Teaching

Natural Language Processing

Lecture · B.Sc. Digital Humanities, B.Sc. Computer Science · Summer Semester

This course introduces students to the field of Natural Language Processing. We start with classic NLP tasks, then cover prerequisites to language models such as preprocessing and tokenisation. We move on to transformers and large language models, and finally cover topics from computational linguistics and their application to LLMs.

Foundations of Machine Learning

Lecture · B.Sc. Digital Humanities, B.Sc. Computer Science · Winter Semester

For a given task and measure of success, a computer program learns when its performance improves with experience. This course introduces machine learning as a guided search through a space of potential hypotheses. Students gain a broad overview of learning paradigms — including linear regression, decision trees, support vector machines, Bayesian learning, and neural networks — and understand the mathematical foundations that determine discrimination power and learning complexity.

Current Topics in Natural Language Processing

Seminar · M.Sc. Digital Humanities, M.Sc. Computer Science, M.Sc. Data Science · Irregular

This seminar covers a different topic from current NLP research each time it is offered. Students each present a paper, and at the end of the semester write up a project proposal for a new research project building on the current state of the topic. The most recent edition focused on Massively Multilingual Language Models.