Module

Voraussetzungen

Inhalte

This module aims to teach advanced methods of scientific computing. The methodological focus lies on advanced computational techniques in numerical linear algebra and related fields. Topics include: a selection of advanced methods for computing eigenvalues and eigenvectors, singular value decomposition, numerical aspects of least-squares approximation, and a selection of matrix factorization methods.

Lernziele

Upon successful completion of the module, students will have acquired advanced knowledge for understanding modern numerical methods across a wide range of fields in science and engineering.

Prüfungsleistung

• Three written tests, 30 minutes each (each 30%) • Presentation of the practical training, 15 minutes (10%)

Bemerkungen

• Study programme Angewandte Mathematik M.Sc.: Compulsory elective module in complex „Numerics“ • Study programme Mathematik B.Sc.: Compulsory elective module in complex „Specialisation“, in limited extend • Study programme Wirtschaftsmathematik B.Sc.: Compulsory elective module in complex „Specialisation“, in limited extend • Study programme Physics M.Sc.: Compulsory elective module in complex „Minor Subject“ • Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex „Advanded Methods“ • Study programme Mathematics M.Sc.: Compulsory elective module in complex „Numerics“ • Study programme Mathematical Data Science M.Sc.: Compulsory elective module in complex „Advanced Mathematical Methods in Data Science“