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mithi/robotics-coursework

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TLDR

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.

Mindmap

mindmap
  root((robotics-coursework))
    Courses series
      MIT Coursera EdX
      ETH Zurich Stanford
      Berkeley Northwestern
    Topics covered
      Kinematics control
      SLAM planning
      Aerial robots
      Deep learning
    Hands-on projects
      Hexapod walker
      Drone Arduino
      Self-driving cars
    Supporting concepts
      Kalman filters
      Control systems
      Machine learning
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Code map

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Things people build with this

USE CASE 1

Find a free university-level robotics course from MIT, ETH Zurich, Stanford, or Berkeley to start learning the field.

USE CASE 2

Locate hands-on robot projects (drone, hexapod, quadruped, self-driving car) to build or simulate while learning.

USE CASE 3

Find supplementary resources on Kalman filters, control theory, or deep learning to support a robotics curriculum.

USE CASE 4

Discover ROS-based courses or self-driving car nanodegrees for career-focused robotics skill development.

Tech stack

PythonC++ROSArduinoRaspberry Pi

Getting it running

Difficulty · easy Time to first run · 5min
The README does not mention a license for this list.

In plain English

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.

Copy-paste prompts

Prompt 1
I'm a beginner who wants to learn robotics from scratch. Based on the mithi/robotics-coursework list, suggest a learning path starting with free courses and ending with a hands-on project.
Prompt 2
I want to learn SLAM (Simultaneous Localization and Mapping). From the robotics-coursework list, which lecture series or course should I start with and what math prerequisites do I need?
Prompt 3
I'm an engineering student interested in aerial robotics. List the free courses from mithi/robotics-coursework that cover quadrotors and drone control and explain what each one focuses on.
Prompt 4
I want to build a small self-driving car prototype using ROS. From the robotics-coursework list, which courses cover ROS and autonomous vehicle basics, and what hardware should I start with?
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