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t.BA.ITM.HM2.19HS (Higher Mathematics for Computer Scientists 2)
Module: Higher Mathematics for Computer Scientists 2
This information was generated on: 28 March 2024
No.
t.BA.ITM.HM2.19HS
Title
Higher Mathematics for Computer Scientists 2
Organised by
T IAMP
Credits
4
Description
Version: 4.0 start 01 February 2021
Short description
Using Python, students learn the advanced basics of numerical mathematics for computer scientists. Topics include the numerical solution of nonlinear equation systems, numerical integration, interpolation and curve fitting, and the solution of ordinary differential equations.
Module coordinator
Reto Knaack (knaa)
Learning objectives (competencies)
Objectives
Competences
Taxonomy levels
Students deepen their knowledge of Python and can apply Python to advanced problems in numerical mathematics in weekly group work.
F, M, SO
K3
Students can explain the principles of the most important solution methods for nonlinear systems and apply them to concrete problems.
F, M
K2, K3
Students can solve typical problems in the fields of interpolation and linear or non-linear regression numerically.
F, M
K2, K3
Students can integrate functions of a single variable and quantify the errors that occur.
Students know the most important numerical solution methods for ordinary differential equations. They can solve simple systems of such differential equations using Python.
F, M
K2, K3
Module contents
Numerical solution of nonlinear systems of equations
Functions with several variables
Newton method and damped Newton method
Regression analysis
Polynomial interpolation & spline interpolation
Linear and non-linear regression problems
Gauss-Newton method
Numerical integration
Quadrature formulas, their extrapolation and error calculation
Numerics of ordinary differential equations
Slope field and approximate solutions
Euler method and Runge-Kutta method
Systems of ordinary differential equations
Teaching materials
Script and presentations
Numerische Mathematik: Eine beispielorientierte Einführung, MichaelKnorrenschild, 5. Auflage, ISBN 978-34464323386
Supplementary literature
Numerik-Algorithmen, G. Engeln-Müllges, Klaus Niederdrenk, Reinhard Wodicka, 10. Auflage, ISBN 978-3642134722
Numerical Methods for Engineers and Scientists, A. Gilat, V. Subrmaniam, 3. Auflage, 978-1118554937
Prerequisites
Analysis 1 & 2
Diskrete Mathematik
Lineare Algebra
The contents of "Höhere Mathematik für Informatiker 1" are required
Teaching language
(X) German ( ) English
Part of International Profile
( ) Yes (X) No
Module structure
Type 3a
For more details please click on this link:
T_CL_Modulauspraegungen_SM2025
Exams
Description
Type
Form
Scope
Grade
Weighting
Graded assignments during teaching semester
weekly assignments and preparations
written
10-13 assignments, preparations
mark
20%
End-of-semester exam
exam
written
120 min
mark
80%
Remarks
Legal basis
The module description is part of the legal basis in addition to the general academic regulations. It is binding. During the first week of the semester a written and communicated supplement can specify the module description in more detail.
Note
Additional available versions:
1.0 start 01 February 2019
,
2.0 start 01 February 2020
Course: Höhere Mathematik für Informatiker 2 - Praktikum
No.
t.BA.ITM.HM2.19HS.P
Title
Höhere Mathematik für Informatiker 2 - Praktikum
Note
No module description is available in the system for the cut-off date of 01 August 2099.
Course: Höhere Mathematik für Informatiker 2 - Vorlesung
No.
t.BA.ITM.HM2.19HS.V
Title
Höhere Mathematik für Informatiker 2 - Vorlesung
Note
No module description is available in the system for the cut-off date of 01 August 2099.