Deep Learning for Engineers (126504-SoSe2026)

The lecture covers deep learning concepts and techniques, including:

• general ideas and mathematical background
• training and regularization methods
• neural network architectures (feed-forward, convolutional, physics-informed, autoenconder,...)
• application to scientific and engineering problems
• employment on modern computer hardware

In hands-on sessions, practical exercises are used to discuss and illustrate the presented content.

• First session: Wednesday, April 15, 10:15h, IC 03/606
• Moodle: enrollment key will be provided in first session
• Contact: hpc-bi@rub.de
• Teaching format: 2h lectures, 2h exercises per week
• Lecture: Presentation (Wednesday, 10:15-11:45h, IC 03/606)
• Exercise: Hands-on programming (Thursday, 16:00-17:30h, CIP Pool, IC 04/630)
• Language: English