General description
This module introduces students to the core principles and methods of natural language processing (NLP) and data-driven AI. Students examine how NLP systems analyse and interpret human language, progressing from word-level processing (i.e., tokenisation, lemmatisation, part-of-speech tagging, named entity recognition, dependency parsing) to corpus analysis, syntactic parsing and semantic modelling using language models and word vectors. Building on this linguistic foundation, the course then explores the workflow of data-driven machine learning, including the development and evaluation of systems applied to real-world tasks such as sentiment analysis and readability prediction. Ethical issues related to language data and model bias are addressed throughout, providing students with a broad understanding of how NLP and ML systems are designed and assessed.
As from 2026 onwards, this module can be followed together with module 13 Introduction to Python in a complete NLP track for this Summer School.
Target audience
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 will be provided, as well as references for background/further reading. The participants are free to bring their own laptops (with Internet connection or using guest accounts provided by the UGent).
Teacher bio
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 sentiment analysis, irony and data preprocessing. As a lecturer, she teaches courses within the field of computational linguistics (NLP, Python, …), audiovisual translation and digital communication.
Schedule
- Monday 13/07/2026, 9:00-10:30 & 11:00-12:30
- Tuesday 14/07/2026, 9:00-10:30 & 11:00-12:30
- Wednesday 15/07/2026, 9:00-10:30 & 11:00-12:30
- Thursday 16/07/2026, 9:00-10:30 & 11:00-12:30
- Friday 17/07/2026, 9:00-10:30 & 11:30-12:30