Algebra

linfo1112  2020-2021  Louvain-la-Neuve

Algebra
Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
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.
Matrix calculation
  • transposition,
  • operation on  matrices,
  • rank and resolution of a linear system,
  • inversion,
  • determinant
Resolution of linear equation systems
  • 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
Linear algebra
  • 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:
  • S1.G1
  • S2.2
Students who have successfully completed this course will be able to:
  • Model concrete problems using matrices and vectors;
  • Solve concrete problems using matrix calculation techniques (in particular the resolution of linear systems);
  • Reason using correctly the mathematical notation and methods keeping in mind but exceeding a more intuitive understanding of the concepts.
 
Faculty or entity
INFO


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Data Science : Statistic

Bachelor in Computer Science