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Learn Graph Algorithms in C++ - AI-Powered Course
4.5
Intermediate
5h
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.
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Overview
Content
Reviews
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.
Graph algorithms are the core of many real-world applications of computer science, such as automotive navigation or routing in ...Show More
WHAT YOU'LL LEARN
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
Learn how graphs can be represented as data structures
Show more
Content
42 Lessons11 Quizzes5 Challenges
1.
Introduction
7 Lessons
Get familiar with fundamental graph concepts, key terminology, and algorithm efficiency analysis.
2.
Graph Representations
6 Lessons
Discover the logic behind graph representations, including adjacency matrices, adjacency lists, and their comparisons.
3.
Graph Traversal
9 Lessons
Work your way through DFS and BFS implementations, topological sort, SCCs, and bipartite graphs.
4.
Shortest Paths
7 Lessons
Break down complex ideas on shortest path algorithms and their implementation techniques.
5.
Spanning Trees
5 Lessons
Deepen your knowledge of minimum spanning trees, Kruskal's algorithm, and maximum spanning tree challenges.
6.
Flow Problems
6 Lessons
Focus on solving max flow problems, Ford-Fulkerson method, and bipartite matching challenges.
7.
Conclusion
1 Lessons
Master the steps to understanding graph algorithms, solving fundamental problems, and exploring advanced topics.
8.
Appendix
1 Lessons
Step through the Disjoint Set Union structure and its optimizations for dynamic connectivity.
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Course Author:
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