Engineering

Graph Theory for Software Engineers

A practical introduction to graph theory — from fundamental concepts through traversal algorithms, cycle detection, topological sorting, and shortest path algorithms — designed for software engineers who need to reason about graph-structured data.

8 modules

Graph Foundations

Vertices, edges, and the vocabulary that makes everything else make sense

Graph Representations

Choosing the right data structure before writing a single line of algorithm code

Traversal Mechanics

How BFS and DFS move through a graph, and what each visit costs

Connectivity and Components

Understanding reachability, connected components, and the structure of directed graphs

Cycle Detection

Four techniques for catching loops in directed graphs, undirected graphs, and linked structures

DAGs and Topological Sort

How acyclic structure enables ordered execution — and the two algorithms that exploit it

Shortest Path Algorithms

From BFS to A*: choosing the right tool for the graph in front of you

Graph Theory in Practice

From abstract algorithms to real engineering problems — a capstone guide to modeling, selecting, and applying the right graph technique

How this plan was made

Each plan on learnings is built by a hand-crafted agentic pipeline: research agents gather primary sources, a claim reviewer verifies facts against them, and a sequencer orders modules for how people actually learn. The curation — topic selection, framing, editorial standards — is Nicolas's. The research and writing is AI-assembled.