***Apologies for cross-posting*** Dear colleagues, We are excited to announce the program of the GESIS Fall Seminar in Computational Social Science 2021, held virtually from 13 September to 01 October 2021. The GESIS Fall Seminar targets social scientists, data scientists, and researchers in the digital humanities that want to collect and analyze data from the web, social media, or digital text archives. Organized along two parallel tracks, it offers six one-week courses on computational social science methods and techniques using either R or Python. 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. Computational Social Science with R Introduction to Computational Social Science with Applications in R (13-17 September)<https://training.gesis.org/?site=pDetails&child=full&pID=0x5F6D5D9F21934389B6F217EA093F8180&subID=0xAA223D757BBE443588588573DC340480> Dr. Aleksandra Urman, University of Bern / University of Zurich (Switzerland) Max Pellert, Medical University of Vienna / Technical University of Graz (Austria) Automated Web Data Collection with R (20-24 September)<https://training.gesis.org/?site=pDetails&child=full&pID=0x5F6D5D9F21934389B6F217EA093F8180&subID=0xB5D4F105772F45B58972878A8465229C> Dr. Theresa Gessler, University of Zurich (Switzerland) Hauke Licht, University of Zurich (Switzerland) Social Network Analysis with R (27 September-1 October)<https://training.gesis.org/?site=pDetails&child=full&pID=0x5F6D5D9F21934389B6F217EA093F8180&subID=0xBAF346ACAB3249D6A6514D579A4E06E9> Dr. Silvia Fierăscu, West University of Timișoara (Romania) Ianis Rușitoru, West University of Timișoara (Romania) Computational Social Science with Python Introduction to Computational Social Science with Python (13-17 September)<https://training.gesis.org/?site=pDetails&child=full&pID=0x5F6D5D9F21934389B6F217EA093F8180&subID=0x883C13C86BDD484F855B36E1CABD2A77> Dr. Orsolya Vásárhelyi, University of Warwick (United Kingdom) Luis Natera, Central European University Budapest (Hungary) Web Data Collection and Natural Language Processing in Python (20-24 September)<https://training.gesis.org/?site=pDetails&child=full&pID=0x5F6D5D9F21934389B6F217EA093F8180&subID=0x94A20B73CE614C7B828751FEFBFFFF36> Indira Sen, GESIS (Germany) Dr. Arnim Bleier, GESIS (Germany) Julian Kohne, GESIS (Germany) Dr. Fabian Flöck, GESIS (Germany) A Practical Introduction to Machine Learning in Python (27 September-1 October)<https://training.gesis.org/?site=pDetails&child=full&pID=0x5F6D5D9F21934389B6F217EA093F8180&subID=0xD00A750313384AFC8E83C510C6662B3B> Assoc. Prof. Damian Trilling, University of Amsterdam (Netherlands) Assist. Prof. Anne Kroon, University of Amsterdam (Netherlands) Courses will be held online via Zoom and can be booked either separately or as a block. There is no registration deadline, but places are limited and allocated on a first-come, first-served basis. To secure a place in the course(s) of your choice, we strongly recommend that you register early. Thanks to our cooperation with the a.r.t.e.s. Graduate School for the Humanities at the University of Cologne, participants of the GESIS Fall Seminar can obtain 2 ECTS credit points per one-week course. For detailed course descriptions and registration, please visit our website<https://www.gesis.org/en/gesis-training/what-we-offer/fall-seminar-in-computational-social-science> and sign up here<https://training.gesis.org/?site=pOverview&cat=Methodenseminar>! For further training opportunities, have a look at our Summer School in Survey Methodology<https://www.gesis.org/en/gesis-training/what-we-offer/summer-school-in-survey-methodology> and workshop program<https://training.gesis.org/?site=pOverview&cat=Workshop>. Feel free to forward this announcement to other interested parties. --- Dr. Marlene Mauk Scientific Coordinator GESIS Fall Seminar in Computational Social Science GESIS – Leibniz Institute for the Social Science www.gesis.org/fallseminar fallseminar@gesis.org<mailto:fallseminar@gesis.org> Please find our data protection information here: https://www.gesis.org/en/institute/data-protection