Seminar Data-Science I (Methods)

In this seminar, students perform scientific research, either in the form of a literature review or by conducting a small experiment, or a mixture of both, and prepare a written report about the results. Topics of interest focus around a variety of problems and tasks from the fields of Data-Science, Network Science and Text Mining. 

Previous participation in the courses “Network Science” and “Text Analytics” are recommended.

Expertise: Students will acquire a deep understanding of the research topic. He/she is expected to describe in-depth and summarize the topic in detail in his/her own words, as well as to judge the contribution of the research papers to ongoing research.

Methodological competence: Students will develop methods and skills to find relevant literature for his/her topic, to prepare methodologically sound scientific experiments, and to write a well-structured scientific paper and to present his/her results. He/she will be also aware of the need to avoid plagiarism.  The key qualification Scientific Research is highly recommended as a prerequisite for the seminar.

Personal qualification: Students will acquire skills on how to find relevant literature for a research topic, organize a small research task, write a well-structured, concise paper about it and present the results of their work. He/she is well prepared to write and present a Master’s Thesis. 

Large language models (LLM) have been trained on vast amounts of data to learn language use and knowledge about the world. However, language and our world are constantly evolving – a fact that most LLMs do not explicitly model. 

In this seminar, we want to understand whether LLMs can capture how the meaning of words and facts change over time. We will also look at how these models can be adapted to achieve an understanding of time and to allow them to be regularly updated with new knowledge.

The schedule below is preliminary, dates are subject to change.

Registration is possible until Monday, 13.02.23 via Portal2.  There will be a central allocation suitable to priorities. After allocation you have the possibility to deregister until Saturday, 25.02.23.