Courses

Natural Language Processing

Fall 6 ECTS

Students will get familiar with common concepts and tasks in NLP. They will learn how to evaluate NLP technologies and frameworks and gain practical experience during the laboratory sessions. They will get a deep understanding of the methods underlying modern transformer-based language models, but at the same time get an understanding of how the field of NLP went from rule-based to more and more data-driven methods. They will also gain basic skills needed for conducting NLP research, such as reading papers, critically discussing results and finding possible ways of improvement. Lastly, they will learn to reflect on the impact of modern NLP technologies on society.




Reflections on AI for Communication

Fall 3 ECTS

The course will cover - among others - the following topics:

  • Introduction to Natural Language Processing (NLP) and Artificial Intelligence (AI)
  • Ethical issues of AI and AI regulations

The aim of this course is to make students critically reflect on the use of AI for communication purposes, to understand the many opportunities it brings, but also to review the attested negative effects, and to discuss possible positive and negative long-term impact on society. In order for students to be able to critically reflect on the societal impact of AI for communication, the course will start with an introduction to NLP, including Machine Learning (ML) and Large Language Models (LLMs) using excerpts from a textbook on NLP (Jurafsky and Martin, 2025). The focus will be on text-based models, but we will also touch upon other modalities such as vision. These introductions will make students understand the machinery behind AI tools that are currently widely used, such as AI chatbots, machine translation, and content generation tools using generative AI. After these introductions, the main topics in AI ethics, such as bias, issues related to data, transparency, privacy as well as initiatives for AI regulation will be discussed. Especially, this latter part of the course requires active student involvement and critical reflection. Students give presentations and co-lead class discussions with help from the lecturer.




NLP for Business and Finance

Spring 3 ECTS

The course will cover - among others - the following topics:

  • Introduction to Natural Language Processing (NLP)
  • Introduction to Machine Learning
  • Basic Python programming
  • Overview of NLP applications most relevant to business and finance