Studienhandbuch | KV Algorithmic methods in numerical analysis

Inhalt

^(*) Unfortunately this information is not available in english.

Workload	Education level	Study areas	Responsible person	Hours per week	Coordinating university
3 ECTS	B1 - Bachelor's programme 1. year	Mathematics	Helmut Gfrerer	2 hpw	Johannes Kepler University Linz

Detailed information

Original study plan

Bachelor's programme Technical Mathematics 2025W

Learning Outcomes

Competences
Students are familiar with the special features of scientific computing and with the basic problems and solution algorithms of numerical linear algebra.

Skills	Knowledge
determine the condition of a mathematical problem; understand the influence of rounding errors; understand various matrix decomposition methods; solve linear systems of equations and equalisation problems numerically; know and analyse iterative methods for the solution of systems of equations;	Error analysis, Gaussian elimination method, Cholesky decomposition, QR decomposition, eigenvalue and singular value decomposition, normal equations, Jacobi and Gauss-Seidel methods;

Criteria for evaluation

^(*)Programmieraufgaben + mündliche Prüfung

Methods

^(*)Tafelpräsentation

Language

German

Study material

^(*)Vorlesungsskriptum

Changing subject?

Corresponding lecture

^(*)TM1PGKVALG2: KV Algorithmische Methoden 2 (3 ECTS)

On-site course
Maximum number of participants	-
Assignment procedure	Direct assignment