General description
Natural Language Processing (NLP) is a discipline that focuses on the interaction between linguistics, computer science, and artificial intelligence. The research domain is particularly concerned with learning machines to read, understand and derive meaning from natural language. The participants of this course will learn important theoretical concepts in NLP (e.g. language models, machine learning) and specific applications (e.g. sentiment analysis). Furthermore, they will acquire basic programming skills in Python by learning fundamental concepts such as variables, operators, conditions, loops and using libraries that are specifically developed for text analysis.
The sessions are organized as follows: NLP fundamentals will be taught in the morning session, which is then followed by a Python course in the afternoon. Both sessions are hands-on; participants will digest the knowledge by exercising on their laptop.
Target audience
PhD students with a background in (applied) linguistics, translation or interpreting studies and an interest in digital techniques.
Course prerequisites
No prior knowledge about programming or NLP is required.
Course materials
Copies of slides and programming exercises will be provided. The participants are free to bring their own laptops (with Internet connection) or to use PCs provided in the classroom (using guest accounts provided by the UGent).
Teacher bio
Dr. Cynthia Van Hee is a lecturer and post-doctoral researcher at the LT3 Language and Translation Technology Team at Ghent University, active in the field of computational linguistics and machine learning. She holds a PhD in linguistics on Automatic Irony Detection on Social Media. As a postdoc researcher, her main research focus lies on automatic (implicit) sentiment analysis. She teaches Audiovisual Language Techniques, Natural Language Processing, Project Management, Desktop Publishing, Subtitling and Dissertation.
Joni Kruijsbergen is a PhD student in the Language and Translation Technology Team at Ghent University, where she researches automated writing support for Dutch learner writing. She obtained a Masters degree in Computational Linguistics and then an Advanced Masters degree in Speech and Language Technology (AI), both of which at KU Leuven.
Colin Swaelens is a PhD student at the Language and Translation Technology Team at Ghent University, with a specific research interest in natural language processing of ancient languages. He obtained a degree in classics (KU Leuven) and then the Advanced Masters degree in Artificial Intelligence (KU Leuven).
Schedule
- Monday 14/07/2025, 9:00-10:30 & 11:00-12:30
- Tuesday 15/07/2025, 9:00-10:30 & 11:00-12:30
- Wednesday 16/07/2025, 9:00-10:30 & 11:00-12:30
- Thursday 17/07/2025, 9:00-10:30 & 11:00-12:30
- Friday 18/07/2025, 9:00-10:30 & 11:30-12:30