Princeton's Algorithms, Part I, taught by Robert Sedgewick and Kevin Wayne, is free on Coursera and remains one of the best algorithms courses ever recorded. It focuses on implementing each structure correctly and analyzing its performance, with programming assignments graded by an autograder that's famously strict about both correctness and efficiency. The course uses Java, but the ideas transfer directly. If you finish Part I and its assignments, you'll understand the fundamentals better than most working developers.
Antti Laaksonen's concise handbook. The gateway into competitive programming.
Three hundred carefully ordered problems. Finishing the early sections is serious evidence of skill.
Whiteboard explanations of dynamic programming, graphs, and complexity that many find clearer than textbooks.
Skiena's practical catalogue of problems and war stories. The book for applying algorithms at work.
Steven Skiena
A full university textbook, free. Exceptionally clear on recursion, dynamic programming, and graphs.
Jeff Erickson
Colt Steele's approachable walk through Big O and problem-solving patterns, in JavaScript.
The standard practice platform. Work from a curated list rather than grinding problems at random.
LeetCode
A curated problem list grouped by pattern, with free video solutions. Efficient interview prep.
NeetCode
Tim Roughgarden's proof-driven course. Teaches you to reason about algorithms, not memorize them.
Implements the core structures in Python step by step. Good for learners who learn by typing.
Illustrated and friendly. The right book if algorithm textbooks have intimidated you before.
Manning Publications
Animations of every classic data structure and algorithm. Use it whenever a diagram would help.
VisuAlgo
A gentle, visual introduction to searching, sorting, recursion, and graphs.
MIT's core algorithms course with full lectures and problem sets. More mathematical than most.
Builds arrays, linked lists, hash tables, and trees in C. Superb foundations for everything else.
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