mat955 - Mathematics of Computer Science (Linear Algebra) (Complete module description)

• 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

Significant techniques and structures, systems of linear equations, vector spaces, dimension, linear maps, determinants, eigenvalues, diagonalization

S. Bosch: Lineare Algebra, Springer 2008 (4. Aufl.)
G. Fischer: Lineare Algebra, Vieweg 2010 (17. Aufl.)
B. Huppert, W. Willems: Lineare Algebra, Teubner 2010 (2. Aufl.)
M. Koecher: Lineare Algebra und analytische Geometrie, Springer 2003 (4. Aufl.)
H.-J. Kowalsky, G. Michler: Lineare Algebra, de Gruyter 2003 (12. Aufl.)
F. Lorenz: Lineare Algebra Spektrum 2008 (4. Aufl.)

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

written exam or oral exam.

Bonus points can be earned.