Course content
This course introduces the theory and practice of natural language processing (NLP), with a strong focus on modern large language models (LLMs). You will learn how these models are structured, how they are trained on large-scale text data, and how they are fine-tuned and evaluated on downstream tasks. By the end of the course, you will be able to explain how LLMs work and understand their limitations. The course also addresses societal and environmental considerations, including bias and the computational cost of large-scale models.
Course outline
The course follows a flipped classroom format. Before each topic, you prepare by watching short video lectures and completing diagnostic quizzes that help you check your understanding. You then participate in an online teaching session focused on clarification of key concepts, problem-solving, and discussion. Each topic concludes with a hands-on assignment in which you implement or experiment with NLP models using Python.
Throughout the course, you receive continuous support and feedback via email and individual video meetings with the course instructors.
The total workload for the course is approximately 80 hours: about 40 hours for video lectures, quizzes, and teaching sessions, and about 40 hours for completing and reflecting on the practical programming assignments.
For more information see https://liu-nlp.ai/ete387/
Information on entry requirements
You must prove that you fulfil the entry requirements when applying for the course. If your grades are not already on your pages at antagning.se, you need to upload them in connection with your application.