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05.12.2021 00:23:00
mat955 - Mathematics of Computer Science (Linear Algebra) (Course overview)
Department of Mathematics 6 KP
Module components Semester courses Wintersemester 2019/2020 Examination
Lecture
Exercises
  • No access 5.01.957 - Übung Lineare Algebra für Informatiker Show lecturers
    • Prof. Dr. Anne Frühbis-Krüger
    • Dr. Bernd Schober

    Monday: 12:00 - 14:00, weekly (from 21/10/19), Location: W32 1-113
    Monday: 14:00 - 16:00, weekly (from 21/10/19), Location: W16A 004
    Monday: 14:00 - 16:00, weekly (from 21/10/19), Location: W04 1-172
    Monday: 16:00 - 18:00, weekly (from 21/10/19), Location: W01 0-015
    Monday: 16:00 - 18:00, weekly (from 21/10/19), Location: W03 1-154
    Friday: 14:00 - 16:00, weekly (from 18/10/19), Location: W32 1-113
    Friday: 14:00 - 16:00, weekly (from 06/12/19), Location: W01 1-117
    Dates on Thursday. 21.11.19 18:00 - 20:00, Friday. 22.11.19 16:00 - 18:00, Monday. 25.11.19, Tuesday. 17.12.19 - Wednesday. 18.12.19 18:00 - 20:00, Friday. 20.12.19 16:00 - 18:00, Tuesday. 07.01.20, Thursday. 09.01.20 18:00 - 20:00, Friday. 10.01.20 16:00 - 18:00, Friday. 10.01.20 18:00 - 20:00, Friday. 07.02.20 09:00 - 11:15, Monday. 10.02.20 10:00 - 12:15, Monday. 10.02.20 14:15 - 16:30 ...(more)
    Location: W32 0-005, W01 0-015, W01 0-006 (+2 more)

Notes for the module
Module examination
written exam or oral exam.

Bonus points can be earned.
Skills to be acquired in this module
• 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