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Use of AI for political analysis (RSS1.05) - Confirmed

Designed for social scientists without advanced programming abilities, this one-week summer course explores how to integrate large language models (LLMs) into social science research. It provides an introduction to LLMs like ChatGPT and teaches how to use them in various settings (creating synthetic samples, testing instruments, text annotation, etc.). All coding and software for this course will be conducted in R.



    The application deadline has passed, applying is no longer possible

    This course is targeted at social scientists without advanced programming skills who are seeking to enhance their research with AI tools (specifically, large language models or LLMs). 

    As a foundation for the course, you will first receive an accessible introduction to nature and behavior of large language models (LLMs), with a focus on models like ChatGPT. The course will then turn to basic principles of interacting with LLMs (sometimes called “prompt engineering”) and the differences between various LLMs (ChatGPT, Claude 2, Bard, etc.). 

    The latter part of the course focuses on the application of LLMs to social science research questions and will be tailored to the ideas and projects that you hope to improve or expand with LLM tools. The course uses covered in the class include, but are not limited to, using LLMs to generate simulated or synthetic samples, testing survey instruments, as a tool in text coding/annotation, and as dynamic experimental treatments. You will also get a brief introduction into how to interact with LLMs through APIs, using R and RStudio. 

    The goal of the course is to offer accessible, hands-on experiences with LLMs. By the end of this course, participants will be equipped to begin to integrate LLMs into their research projects and workflow.


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    Starting date

    17 June 2024, 9 am
    Educational method
    Main Language
    17 June 2024, 9 am - 21 June 2024, 5 pm
    Ethan C. Busby
    Unique code


    Type of education
    Entry requirements
    See the requirements in cost and admission
    Study load (ECTS)
    Radboud Summer School

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    Ethan C. Busby

    Ethan C. Busby

    Ethan Busby is an Assistant Professor of Political Science at Brigham Young University, specializing in political psychology, extremism, artificial intelligence, public opinion, racial and ethnic politics, quantitative methods, and computational social science. More information can be found at His research relies on various methods, including artificial intelligence, large-language models, lab experiments, quasi-experiments, survey experiments, online conversations, text-as-data, and surveys.

    The application deadline has passed, applying is no longer possible



    • Regular: €1049 (application deadline 13th of May)
    • Student & PhD's: €699 (application deadline 13th of May)

    Includes: your course, short morning and late afternoon courses, coffee and tea during breaks, a warm lunch every day, Official Opening, MethodsNET Café (including some drinks and snacks) Official Closing (with some drinks and snacks) and a 1-year (2024 calendar year) free membership as MethodsNET regular member.

    Excludes: transport, accommodation, social events and other costs. 

    Discounts and Scholarships


    Level of participant: 

    • Master
    • PhD
    • Postdoc
    • Professional

    Admission requirements:  

    The requirements for this course are moderate familiarity with R and RStudio. Participants should bring laptop computers to the course. It will also be helpful to come to the course with research ideas and projects in mind to use with large language models. 
    Setting up an account with OpenAI (, Anthropic (, and Bard (Google's AI - will be useful but not required.

    Admission documents: