Fall Seminar - Course Recommendations

All courses in the GESIS Fall Seminar are stand-alone and can be booked separately – feel free to mix and match to build your own personal Fall Seminar experience! Below, you can find some of our recommendations for possible course combinations.

If you are starting from scratch and would like to go from zero to hero in Computational Social Science with either R or Python, we suggest taking one of these course sequences:

Week 0 (26-29 Aug): Introduction to Python (online workshop)
Week 1 (30 Aug-05 Sep): Introduction to Computational Social Science with Python (blended learning online course)
Week 2 (09-13 Sep): Automated Web Data Collection with Python and R (in-person course)
Week 3 (16-20 Sep): Introduction to Machine Learning for Text Analysis with Python (in-person course) or Agent-Based Computational Modeling (in-person course)

Week 0 (27-29 Aug): Introduction to R (online workshop)
Week 1 (30 Aug-05 Sep): Introduction to Computational Social Science with R (blended learning online course)
Week 2 (09-13 Sep): Automated Web Data Collection with Python and R (in-person course)
Week 3 (16-20 Sep): Introduction to Social Network Analysis with R (in-person course) or Agent-Based Computational Modeling (in-person course)

If you are planning to collect and analyze your own text or visual data from the web, have a look at these courses:

Week 2 (09-13 Sep): Automated Web Data Collection with R and Python (in-person course)
Week 3 (16-20 Sep): Introduction to Machine Learning for Text Analysis with Python (in-person course)
Week 4 (23-27 Sep): From Embeddings to LLMs: Advanced Text Analysis with Python (in-person course) or Automated Image and Video Data Analysis (live online course)

If you want to study social networks, you might find these three courses interesting:

Week 2 (09-13 Sep): Automated Web Data Collection with R and Python (in-person course)
Week 3 (16-20 Sep): Introduction to Social Network Analysis with R (in-person course)
Week 4 (23-27 Sep): Advanced Social Network Analysis (in-person course)

If you need any advice on which course(s) might be the right one(s) for you, please do not hesitate to contact us. We’re happy to help!