Modern Text Analysis and NLP with Python by Dr Patrick Gildersleve
This workshop offers students hands-on experience of modern approaches in text analysis and natural language processing (NLP) using Python. We will start with the essential preprocessing steps that allow us to apply standard machine learning models to text. Then, we will journey through more advanced methods such as text embeddings, named entity recognition, neural topic modelling, exploring transformers, and interfacing with state-of-the-art Large Language Model APIs. Participants will apply these techniques to various social science research scenarios, equipping them with a powerful toolkit for handling text data across diverse fields and providing an entry into the fast-developing methodological area of advanced NLP. Students should have a pre-existing understanding of coding in Python and general principles of machine learning. Prior experience in text analysis is optional.
Session Details
Time: 10:00 - 15:00 (12:00 - 13:00 Lunch break)
Date: 27 May 2025
Mode: Hybrid - In person at CON 1.01 and on Zoom
Please note that in-person attendance will be prioritised/ preferred for this course, as remote debugging will be difficult.
All session materials and the Zoom link will be circulated after the sign-up closes on 26 May.
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