Open source. Open possibilities.

Tech Interview Handbook provides free, curated technical interview preparation materials for software engineers, covering coding questions, behavioral questions, resume guides, and system design.

JavaScript implementations of popular algorithms and data structures, each with its own README explanation, complexity notes, and links to further reading. Useful for study and interview prep.

labuladong's algorithm notes: an open-source tutorial and problem-solving toolkit centered on LeetCode. With 60+ original Chinese articles, core pattern frameworks, a visualization panel, and multi-platform plugins, it helps learners master data structures and algorithms conceptually rather than just memorizing code.

SciPy is an open-source software library for mathematics, science, and engineering, providing efficient numerical routines built to work with NumPy arrays.

Hello Algorithm is a free open-source introductory tutorial on data structures and algorithms, featuring animated illustrations and runnable code. It supports five languages and 14 programming languages, making it ideal for beginners.

An interactive visual learning platform designed to make algorithms and data structures easy to understand through step-by-step animations, custom inputs, and playback controls.

Clean, well-documented Python implementations of common algorithms and data structures for learning and reference.

Educational collection of algorithms implemented in Java, intended for learning purposes. Includes a full directory of applications, contribution guidelines, and support for running/editing in Gitpod.

ML.NET is an open-source, cross-platform machine learning framework for .NET that lets developers build, train, deploy, and consume custom models directly in .NET apps without needing Python or R.

A curated list of computer science courses with video lectures, covering algorithms, AI, databases, operating systems, and more.

A comprehensive Java library of algorithm and data structure implementations covering data structures, dynamic programming, graph theory, geometry, linear algebra, and mathematics, with Bazel build support and companion YouTube video tutorials.