Veranstaltungsverzeichnis

Department of Health Services Research

• English course offer for exchange students :
• School of Medicine and Health Sciences
• Department of Health Services Research

Winter semester 2025/2026 8 Seminars

VAK Course Number	Title	Type Lecture Preliminary studies Advanced courses Practical course Colloquium Research group Workgroup Project group Council conference Internship Language course Subject didactics Excursion Tutorial Committee	SWS Semester weekly hours	Teachers	Degree
6.07.5408_E1	Applied Deep Learning Wednesday: 16:00 - 18:00, weekly (from 22/10/25) Description:	Exercises	2	Prof. Dr. Nils Strodthoff Juan Lopez Alcaraz Zahra Mansour	Master
6.07.5408_L	Applied Deep Learning Friday: 12:00 - 14:00, weekly (from 17/10/25), Location: A11 1-101 (Hörsaal B) Dates on Thursday, 19.02.2026 09:00 - 11:00, Location: V03 0-D002 Description: This lecture provides a comprehensive introduction to contemporary Deep Learning methods, with a specific emphasis on their practical application. Concurrently, it serves as a primer for the widely-used PyTorch Deep Learning framework, assuming only a basic familiarity with Python. The course encompasses a wide range of prevalent machine learning tasks across various data types, including tabular, image, text, audio, and graph data. Throughout the course, we delve into the most crucial and up-to-date model architectures within these domains. This encompasses convolutional neural networks, recurrent neural networks, and transformer models. The lecture is complemented by hands-on exercise sessions, where students will gain practical proficiency with PyTorch. Simultaneously, they will acquire practical insights to effectively apply contemporary deep learning methods within their specific fields of interest. This lecture provides a comprehensive introduction to contemporary Deep Learning methods, with a specific emphasis on their practical application. Concurrently, it serves as a primer for the widely-used PyTorch Deep Learning framework, assuming only a basic familiarity with Python. The course encompasses a wide range of prevalent machine learning tasks across various data types, including tabular, image, text, audio, and graph data. Throughout the course, we delve into the most crucial and up-to-date model architectures within these domains. This encompasses convolutional neural networks, recurrent neural networks, and transformer models. The lecture is complemented by hands-on exercise sessions, where students will gain practical proficiency with PyTorch. Simultaneously, they will acquire practical insights to effectively apply contemporary deep learning methods within their specific fields of interest.	Lecture	2	Prof. Dr. Nils Strodthoff Juan Lopez Alcaraz Zahra Mansour Maham Khokhar Nils Neukirch	Master
6.06.811	Journal Club Tuesday: 08:15 - 09:45, weekly (from 14/10/25) Description: Die Seminare vermitteln Kenntnisse zum Verständnis und zur Analyse englischsprachiger wissenschaftlicher Studien. Der Schwerpunkt liegt auf der geschriebenen Sprache. Die Seminare vermitteln Kenntnisse zum Verständnis und zur Analyse englischsprachiger wissenschaftlicher Studien. Der Schwerpunkt liegt auf der geschriebenen Sprache.	Seminar	-	Prof. Dr. Kathrin Börner	Master
6.07.001	Tutorial for new Data Science and Machine Learning students Friday: 14:00 - 16:00, weekly (from 17/10/25) Description:	Tutorial	-	Prof. Dr. Nils Strodthoff Jalil Alipour
6.07.5408_E3	Applied Deep Learning Wednesday: 12:00 - 14:00, weekly (from 22/10/25) Description:	Exercises	2	Prof. Dr. Nils Strodthoff Juan Lopez Alcaraz Nils Neukirch	Master
6.07.5408_E2	Applied Deep Learning Monday: 12:00 - 14:00, weekly (from 20/10/25) Description:	Exercises	2	Prof. Dr. Nils Strodthoff Juan Lopez Alcaraz Maham Khokhar	Master
6.07.550	Ethics in Data Science Friday: 10:00 - 12:00, weekly (from 07/11/25), Location: A05 1-160 Dates on Friday, 09.01.2026 14:00 - 16:00, Location: V03 2-A208 Description:	Lecture	-	Prof. Dr. Mark Schweda Prof. Dr. Nils Strodthoff Prof. Dr. Antje Wulff Matthias Hauer Prof. Dr. Gerald Enzner Prof. Dr. Bernd Meyer Prof. Dr. Peter Ruckdeschel Prof. Dr. Alexander Hartmann	Master
6.06.812	English Grammar Lab The course times are not decided yet. Description: Die Seminare vermitteln Kenntnisse zum Verständnis und zur Analyse englischsprachiger wissenschaftlicher Studien. Der Schwerpunkt liegt auf der geschriebenen Sprache. Die Seminare vermitteln Kenntnisse zum Verständnis und zur Analyse englischsprachiger wissenschaftlicher Studien. Der Schwerpunkt liegt auf der geschriebenen Sprache.	Seminar	-	Prof. Dr. Kathrin Börner	Master
8 Seminars