Natural Language Processing

This class is offered in German this semester.

Registration via LSF

The module Natural Language Processing provides a broad overview of research on developing systems to process textual human language data (no recognition of audio or handwriting). Beginning with early foundations in information retrieval and full-text search, over approaches to cluster text and model topics, we continue to the area of neural networks and embeddings, and touch the ideas of the transformer, the GPT and ChatGPT models.

This is an algorithm-oriented computer science class, and not designed to be an interdisciplinary module. The focus is on the algorithms, the foundations, the theory, and the data structures, as well how to implement and optimize them. We do not focus on applications or tools, as these constantly evolve, and are quickly obsolete. This lecture aims to teach you lasting knowledge of the foundations and the skills to acquire the latest ideas and develop future methods yourself. Good programming skills are a prerequisite. We -unfortunately- see high drop-out rates for attendees that do not have the necessary background.

Contents

Lecture contents include, but are not limited to:

Requirements: