5 credits
30.0 h + 30.0 h
Q2
Teacher(s)
Craeye Christophe; Peters Thomas;
Language
French
Prerequisites
This course assumes that the student already masters the skills of end of secondary allowing to translate a problem into a system of equations with several variables and to solve it.
Main themes
The course focuses on :
- the understanding of mathematical tools and techniques based on a rigorous learning of concepts favored by highlighting their concrete application,
- the rigorous manipulation of these tools and techniques in the context of concrete applications.
- transposition,
- operation on matrices,
- rank and resolution of a linear system,
- inversion,
- determinant
- Matrix writing of a system of linear equations
- Basic operations on the lines
- Elimination of Gauss-Jordan
- LU Factoring
- Implementation of Linear Equation System Resolution Algorithms
- vectors, vector operations,
- vector spaces (vector, independence, base, dimension),
- linear applications (applications to transformations of the plan, kernel and image),
- eigenvectors and eigenvalues (including applications)
Aims
At the end of this learning unit, the student is able to : | |
| 1 |
Given the learning outcomes of the "Bachelor in Computer science" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
Students who have successfully completed this course will be able to:
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The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
Matrix calculation
- transposition,
- operation on matrices,
- rank and resolution of a linear system,
- inversion,
- determinant
- Matrix writing of a system of linear equations
- Basic operations on the lines
- Elimination of Gauss-Jordan
- Orthogonality and QR factoring
- Python language implementation of linear equation system solving algorithms
- vectors, vector operations,
- vector spaces (vector, independence, base, dimension),
- linear applications (applications to transformations of the plan, kernel and image),
- eigenvectors and eigenvalues (including applications)
Teaching methods
The computer implementation of the algorithms will be the subject of three mandatory homeworks.
Evaluation methods
Written exam and 3 homeworks
Faculty or entity
INFO
