Data science and Applied Mathematics

Students completing the major “Data science and Applied Mathematics” must be able to:

  • Understand engineering fields requiring synergy between applied mathematics and computer science such as algorithms, scientific calculations, modelling computer systems, optimisation, machine learning or data mining;
  • Understand and put to good use algorithms and techniques used in data science;
  • Identify and implement models and techniques relating to statistics, machine learning and data mining;
  • Learn classes of applications such as the treatment of noisy data, pattern recognition or automatic extraction in large data collections.

 
> Légende
Mandatory Optional
Course not taught in 2020-2021 Periodic course not taught in 2020-2021
Periodic course taught in 2020-2021 Activity with prerequisites
Click on the course title to see detailed informations (objectives, teaching methods, evaluation...)
This option is limited to students who have taken the INFO/MAP major/minor pairing or the SINF Bachelor's degree program with the equivalent of a minor in mathematics. The student shall select
From 20 to 30 credits
Annual unit
  1 2

Mandatory Content:
Mandatory Required courses in Computing and Applied Mathematics
Mandatory LINMA2472 Algorithms in data science   Jean-Charles Delvenne (coord.)
, Gautier Krings (compensates Vincent Blondel)
30h+22.5h  5 credits q1 x x
Mandatory LINMA2710 Scientific computing   Pierre-Antoine Absil (coord.)
, Karl Meerbergen (compensates Anthony Papavasiliou)
,
30h+22.5h  5 credits q2 x x
Mandatory LINGI2364 Mining Patterns in Data   Siegfried Nijssen
30h+15h  5 credits q2 x x
Mandatory LSINF2275 Data mining & decision making   Marco Saerens
30h+15h  5 credits q2 x x
Optional Elective courses in computing and applied mathematics
The student can select 10 credits amongst
Optional LELEC2870 Machine learning : regression, deep networks and dimensionality reduction   John Lee
, Michel Verleysen
30h+30h  5 credits q1 x x
Optional LINGI2266 Advanced Algorithms for Optimization   Pierre Schaus
30h+15h  5 credits q1 x x
Optional LINGI2348 Information theory and coding   Jérôme Louveaux
, Benoît Macq
, Olivier Pereira
30h+15h  5 credits q2 x x
Optional LINGI2365 Constraint programming   Pierre Schaus
, Pierre Schaus (compensates Yves Deville)
30h+15h  5 credits q2 x x
Optional LINMA2450 Combinatorial optimization   Jean-Charles Delvenne
, Julien Hendrickx
30h+22.5h  5 credits q1 x x
Optional LINMA2470 Stochastic modelling   Philippe Chevalier
30h+22.5h  5 credits q2 x x
Optional LINMA2471 Optimization models and methods II   François Glineur
30h+22.5h  5 credits q1 x x
Optional LMAT2450 Cryptography   Olivier Pereira
30h+15h  5 credits q1 x x
Optional LMECA2170 Numerical Geometry   Vincent Legat
, Jean-François Remacle
30h+30h  5 credits q1 x x