|Registration is open until||19.10.2023 - 22:59 o'clock|
|Start date||02.11.2023 - 15:00 o'clock|
|End date||03.11.2023 - 16:00 o'clock|
until 05.10.2023100 Euro
Machine learning cannot do without algorithms and statistical methods. Aimed at predictive analytics, some of these algorithms and methods are core to machine or statistical learning. The course introduces these learning methods, covers their basics, components and variants, and shows how they can be practically applied in the context of regression and classification and how their results can be interpreted. Linear and logistic regression, regression splines for modeling non-linear relationships as well as regression-, similarity-, probability- and information-based classification are treated.
A three-hour LIVE session is planned for each of the 2 course days, as well as time to work on exercises and discuss them with the lecturer.
At the latest by the registration deadline fourteen days before the start of the course, the persons taking part in the course will receive access to the instructional videos of the course - in addition to the course documents. These videos provide a first introduction to the subject matter and show practical programming applications. They serve to prepare the course participants for the live course and are taken up in the course, continued and included in the discussion.
The mornings are all about the theoretical introduction to the subject, the demonstration of application examples and the discussion of this content and applications. The presentation and discussion phases are balanced in terms of time. The afternoons are about practice and programming and about independent application of the previously taught material in the digital lab.
Priorities in terms of content can be set at any time in consultation with the participants.