mat955 Mathematics of Computer Science (Linear Algebra) (Course overview)

mat955 Mathematics of Computer Science (Linear Algebra) (Course overview)

Department of Mathematics 6 KP
Module components Semester courses Wintersemester 2021/2022 Examination
Lecture
Exercises
Hinweise zum Modul
Further information

Module Capacity:
unrestricted

Links:
S. Bosch: Lineare Algebra, Springer 2014 G. Fischer: Lineare Algebra, Springer 2014 G. Fischer: Lernbuch Lineare Algebra und Analytische Geometrie, Springer 2017 B. Huppert, W. Willems: Lineare Algebra, Springer 2010 M. Koecher: Lineare Algebra und analytische Geometrie, Springer 2003 H.-J. Kowalsky, G. Michler: Lineare Algebra, de Gruyter 2003 F. Lorenz: Lineare Algebra, Spektrum 2008
Method of assesment
written exam or oral exam.

Bonus points can be earned.
Learning outcomes/competencies
• Getting to know and to understand the axiomatic structure of mathematics and the importance of mathematical reasoning
• Mastering basic mathematical proof techniques and their logical structure
• Recognizing the relevance of premises in mathematical theorems: Localization of premises within proofs and possible consequences if premises are not met
• Learning the significant ideas and methods of linear algebra
• Mastering the fundamental concepts of algebra, such as groups, rings, fields
• Mastering the fundamental concepts and significant methods of linear algebra, such as systems of linear equations, Gaussian algorithm, vector spaces, dimension, linear maps, matrices, determinants
• Mastering of further notions and methods of linear algebra, e.g. eigenvectors, eigenvalues, diagonalization