This course is aimed at Master's students in Statistics and Data Science. Its goal is to deepen students' ability to apply deep learning methods in practice. Most projects are research-oriented and always supervised by one of the course instructors.
As in the Statistical Consulting course, projects are assigned based on availability. If you are interested in a guided research project, please familiarize yourself with the instructors' research and submit an application.
Trainers:
- David Rügamer
- PhD Students in the muniq.ai group
- Mina Rezeai
Enrollment Key: ApplDeeLear
- Викладач: Rezaei Mina
- Викладач: Rügamer David
Information on how to do your thesis in Bachelor and Master Statistics and Data Science.
Key: Ludwig33
- Викладач: Bender Andreas
- Викладач: Bischl Bernd
- Викладач: Boulesteix Anne-Laure
- Викладач: Drechsler Jörg
- Викладач: Haensch Anna-Carolina
- Викладач: Heumann Christian
- Викладач: Hoffmann Sabine
- Викладач: Höhler Lea
- Викладач: Kauermann Göran
- Викладач: Kern Christoph
- Викладач: Kreuter Frauke
- Викладач: Müller Christian
- Викладач: Nagler Thomas
- Викладач: Rügamer David
- Викладач: Sakshaug Joseph
- Викладач: Scheipl Fabian
- Викладач: Schmid Volker
- Викладач: Schomaker Michael
- Викладач: Schomaker Michael
- Викладач: Wilhelm Daniel
This course is aimed at students of statistics in the master's program (PO2010 & PO2021). Its goal is to deepen the ability to work in an interdisciplinary way and practice the communication of statistical methods and results.
The course consists of 2 parts. The first part consists of a self-study introductory video course and an online test. The second part consists of working on a project in groups of 2-3 students each. This project can be started at any time after finishing the first part, even outside of lecture times.
Important:
Please enroll in the course with enrollment code "Consulting" to be informed by mail about current lecture dates, open projects and upcoming introductory events.
The course consists of 2 parts. The first part consists of a self-study introductory video course and an online test. The second part consists of working on a project in groups of 2-3 students each. This project can be started at any time after finishing the first part, even outside of lecture times.
Important:
Please enroll in the course with enrollment code "Consulting" to be informed by mail about current lecture dates, open projects and upcoming introductory events.
- Викладач: Aßenmacher Matthias
- Викладач: Bender Andreas
- Викладач: Bischl Bernd
- Викладач: Brunner Martina
- Викладач: Casalicchio Giuseppe
- Викладач: Haensch Anna-Carolina
- Викладач: Hoffmann Sabine
- Викладач: Kauermann Göran
- Викладач: Racek Daniel
- Викладач: Radermacher Walter
- Викладач: Rügamer David
- Викладач: Scheipl Fabian
- Викладач: Windmann Michael