Study Programmes 2017-2018
WARNING : 2016-2017 version of the course specifications
MATH0500-1  
Introduction to numerical algorithmic
Duration :
24h Th, 14h Pr, 6h Labo., 45h Proj.
Number of credits :
Bachelor in computer science5
Master in data science (120 ECTS)5
Master of science in computer science and engineering (120 ECTS)5
Master in computer science (120 ECTS)5
Master in computer science (60 ECTS)5
Lecturer :
Quentin Louveaux
Language(s) of instruction :
French language
Organisation and examination :
Teaching in the first semester, review in January
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Learning unit contents :
Numerical analysis is at the boundary between Mathematics and Computer Science. It consists in studying how to practically obtain in a computer different mathematical concepts studied in other courses.
This course gives a brief introduction on good ways to implement a numerical method.
The following topics are considered: - number representations in a computer - Non-linear equations and systems - Linear algebra - Sparse linear algebra - Monte-Carlo methods                                                                           - interpolation and linear regression  
Learning outcomes of the learning unit :
- representation of numbers in a computer and implications on the roundoff errors in floating point computing - numerical methods for the resolution of nonlinear equations - basics of numerical linear algebra - basics of sparse linear algebra - basic concepts of the software matlab
Prerequisite knowledge and skills :
A basic course in linear algebra
Planned learning activities and teaching methods :
Tutorials are organized every week. An introduction to matlab is given. An implementation project is also given.
Mode of delivery (face-to-face ; distance-learning) :
face-to-face
Recommended or required readings :
Lecture notes will be availableon the course's website.
Assessment methods and criteria :
A written exam is organized.
The implementation project by groups of two also counts in the final grade.
The final grade is obtained as the geometric mean of the two scores.
Work placement(s) :
Organizational remarks :
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Contacts :