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103-0849-AAL 4 Credits MSC D-BAUG
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Multivariate Statistics and Machine Learning

Lecturers & Examiners: Prof. Dr. Konrad Schindler
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
VVZ CR n/a

Last Updated: 2026-06-01 11:31:12

Abstract

Introduction to statistical modelling and machine learning.

Objective

The goal is to familiarise students with the principles and tools of machine learning, and to enable them to apply them for practical data analysis.

Content

multivariate probability distributions; comparison of distributions; regression; classification; model selection and cross-validation; clustering and density estimation; mixture models; neural networks

Resources

Literature

- Hastie, Tibshirani, Friedman: The Elements of Statistical Learning, Springer 2009 - Bishop: Pattern Recognition and Machine Learning, Springer 2006 - Duda, Hart, Stork: Pattern CLassification, Wiley 2012

General Information

Language
English
Levels
MSC
Frequency
Semesterly recurring

Examination

Type
graded semester performance

Course Components

Type Title Time & Place Hours
revision course / private study Multivariate Statistics and Machine Learning
Self-study course. No presence required.
No time listed 120 h semesterly

Offered In