Seamless Integration of Machine Learning Contents in Mechatronics Curricula

The topic of machine learning is becoming more and more important for mechatronical systems and will become ordinary part of today's student life. Thus, it is obvious, that machine learning should be part of today's student's curriculum. Unfortunately, machine learning seldomly is implemented into the curriculum in a substantial or linking manner, but rather offered as an elective course. This paper provides an analysis of how machine learning can be integrated as a mandatory part of the curriculum of mechatronic degree courses. We consider, what the required minimal changes in fundamental courses should be and how traditional subjects like robotics, automation and automotive engineering can profit most of this approach. We will show, that only minimal reassignments within the classical curriculum and minimal changes in the mathematical fundamentals combined with a good link to control theory and simulation are necessary, which results in reassignments of only 8 European Credit Points (ECTS) in total. As a case study we utilize an existing German mechatronic degree course specialized on information technology, which covers most of the discussed aspects.