This course is specifically aimed at young and advanced researchers from any research field who want to acquire a more in-depth theoretical understanding of several data science-related topics. Researchers from universities, research institutes, and research departments are welcome to join the course. Participants should already have basic knowledge in statistics, data analysis and machine learning as the course will have a strong focus on methodological and theoretical foundations of advanced topics. As a prerequisite for the course, participants should be familiar with the content of the online lecture "introduction to machine learning" (see https://compstat-lmu.github.io/lecture_i2ml). If this is not the case, participants are expected to study the contents from this online lecture either in a self-study or by visiting a separate machine learning course, e.g., https://www.essentialds.de/kurse/machine-learning-r.
General Information
- Duration: 10 days, from 11th of November 2019 to 22th November 2019 (9 a.m. - 5 p.m.) and on Friday, 29th of November an assessment of the learning progress in a test with short questions
- Language of instruction: The planned course language is English unless all participants understand German well enough
- Please click here to see the Curriculum
- Trainer/in: Bernd Bischl
- Trainer/in: Giuseppe Casalicchio
- Trainer/in: Göran Kauermann
- Trainer/in: Peer Kröger
- Trainer/in: Nils Otto vor dem Gentschen Felde
- Trainer/in: Janek Thomas
- Trainer/in: Markus Wiedemann