25.6K ·GitHub
What is this?
A curated list of places to learn and practice algorithms: links to courses, books, blogs, visualizers and problem sites, sorted by level and topic.
So it's not an app or a course — just a page of links?
Right: a single hand-picked reading list on GitHub in the style of other 'awesome' lists. There is nothing to install — you open it and follow the links that fit your level.
I've never studied algorithms — where should I start?
The Beginner-Friendly section: Khan Academy's course, FreeCodeCamp's animated tutorial, and puzzle-style books — Levitin's 'Introduction to Algorithms' requires no programming experience at all.
Can I reuse or fork the list?
Yes — it is licensed under Creative Commons Attribution 4.0, so you can share and adapt it with attribution; contributions are welcome via the contribution guidelines.
Is everything on the list free to access?
The list itself is free. Many entries are open — Khan Academy, FreeCodeCamp, MIT courses, CP-Algorithms, ProjectEuler — but several are commercial books like CLRS or Knuth, so check each link.
Does it cover anything beyond classic theory?
Yes — Production System (MIT's hands-on course on high-performance software, a cloud & distributed computing book), Database (PostgreSQL query optimization) and Special Topic (lesser-known structures like immutable stacks, queues and deques).
Can I play with algorithms right in the browser?
Yes — the beginner section links VisuAlgo's animated visualizations, See Algorithms for building custom graphs and binary trees, and Recursive, which steps through Python and JavaScript code with a call tree.
What are similar projects?
leetcode, interview, swift-algorithm-club, DSA-Bootcamp-Java, leetcode, hello-algorithm, awesome-programming-books, tech-interview-handbook
Which topics is it in?
online-learning, cheat-sheet, math, leetcode, books, interview-questions, youtube, data-structures, interview-preparation, algorithms, visualization, programming
