Study Programmes 2016-2017
| MATH0500-1 | ||||||||||||||
| Introduction to numerical algorithmic | ||||||||||||||
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Duration :
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| 24h Th, 14h Pr, 6h Labo., 45h Proj. | ||||||||||||||
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Number of credits :
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Lecturer :
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| Quentin Louveaux | ||||||||||||||
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Language(s) of instruction :
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| French language | ||||||||||||||
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Organisation and examination :
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| Teaching in the first semester, review in January | ||||||||||||||
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Units courses prerequisite and corequisite :
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| Prerequisite or corequisite units are presented within each program | ||||||||||||||
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Learning unit contents :
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| 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 |
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Learning outcomes of the learning unit :
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| - 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 | ||||||||||||||
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Prerequisite knowledge and skills :
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| A basic course in linear algebra | ||||||||||||||
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Planned learning activities and teaching methods :
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| Tutorials are organized every week. An introduction to matlab is given. An implementation project is also given. | ||||||||||||||
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Mode of delivery (face-to-face ; distance-learning) :
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| face-to-face | ||||||||||||||
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Recommended or required readings :
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| Lecture notes will be availableon the course's website. | ||||||||||||||
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Assessment methods and criteria :
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| 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. |
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Work placement(s) :
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Organizational remarks :
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Contacts :
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