• Module title: Master’s Seminar ScaDS.AI
• University: Leipzig University
• Fakulty: Faculty of Mathematics and Computer Science
• Degree: Master of Science (M.Sc.)
• Applicability: Data Science (M. Sc.)
• Language: German, partly English

Module specifications (show more)

Module form:

Recommended for:

Duration:

Module frequenzy:

Teaching methods:

 

 

Compulsory

4th semester

1 semester

every semester

Seminar “Masterseminar ScaDS.AI” (2 SWS) = 30h attendance time and 120 h self-study = 150 h
Workload

 

 

Qualification goals:

After active participation in the “Master’s Seminar ScaDS.AI” module, students are able to familiarize themselves independently with current research topics at ScaDS.AI. They can independently select and analyze the relevant literature and present the topic appropriately in a group. They learn to present the core content of their own work in the form of a poster.

Content:

The students take part in the internal 2-weekly working group seminars of ScaDS.AI. The seminars deal with current research topics at ScaDS.AI. The research topics vary from semester to semester. A current overview of topics can be found here: https://scads.ai/research/ . Students choose from the topics and take part in the discussion in the seminars. At one of the seminar dates, students present a paper on their Master’s thesis as their own research topic and answer questions about it. In addition, students take part in two scientific poster sessions in the form of one-day block events (so-called General Assembly at ScaDS.AI). As part of their preliminary examination work, students present their work as a poster on one of the dates.

Participation requirements:

None (the Master’s thesis should already have been started)

Literature:

Information on literature references will be provided in the courses.

Examinations and prerequisites:

• Module examination: Presentation 60 minutes, with weighting: 1
• Examination prerequisite: Poster presentation (processing time 6 weeks)