24h Th, 14h Pr, 6h Labo., 45h Proj.
Number of credits
|Bachelor in computer science||5 crédits|
|Master in data science (120 ECTS)||5 crédits|
|Master of science in computer science and engineering (120 ECTS)||5 crédits|
|Master in computer science (120 ECTS)||5 crédits|
|Master in computer science (60 ECTS)||5 crédits|
Language(s) of instruction
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 (or julia)
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 (or julia) is given. An implementation project is also given.
Mode of delivery (face-to-face ; distance-learning)
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.
If the project is not submitted in December, it has to be submitted in August (the same statement holds). The absence of any project submitted implies a "no show" grade.