We have developed a focused set of courses aimed at addressing the boundary between systems and software engineering, machine learning, computational neuroscience and computer vision. As part the recent revised graduate curriculum for Masters in Computer Science students can take key courses focused on systems science and engineering for intelligence:
1. Systems and Software Engineering I & II – a projects oriented course teaching systems and software engineering practices. Students learn to think holistically and understand how to examine a system from a user perspective, modeling, architecting and design perspective, and from implementation and validation perspectives. This course is complemented by a theory oriented course.
2. Systems Engineering meets Life Sciences I & II – This course focuses on natural systems, human and computer vision, bio-inspired vision system designs, and systems theory required for modeling, analysis, simulation and validation of cognitive vision systems. The emphasis is on abstractions, modeling, and rigorous statistical approaches to performance evaluation. Connections are also made between engineering designs and architectural designs in natural systems.
3. Machine learning I & II (Foundations and advanced machine learning) – This course focuses on foundations of machine learning, applied statistics, and the latest advances in machine learning – deep learning, Bayesian learning, etc.
4. Seminar in Advanced topics on Pattern Analysis and Machine Intelligence
5. Seminar in Advanced topics on Systems and Software Engineering
6. Machine Learning Practice – Practice course in Machine Learning and Intelligent Systems Engineering
Courses Winter Semester 2019/20
Machine Learning I ( Please see Prof. Dr. Bertschinger/Prof. Kaschube’s FIAS page).
Seminar: Pattern Analysis and Machine Intelligence ( Jointly with Prof. Dr. Bertschinger, Prof. Kaschube) http://www.ccc.cs.uni-frankfurt.de/pami-seminar-ws-19-20/
Machine Learning Practice – (with M. Mundt, I. Pliusch)
Systems and Software Engineering I (Link)
Systems Engineering meets Life Sciences I (Link)
Courses Summer Semester 2019
Machine Learning II (Jointly with Prof. Dr. Bertschinger).
Seminar: Pattern Analysis and Machine Intelligence ( Jointly with Prof. Dr. Bertschinger) Link to webpage at FIAS
Machine Learning Practice – (with M. Mundt, I. Pliusch) Github link to course material
Courses Winter Semester 2018/2019
Machine Learning I (is offered by Prof. Bertschinger/Prof. Kaschube).
Seminar: Pattern Analysis and Machine Intelligence (Jointly with Prof. Bertschinger and Prof. Kaschube) (Link to papers)
Courses Summer Semester 2018
Machine Learning I (is offered by Prof. Bertschinger).
Seminar: Pattern Analysis and Machine Intelligence (see webpage of Prof. Bertschinger at FIAS)
Courses Winter Semester 2017/2018
Machine Learning I (is offered by Prof. Kaschube and Prof. Bertschinger).
Courses Summer Semester 2017
Systems and Software Engineering II
Courses WS 16/17
Courses SS 16
Introduction to Programming
Courses WS 15/16
Introduction to Programming