Duration
24h Th, 14h Pr, 6h Labo., 45h Proj.
Number of credits
| Bachelor of Science (BSc) in Computer Science | 5 crédits | |||
| Master of Science (MSc) in Computer Science | 5 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
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
- interpoolation issues
- 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 implementation project in C 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 and counts for 2/3 of the final grade.
The implementation project by groups of two counts for 1/3 of the final grade.
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.
Work placement(s)
Organizational remarks
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Contacts
Adaptation of teaching commitments following the COVID-19 pandemic for the May-June 2020 session
Teaching methods implemented : distance-learning
Assessment subjects
Assessment methods
Contacts
Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session
Assessment subjects
Same as January
Assessment methods
The exam is an oral videoconference exam without preparation and open book.
The exam consists of a theoretical question drawn from the list available in the dox repository. Then an exercise is given to the student who has ten minutes to solve / start the exercise, take a photo of his notes and send it by email to the professor. If the exercise is not finished after 10 minutes, the student orally explains how to finish it. A list of exercise topics will also be made available on the dox repository.
The exam lasts twenty-five minutes in total (5-10 minutes for the theory, 10 minutes for preparation of the exercise and 5-10 minutes for a discussion of the exercise).
Contacts
q.louveaux@uliege.be
04/366 27 89