Large Language Models for Health and Social Science Research - Special Rate

Date: 29th June through 3rd July 2026.

By: Daniel Valdenegro (Teaching Assistant to be Confirmed)

Location: Nuffield College, University of Oxford

Course fee £300

For Students £225

Registration Closes: 23:59 GMT, 18th June 2026

Course Description

Course Description: Artificial Intelligence (AI) and Large Language Models (LLMs) have become ubiquitous concepts in research and everyday life. The demand for a clear, grounded understanding of the capacities and shortcomings of these tools will only grow as their popularity increases. In this 5-day intensive course, we will explore the fundamental theoretical and practical aspects of using Large Language Models in health and social science research, maintaining a grounded and critical stance. We will examine the origins and development of the core architectures powering today’s most widely used language models, as well as their current applications in research, complemented by practical sessions on how to work with both commercial and locally hosted models.

Each day runs from 9:30 to 16:30, with:

Morning lectures (9:30–12:30): Concepts, theory, and methods.
Lunch (12:30–13:30): Provided at Nuffield College.
Afternoon practicals (13:30–16:30): Guided coding sessions, data activities, research talks, and group exercises By the end of this course, you will gain:

1. A working knowledge of how LLMs are trained, evaluated, and applied in research.
2. Practical skills in accessing, fine-tuning, and applying LLMs to real-world datasets.
3. Critical tools to assess bias, ethics, and reproducibility in LLM-driven research.
4. Exposure to interdisciplinary projects at the intersection of AI, health, and the social sciences.

Lunch and refreshments are provided daily, fostering an informal, collaborative learning environment in the heart of Oxford’s academic community. Course content by day:

Day 1: Foundations – Introduction to NLP and initial language models: tokenization, embeddings, RNN-LSTM vs Attention, Text-generation Transformer Models.
Day 2: Applications – Advent of Large, transformer-based, text-generation language models: Emerging capacities in summarization, classification and information extraction. Review of application in health and social science research. Practical session on this tasks.
Day 3: Use: Review of current commercial and open-source models. Review of the API use and local hosting options.