's algorithm, and maximum spanning tree challenges.
6.
Flow Problems
Flow Problems
6 Lessons
6 Lessons
Focus on solving max flow problems, Ford-Fulkerson method, and bipartite matching challenges.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
ABOUT THIS COURSE
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.
ABOUT THE AUTHOR
Lukas Huwald
Machine learning engineer & functional programming enthusiast.
Trusted by 2.9 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
V
Vinay Krishnaiah
Software Developer
Built for 10x Developers
No Passive Learning
Learn by building with project-based lessons and in-browser code editor
Personalized Roadmaps
The platform adapts to your strengths & skills gaps as you go
Future-proof Your Career
Get hands-on with in-demand skills
AI Code Mentor
Write better code with AI feedback, smart debugging, and "Ask AI"
MAANG+ Interview Prep
AI Mock Interviews simulate every technical loop at top companies
Free Resources
