GESIS Fall Seminar in Computational Social Science

The GESIS Fall Seminar in Computational Social Science takes place in Mannheim and online. Its courses are taught by both GESIS and international experts and cover methods and techniques of working with digital behavioral data. The Fall Seminar targets advanced graduate or PhD students, post-docs, junior and senior researchers in the social sciences, data science, communication science, or digital humanities who collect and analyze data from the web, social media, or digital text archives. Participants can pick from nine week-long courses, including introductory courses on Computational Social Science, Web Data Collection, or Machine Learning, and more specialized topics such as Automated Image and Video Data Analysis, Agent-Based Computational Modeling, Deep Learning for Advanced Computational Text Analysis, or Network Analysis. Lectures in each course are complemented by hands-on exercises giving participants the opportunity to apply these methods to data. All courses are held in English.

For those without any prior experience in R or Python and those who’d like a refresher, we’re additionally offering two pre-courses “Introduction to R” and “Introduction to Python” (three to four days, online) in the week before the start of the Fall Seminar – join those for optimal preparation! 

All courses are stand-alone and can be booked separately – feel free to mix and match to build your own personal Fall Seminar experience that perfectly suits your needs and interests. For some recommendations of possible course sequences, click here. 

► Find more information on course fees, ECTS credits, and how to contact us on our website. 

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Each course has specific prerequisites, which will be detailed on the course websites. In addition, all Fall Seminar participants are expected to:

• have basic knowledge of empirical research methods;
• have a good command of English.