The GESIS Fall Seminar in Computational Social Science features introductory and advanced courses on collecting and analyzing digital behavioral data from the web, social media, or digital archives. Courses are taught by leading experts in the field and offer plenty of opportunities to learn from and connect with other like-minded researchers. Lectures in each course are complemented by hands-on exercises, giving you the opportunity to directly implement your newly acquired skills and knowledge.
If you are new to computational social science, you may want to get an overview of debates and methods in the field in one of our blended learning introductions to computational social science with R or Python. If you plan to collect your own textual or visual data from the web, have a look at web data collection with R or Python, or learn how to collect data with smartphones and analyze the resulting data with intensive longitudinal methods. For those interested in data analysis, we offer courses on machine learning for text analysis for beginners, cutting-edge text analysis methods, computer vision, causal machine learning, and agent-based modeling.
For those without prior experience in R or Python and those who would like a refresher, we additionally offer two introductory online pre-courses for R and Pythonin the week before the start of the Fall Seminar – join those for optimal preparation!
All courses in the GESIS Fall Seminar are stand-alone and can be booked separately – feel free to mix and match courses to build your own personal Fall Seminar experience! Contact us if we can assist with tailored recommendations for possible course combinations or if you have any other questions. Learn more about our course feesand ECTS credits on our website.
