Are you working with text and looking for new ways to tackle language-related tasks?

Large Language Models (LLMs) might be just the tool you need! This master-class introduces LLMs in the context of social sciences, offering hands-on, practical experience - no coding expertise or advanced maths skills required.

You'll explore the basics of Natural Language Processing (NLP) and LLMs, diving into real-world applications like text classification, topic modeling, and text generation. We’ll be using Python and Google Colab, but don’t worry if you have no prior programming experience—we’ve got you covered every step of the way.

Our focus is on equipping you with practical skills that you can directly apply to your research. Need to analyze a large body of diverse literature, bulk social media discussions, interview responses, or news articles? Want to detect emerging trends, automate qualitative coding in interviews, or generate synthetic survey responses to test hypotheses? LLMs are revolutionizing how we understand and process text-based data in the social sciences—and this is just the beginning. Don’t miss out!

The course requires understanding of a basic of statistical concepts and text analysis tasks, exposure to machine learning foundations is beneficial as well, such as ACSPRI's Machine Learning for Data Science: Surpervised Learning Techniques

The course assumes no prior knowledge of Python, though some programming experience (e.g. using R) is beneficial.

By the end of the course, you won’t just know about LLMs—you’ll know how to use them to solve real problems (your research problems in the first place), manage data efficiently, and generate results that MATTER. Whether you're a researcher looking to enhance your studies or a professional aiming to leverage AI for industry insights, this course gives you the hands-on experience and tools to stay ahead in the fast-changing world of AI-powered text analysis.

The course uses Google Colab and requires a Google account (please make sure you have one or please register one before the session)

All course materials will be provided