Princeton's full algorithms course — sorting, searching, graphs, strings — with runnable Java implementations and a companion Coursera course.
Why it's here: University-level rigor with practical, working code, not just pseudocode.
The Hub
The best resources for the craft.
A working library — not a link dump. Every entry here is something worth your time: free where free exists and is genuinely good, paid where the depth justifies it. Organized by what you're actually trying to learn.
Algorithms & Data Structures
Think efficientlyThe mathematically rigorous reference for algorithm design and analysis — the book most CS programs build their theory courses around.
Why it's here: The depth CS50 and Sedgewick don't go into. Worth owning once you're serious.
A GitHub-native guide to designing large-scale systems — scalability, caching, sharding, and consistency — with real interview Q&A.
Why it's here: The most-starred free resource on this exact topic for a reason: comprehensive and current.
A war-stories approach to algorithm design, paired with a catalog of algorithmic problems mapped to real solutions.
Why it's here: Best for the "I recognize this problem shape" instinct CLRS doesn't build.
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