Seminar Data-Science II (Empirical Studies)

The learning goals will be achieved by in-depth learning from examples on the basis of personally assigned scientific topics as well as by active participation in the presentation sessions. The organizer will choose subject areas within the field of data science and provide scientific papers for the students to work through.

Previous participation in courses offered by our chair is recommended.

On the basis of scientific literature, in particular original research articles, students independently familiarize themselves with one topic in data science. They classify and narrow down the scope of the topic appropriately and provide a critical evaluation. Students work out concepts, procedures and results of a given topic clearly and with appropriate formalisms. They do so in-depth by writing in a concise manner and to a defined extent. They are expected to show evidence of independent development of their arguments by presenting self-selected examples. Towards the end of the course they give a descriptive, in-depth oral presentation of the data science topic using suitable media and examples in an agreed-on format.

In a rapidly evolving digital landscape, language models play a crucial role in shaping and analysing textual content. As their influence on our daily lives continues to grow, the responsible use of language models becomes an imperative consideration.  This seminar explores the responsibilities associated with language models and their applications aiming to raise awareness of their societal impact. The students will gain insights into the ethical considerations, biases, transparency, and regulatory aspects of working with language models.

If you are interested in this seminar, please apply to Marlene Lutz 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).