Lecturer | Prof. Dr. Markus Strohmaier, Tobias Schumacher, Marlene Lutz |
Course Format | Seminar |
Offering | HWS |
Credit Points | 6 ECTS |
Language | English |
Grading | Written report (50%), oral presentation (40%) and discussion (10%) |
Examination date | See schedule below |
Information for Students | The course is limited to 15 participants. The registration process is explained below. |
For administrative questions, please contact office.strohmaier. uni-mannheim.de
The achievement of the learning goals is pursued by practicing on the basis of personally assigned in-depth scientific topics as well as by actively participating in the presentation dates. The organizer will choose subject areas within the field of Data-Science (see Topics) and provide scientific papers to students to work through.
Previous participation in the courses offered by our chair are recommended.
This seminar will be split into two main topic blocks. Every student will be assigned a research paper from only one of these blocks to work on. Yet, it is expected that students also actively participate in discussion on papers from the other topic blocks after they have been presented.
When applying for this seminar, please indicate whether you would be interested in only one or both topic blocks. The exact research articles that are to be worked on will be determined once we have an overview over the number of participants and their rough preferences.
The two topics we discuss this semester are the following:
On the basis of suitable literature, in particular original scientific articles, students independently familiarize themselves with a topic in data-science, classify and narrow down the topic appropriately and develop a critical evaluation. Students work out concepts, procedures and results of a given topic clearly and with appropriate formalisms in a timely manner and to a defined extent in depth in writing; Evidence of independent development by presenting self-selected examples. Descriptive oral presentation of an in-depth data science topic using suitable media and examples in a given format.
Registration period | until 04.09.23 (11.59 PM) | see „Registration“ |
Notification of acceptance/ | 06.09.23 | |
Drop-out until | 07.09.23 | |
Kick-off meeting | 13.09.23, 14:45 | general information |
Midterm | 16.10.23 (tentative) | midterm presentations |
Endterm | 01.12.23 (tentative) | endterm presentations |
Submission deadline | 08.12.23 (11.59 PM) |
If you are interested in this seminar, please apply to Tobias Schumacher via email.
Please start the Subject Line with “[SemDSII]”, and provide some details about your background, e.g., whether you have taken some relevant classes before (cf. course description) and your motivation to take this seminar. Also, make sure to indicate which of the two given topics – Explainability in AI Decision-Making and Advertising on Social Media in Political Contexts – you are interested in.