Although Artificial Intelligence (AI) is transforming the industry, many univer-sity programs prioritize generic AI principles above domain-specific applica-tions. This paper investigates an adaptive course format to overcome the gap to real-world use cases. The suggested concept expands on a two-semester pro-gramming course and introduces students to current AI approaches used in re-search and industry in mechanical engineering. The authors aim to address bu-reaucratic limitations in curriculum reform by focusing on modules that pro-mote flexible, problem-based learning. The course structure will include a lec-ture series with a high-level overview and in-depth workshops on specific ap-plications led by active AI researchers. Students will work on semester-long projects with instructors as clients, which specify the technical requirements to be fulfilled. This dual position requires learners to deal with not only AI tech-niques, but also project management, client communication, and interdiscipli-nary interaction.

The broad representation of AI applications is highlighted by providing a brief overview over the starting topics and goals of challenges set in different me-chanical engineering domains such as product development, control systems and thermodynamics.