mithi/robotics-coursework — explained in plain English
Analysis updated 2026-05-18
Find a free university-level robotics course from MIT, ETH Zurich, Stanford, or Berkeley to start learning the field.
Locate hands-on robot projects (drone, hexapod, quadruped, self-driving car) to build or simulate while learning.
Find supplementary resources on Kalman filters, control theory, or deep learning to support a robotics curriculum.
Discover ROS-based courses or self-driving car nanodegrees for career-focused robotics skill development.
| mithi/robotics-coursework | feiyangqingyun/qtkaifajingyan | multimc/launcher | |
|---|---|---|---|
| Stars | 4,625 | 4,625 | 4,625 |
| Language | — | — | C++ |
| Setup difficulty | easy | moderate | easy |
| Complexity | 1/5 | 2/5 | 2/5 |
| Audience | researcher | developer | general |
Figures from each repo's GitHub metadata at analysis time.
robotics-coursework is a curated list of places to learn robotics online, maintained by Mithi. It collects courses, video lectures, hands-on projects, blogs, and supplementary tools in one place, organized so someone new to the field can find a path into the subject without getting lost in search results. The course section covers a wide range of learning formats and institutions. Free options include MIT OpenCourseWare robotics lectures, Coursera and EdX offerings from Northwestern University, ETH Zurich, Columbia, Penn, and others, plus standalone YouTube lecture series from professors at Freiburg, Berkeley, MIT, and Stanford. Paid options from Udacity (self-driving cars, flying cars, sensor fusion) and The Construct platform are also listed. Courses span foundational topics (kinematics, control theory, probability, motion planning) through specialized areas like aerial robots, SLAM (Simultaneous Localization and Mapping), manipulation, and deep learning for robotics. The hands-on section links to actual robot projects you can build or simulate: hexapod walkers, quadruped dogs, Arduino drones, self-driving mini cars, and the Hugging Face LeRobot project. These are useful if you prefer learning by building rather than sitting through lectures. The repository also highlights the author's own hexapod robot simulator as a reference project. A useful concepts section covers Kalman filters, control systems, mechanical design, and machine learning as supporting knowledge that robotics relies on. The list is annotated with icons: a sprout for curated fundamental content, a dollar sign for paid resources, a video camera for lecture series, and a heart for the author's personal bookmarks. There is also a companion page for prototyping with Arduino or Raspberry Pi, and a separate book list. No license is stated. The repository is language-agnostic since it is a resource list, not code.
A curated list of online robotics courses, video lectures, hands-on projects, and learning resources spanning foundational theory through SLAM, aerial robots, and deep learning.
The README does not mention a license for this list.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.