250337 VO Introduction to linear algebra and geometry (2008S)
Labels
Details
Language: German
Lecturers
Classes (iCal) - next class is marked with N
- Monday 21.04. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 23.04. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 28.04. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 30.04. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 05.05. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 07.05. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 14.05. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 19.05. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 21.05. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 26.05. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 28.05. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 02.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 04.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 09.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 11.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 16.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 18.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Monday 23.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
- Wednesday 25.06. 17:00 - 19:00 Hörsaal 3 2A211 2.OG UZA II Geo-Zentrum
Information
Aims, contents and method of the course
Assessment and permitted materials
Minimum requirements and assessment criteria
understanding of the subject
Examination topics
lecture
Reading list
(Auswahl) Gilbert Strang, Lineare Algebra; Howard Anton: Lineare Algebra; Herbert Muthsam: Linear algebra und ihre Anwendungen; H.-J. Kowalsky, G. O. Michler: Lineare Algebra
Association in the course directory
EHM
Last modified: Sa 02.04.2022 00:24
vectors, matrices, inner product, norm; systems of linear equations, Gaussian algorithm; abstract vector spaces with K^n as standard example; subspaces, linear independence, basis, dimension; linear mappings, image, kernel, change of bases, elementary matrix transformations, rank; inversion of matrices