Thousands of teachers use GitHub to host their courses, distribute assignments, and get insight into student progress. Many teachers open source their materials, so other teachers can use them. Between Massive Open Online Courses (MOOCs) and custom lessons from individual teachers, there’s plenty of materials for new teachers to adapt and reuse in their classrooms.
This is an extended list of popular courses we found on GitHub. Did we miss one? Let us know.
Top courses based on stars
1. Ada Developers Academy’s Jump Start Curriculum (223 stars)
ADA’s Jump Start Curriculum helps prospective students become familiar with the tools, concepts, and vocabulary they’ll need to be successful in the larger program. Each lesson begins with stating learning goals, so students can be sure they’re retaining what they need to prior to entering the program.
2. React From Zero (207 stars)
React From Zero is a straightforward introduction to React that is broken into 17 parts. Each part of the tutorial is in the code for that lesson, using comments to explain concepts in React and examples right in the editor. Each lesson also links to a preview of how the code renders in a browser, so you can follow along and immediately see the outcome of code while you’re learning.
3. Hear Me Code’s Python Lessons (199 stars)
Hear Me Code, based in Washington, D.C., is an organization that offers free, beginner-friendly classes to women. This repository has a “Start Here” guide for those who’ve never installed or run Python before. The lessons are broken into 16 sections, each covering a different concept. Hear Me Code’s slides are also hosted on GitHub, so it’s easy for you to follow this curriculum on your own.
4. Ada Developers Academy’s Textbook Curriculum (154 stars)
This repository is an 11-week prep course for programming competitions, but it can be used to practice algorithm challenges for interviews or improve algorithmic thinking. Prior programming knowledge and familiarity with data structures will help students who want to get started with this advanced course.
6. Labs for Foundations of Applied Mathematics Course, 30 stars — Brigham Young University is hosting their labs for the Foundations of Applied Mathematics course on GitHub. They’re working on four volumes of textbooks for the course, and the information about the coursework is also hosted on GitHub Pages. The organization has several other repositories for curriculum as its being developed, but the Labs repo has the most stars.
7. Michael’s Data Science Curriculum, with companion guide, 28 stars — Tied in stars with Intro to Deep Learning with Python, Michael Alcorn’s data science curriculum comes with a companion guide, also hosted on GitHub, that he wrote after being asked how he transitioned into a data science career. It’s a DIY curriculum that recommends textbooks, various MOOCs, and subjects to explore on the way to becoming a data scientist.
8. Intro to Deep Learning with Python, 28 stars — This course, from Lesley Cordero and Dan Schlosser, walks students through setup and getting started with Python and introduces them to background information on deep learning before providing step-by-step instructions on building and training a neural network.
9. Minecraft U Curriculum, 25 stars — Minecraft U is a curriculum developed to introduce coding to children, using Minecraft as a bridge. The first lesson starts with the very basics on how to use a computer, and is meant to be led by an instructor. Each level of the curriculum denotes the target age or prerequisite experience, and leads students through learning about problem solving, electricity, programming basics, and eventually Java and product management.
10. CyberSecurity, 10 stars — This repository, from Derek Babb, lays the groundwork for a high school cybersecurity curriculum. The curriculum features units that can be taught as standalone courses, or they can be taught together to comprise a yearlong course. Units come with a teaching guide outlining student objectives, suggested activities, and assessment questions.
Top courses based on forks
1. Stanford TensorFlow Tutorials (2,452 forks)
These tutorials go along with Stanford’s TensorFlow for Deep Learning Research course. The syllabus, slides, and lecture notes are all available on the website, and each week’s assignments and examples are available in this repository.
2. Deep Learning Specialization on Coursera (1,133 forks)
This student-created repository includes all work from Coursera’s Deep Learning Specialization programming assignments. While this repository itself is not a curriculum, it’s a helpful guide for self-teaching and reading more about the concepts and solutions from this deep learning series of courses.
3. Creative Applications of Deep Learning with Tensorflow (591 forks)
This repository is comprised of assignments and lecture transcripts for Kadenze Academy’s Creative Applications of Deep Learning with TensorFlow curriculum. There are a total of five courses, and the repository also contains extensive documentation on setup and getting started with the tools students will need.
4. Practical RL: A course in reinforcement learning in the wild (401 forks)
This course is taught on-campus in Russian at the Higher School of Economics, but its online version is available to both English and Russian speakers. The entire course is nine weeks long, and the repository also contains bonus materials for students to explore after completing the curriculum.
5. Data Science Coursera (152 forks)
Michael Galarnyk, a Data Science M.A. student, decided to document his journey through Johns Hopkins’ Coursera Data Science curriculum as a supplement to his program at UC San Diego. Along with a directory for each course and its assignments, there’s also a link to a blog post reviewing each course week-by-week, so prospective students can get an idea of what to expect each week.
6. Hear Me Code Python Lessons, 111 forks — Hear Me Code, based in Washington, D.C., is an organization that offers free, beginner-friendly classes to women. This repository has a “Start Here” guide for those who’ve never installed or run Python before. The lessons are broken into 16 sections, each covering a different concept. Hear Me Code’s slides are also hosted on GitHub, so it’d be easy for anyone to follow this curriculum on their own.
7. Developing iOS Apps with Swift, 110 forks— This repository contains lecture notes, assignments, problem sets, and slides for the Stanford School of Engineering’s course on Developing iPhone Applications, available on iTunesU. Created by a student of the course, this repo is organized in a table, where each lecture is a row and contains links to slides, demo code, and the lecture video for the lesson. This format makes it easy for others to follow along, or explore by lesson topic.
8. Udacity’s Machine Learning Engineer Nanodegree Stanford’s Convolutional Neural Networks for Visual Recognition, 48 forks — While Udacity’s Machine Learning Engineer Nanodegree curriculum has a number of repositories, this one is especially usable due to its README. There’s info about how to use the content of the repo, links to all the class materials, and links to additional helpful resources for students. After students have finished an assignment, they’re invited to add their solutions to the repo for others to reference.
9. Introduction to Hadoop and MapReduce, 41 forks — This repository contains the source code and problem sets for Udacity’s Intro to Hadoop and MapReduce course. The README provides instructions for setup, documentation on input and output data files, and question sets for the course, which includes both Python and Java variants.
10. Prep Course for North American University’s Chapter of Association for Computing Machinery International Collegiate Programming Competition, 26 forks — This repository is an 11-week prep course for programming competitions, but can be used to practice algorithm challenges for interviews or improving one’s algorithmic thinking. Prior programming knowledge and familiarity with data structures will help those who want to get started with this more advanced course.