| Topic | Natural language processing with R |
| Time | 9, 10, 11 January 2023 |
| Duration | 15:00 - 18:00 |
| Location | Virtual |
| Speaker | Julia Silge |
| Content | Introduction to basic methods of natural language processing |
| Topic | Introduction to Qualitative Research and the Grounded Theory Approach |
| Time | 9 November 2023 |
| Duration | 08:00 - 16:00 |
| Location | Missionsstrasse 64a, room 00.007 |
| Speaker | Annika Wilhelmy |
| Content | Introduction to qualitative research methods, followed by a deep-dive into interviews and the grounded theory approach |
| Topic | Papaja (Preparing APA Journal Articles) - R package |
| Time | 22 February 2023 |
| Duration | 15:00 - 16:30 (90 minutes, 60 minutes presentation + 30 minutes Q&A) |
| Location | Virtual (Link coming soon) |
| Speaker | Frederik Aust |
| Topic | The future of digital health promotion and treatment |
| Time | 29 March 2023 |
| Duration | 10:00 - 11:30 (90 minutes, 60 minutes presentation + 30 minutes Q&A) |
| Location | Virtual (Link coming soon) |
| Speaker | Dominika Kwasnicka |
| Idea | Time to focus on writing, coding, launching that new project! |
| Date | 8. - 10. December 2023 |
| Location | Gut Lilienfein, Wieden (Germany) |
| Expert | TBC |
| Topic | Machine Learning with R |
| Time | 7 October |
| Duration | 9:00 - 17:00 |
| Location | In person, Biozentrum, room 02.094 |
| Speaker | Markus Steiner |
| Content | Introduction to basic principles (preprocessing, fitting, prediction, optimization) and implementation of machine learning using the new tidymodels framework in R |
CODING RETREAT
| Topic | Data Analytics |
| Time | 11. - 13. November |
| Duration | 3 days (2 nights) |
| Location | Gut Lilienfein, Wieden, Germany |
| Expert | Markus Steiner |
| Content | The coding retreat will provide participants the opportunity to advance a data analytic project in an environment that affords focused work and provides expert and peer support. The coding retreat will take place over 3 days (2 nights) in a seminar hotel in the Black Forest. Joining the participants will be a tutor with broad expertise in programming and statistical methods who will support the data analytic projects with expert advice. Furthermore, we will create a buddy system to encourage peer support. Participants will be instructed to select a specific data analytics project that involves applying new methodology to an existing data set. |