Statistics, Econometrics and Quantitative Methods

S317 Machine Learning for Economists

Lecturer:   Martin Kroczek, Philipp Kugler

B.Sc. in Economics and Business Administration
B.Sc. in International Economics
B.Sc. in International Business Administration

Prerequisites:   Quantitative Methods in Economics and Business Administration recommended
Language:   English
Time and Place:  

Lecture + Tutorial:
Mon 8-10, PC-Lab Nauklerstr.
Mon 10-12 (every other week), PC-Lab Nauklerstr.

Start:   16.10.2023
Exam:   Written Exam (60 Min), group assignments, data project
Credits Points:  



To be announced

Course information

This course offers an introductory view to various tools of statistical learning. The main topics of the course are supervised machine learning methods such as shrinkage methods, tree based methods, and neural networks. At the end, we will discuss the link between machine learning methods and conventional econometric analysis. A PC-lab class is an essential part of the module.


James/Witten/Hastie/Tibshirani: An Introduction to Statistical Learning