Open Source Robotics
Hands-on introduction course to general-purpose open source robotics covering basics of robotics, machine learning in robotics as well as simulation software and ways to improve existing robots.
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Learning Goals:
- Create robotic machine learning datasets
- Setup simulation environments for different robots
What you get:
It provides a practical introduction to machine learning and robotics applications, covering topics such as computer vision with convolutional neural networks, natural language processing, time series forecasting, and other core techniques in modern AI.
The learning material is drawn from multiple sources and will give you both a broad and applied understanding of the field. A key component of the course is the team project, where you can explore your own ideas. Project options include a wide range of machine learning and robotics applications — for example, training a model to control a robot arm or developing an intelligent sensor add-on for a robot.
By the end of the course, you will have both theoretical knowledge and hands-on experience, building a strong foundation for further studies or a career in machine learning and robotics.
This course is part of the opencampus.sh Machine Learning Degree, and participants in the program receive preferred access. More details about the degree program can be found here.
What you should bring:
To participate in this course, basic programming knowledge in Python is sufficient. No prior experience in machine learning or robotics is required. You do not need to have access to a robot to take part as there are a few robot arms available. If you are interested in building one, support will be available.
Participants are expected to attend the weekly in-person sessions in Kiel and to dedicate additional time each week to study the provided learning material. Once the team projects begin (around four to five weeks into the course), you should also plan extra time during and after the session period to develop your project.
In order to receive a certificate of achievement (Leistungszertifikat/ECTS), active participation is required. Attendance is mandatory (no more than two missed sessions are allowed), and students must complete a team project (1–3 members). At the end of the course, the project must be presented and the well-documented source code submitted.
(Please note that certificates of attendance will not be issued for this course.)
Course Dates:
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22.10.2025 // 16:00 - 17:45General Introduction & Robotics Basics
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29.10.2025 // 16:00 - 17:45Introduction to LeRobot & Teleoperation
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05.11.2025 // 16:00 - 17:45Imitation Learning
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12.11.2025 // 16:00 - 17:45Vision-Language-Action Models (VLAs)
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19.11.2025 // 16:00 - 17:45Robotics Simulation
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26.11.2025 // 16:00 - 17:45Reinforcement Learning
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03.12.2025 // 16:00 - 17:45Real2Sim, Sim2Real, Real2Sim2Real
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10.12.2025 // 16:00 - 17:45Smart Sensors & TinyML Basics
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17.12.2025 // 16:00 - 17:45Project Work & Feedback
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07.01.2026 // 16:00 - 17:45Robot Operating System (ROS)
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14.01.2026 // 16:00 - 17:45Project Presentation
Registration at: edu.opencampus.sh