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Introduction to Statistical Learning (March 17th, 2025)

This term fu:stat offers the course “Introduction to Statistical Learning”. This course can stand alone and might be seen as a complement to traditional statistical courses.

"Introduction to Statistical Learning" will give a introduction into the following topics:

  • Visualization
  • Clustering (SOM and k-means extensions)
  • Classification (Decision trees, Boosted trees and Random forest)
  • Regression (Ridge regression, Lasso regression and Elastic Net)
InstructorFelix Skarke/ Vincent Keyaniyan
Number of Placesabout 30 participants (fu:stat reserves the right to rescedule or cancel the course if the number of participants lies below 15)
Registration→ Register online
Registration Mode

General information about our course offers (questions about the group of participants, registration or cancelation, about payment, organsation, certificates of participation etc.) you can find here

Participation Fee60 € for students (incl. PhD), 120 € for employees, members of Potsdam Graduate School please register through the PoGS website, Financial support of Dahlem Research School: Doctoral candidates of the Berlin University Alliance can participate in this course cost free as long as budget lasts.
RoomFB Wirtschaftswissenschaft, Garystr. 21, 14195 Berlin HS 105
Time

Monday, March 17th, 2025, 9:00 a.m. to 5:00 p.m.

Student Profile

Students and employees of all universities

Requirements

Participants should possess knowledge of basic statistical methods, such as hypothesis testing and linear regression.

Description:

The course provides a first insight into statistical learning, which refers to a set of tools for modeling and understanding complex datasets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine learning. With the explosion of “Big Data” problems, statistical learning has become a very hot field in many scientific areas as well as marketing, finance and other business disciplines. Besides an introduction to the characteristics, benefits and challenges of Big Data, four applications from the field of statistics are presented. This course addresses all who want to enlarge their knowledge of traditional statistics. Thus, a basic knowledge of statistics (at least up to linear regression) is mandatory. Please note that this course has a statistical focus, therefore technical issues like memory allocations and data storage are not included.

Important information for the registration

After filling out the registration form below, you will receive a within 7 days to your specified email address.