Statistics for Big Data (March 21, 2022)
This term fu:stat offers the course “Statistics for Big Data”. This course can stand alone and might be seen as a complement to traditional statistical courses.
"Statistics for Big Data" will give a introduction into the following topics:
- Clustering (SOM and k-means extensions)
- Classification (Decision trees, Boosted trees and Random forest)
- Regression (Ridge regression, Lasso regression and Elastic Net)
|Instructor||Patrick Krennmair/ Akira Karimkhani|
|Number of Places||about 30 participants (fu:stat reserves the right to rescedule or cancel the course if the number of participants lies below 15)|
|Registration||→ Register online|
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 Fee||60 € for students (incl. PhD), 120 € for employees, for members of Potsdam Graduate School (20 € PhD-students, 30 € Postdocs).|
|Room||FB Wirtschaftswissenschaft, Garystr. 21, 14195 Berlin HS 102|
Monday, March 21, 2022, 9:00 a.m. to 5:00 p.m.
Students and employees of all universities
Participants should possess knowledge of basic statistical methods, such as hypothesis testing and linear regression.
The course provides a first insight into the well-established keyword: Big Data. 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.