Module number
Description
Module number Applied Machine Learning and Deep Learning MBM 2.9 German module title Anwendung des maschinellen Lernens und des Deep Learnings Module Coordinator Prof. Dr. Marcin Hinz Other lecturers N.N. Language English Assignment to curricula (Term) Master TBM, Semester 1/2, summer term Usability in this programme / in other programmes / in certificates Elective Course Master MBM and TBM Type of course, SWS (semester hours per week) Lecture (SU): 2 SWS, Exercise (Ü): 2 SWS Workload in hours Presence: 45 h – Self study: 135 h Credit points 6 Recommended prerequisites • Basic programming skills (preferably in Python) • Engineering mathematics Course objectives (Skills and competences) In this course students will learn how machine learning and deep learning techniques can be applied to extract knowledge from complex data of technical systems. The course combines an introduction and application of
Preview the 5 closest equivalencies already indexed in our system
HM-00187C19B9 has possible credit equivalents including 6CCYB064 at King's College London.
| Course | University | Qwest Score |
|---|---|---|
6CCYB064 Machine Learning for Biomedical Applications | King's College London | 72 |
6CCYB064 Machine Learning for Biomedical Applications | King's College London | 72 |