Modern engineering increasingly relies on data-driven solutions across domains such as product design, production systems, logistics, and robotics. To address these developments, this project-based course enables students to work in small teams on a data-driven engineering problem in one of the domains.

The focus is on collaboratively structuring and solving an open-ended task, organizing project work, and selecting or combining suitable methods from machine learning, optimization, and simulation. Students use state-of-the-art tools and software libraries for data-driven engineering applications (depending on the task, e.g., Isaac Sim, PyTorch, ROS2, Gymnasium) to develop, implement, and evaluate a prototypical solution. Students document their work and communicate their results through presentations and suitable media formats.

The course is designed as an on-site project with regular in-person collaboration and supervision. Familiarity with Python programming is strongly recommended. Students should be open to learning and working with operating systems and tools such as Linux, Docker, and Git.

Learning Objectives

After successful completion of the course, students will be able to:

• Analyze and formulate an open-ended engineering problem as a data-driven task and select appropriate methods from machine learning, optimization, and simulation.
• Design, implement, and manage a team-based project workflow, including task allocation, milestone planning, and effective team communication, using modern tools and software libraries for data-driven engineering applications.
• Evaluate and communicate project results effectively to different audiences using appropriate formats, including technical presentations, pitch-style formats, and short project videos.

Additional Information

The number of participants is limited. Information on the application process is available in ILIAS.

Organizational Information

See further details on course organization at: lehre.imi.kit.edu and in ILIAS.

Workload

120 hours

See ILIAS for time and location / Zeit und Ort siehe ILIAS