33 JS Concepts is a structured collection of core JavaScript topics for learning the language deeply.
Open Source: #education
Catalog projects marked with #education. Tags work as dedicated landing pages, so related tools are easier to find and connect.
This collection holds 78 projects with a combined 6,658,813 GitHub stars. Main languages: Python, Jupyter Notebook, JavaScript.
About the educational projects
The best programming study materials have long lived on GitHub: free, current, and vetted by thousands of learners. Roadmaps, interactive courses, and exercise collections update faster than any paid course.
This collection gathers educational repositories, from structured curricula to exercise sets. Stars are an honest signal here: bad study material does not collect hundreds of thousands of them.
Repositories
The Algorithms - Java is an educational collection of algorithms and data structures implemented in Java.
30 Days Of Python is a step-by-step Python learning course organized by daily topics and exercises.
Rustlings is a set of small exercises for learning to read and write Rust.
Hello Agents is an educational project about the principles, design, and practice of agent systems.
LeetCode Master is a learning route for LeetCode algorithm practice with topics, templates, and explanations.
AI Hedge Fund is an educational Python project where multiple AI agents simulate an investment committee.
nanoGPT is a compact Python implementation for training and fine-tuning medium-sized GPT models.
LeetCode Solutions is a large learning repository with algorithm problem explanations, data structures, and interview preparation material.
nanochat is Andrej Karpathy’s educational project for walking through the main stages of training a small language model and running a simple chat.
First Contributions is a learning repository that walks beginners through their first contribution to an open-source project: fork, branch, commit, and change request.
MiniMind is an educational PyTorch project for reproducing a small language model end to end: data, pretraining, finetuning, and experiments.