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Study programme 2015-2016

Teaching and training




The objective of this major is to provide students with a fundamental body of knowledge necessary to acquire and analyse biomedical data whether raw signal data or large bases of pre-processed data. This major is especially well-suited for students who have already studied computer science, electricity or applied mathematic

 
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Students selecting this major may choose
De 20 à 30 credits parmi
Annual block
  1 2
Mandatory Required courses (10 credits)
Mandatory LELEC2870 Machine Learning : regression, dimensionality reduction and data visualization   John Lee (compensates Michel Verleysen), Michel Verleysen 30h+30h  5 credits 1q x x
Mandatory LELEC2900 Signal processing   Benoît Macq, Luc Vandendorpe 30h+30h  5 credits 2q x x
 
Mandatory Elective courses

  De 10 à 20 credits parmi

Optionnal LELEC2811 Instrumentation and sensors   David Bol, Laurent Francis 30h+30h  5 credits 1q x x
Optionnal LINGE1222 Multivariate Statistical Analysis   Johan Segers 30h+15h  4 credits 2q x x
Optionnal LINGI2251 Software engineering: development methods   Charles Pecheur 30h+30h  5 credits 2q x x
Optionnal LINGI2261 Artificial intelligence: representation and reasoning   Yves Deville 30h+30h  6 credits 1q x x
Optionnal LINGI2262 Machine Learning :classification and evaluation   Pierre Dupont 30h+30h  5 credits 2q x x
Optionnal LINMA2361 Nonlinear dynamical systems   Pierre-Antoine Absil 30h+22.5h  5 credits 1q x x
Optionnal LINMA2370 Modelling and analysis of dynamical systems   Jean-Charles Delvenne, Denis Dochain (coord.) 30h+22.5h  5 credits 1q x x
Optionnal LINMA2471 Optimization models and methods   François Glineur 30h+22.5h  5 credits 1q x x
Optionnal LINMA2875 System Identification   Julien Hendrickx 30h+30h  5 credits 2q x x
Optionnal LSTAT2320 Design of experiment.   Patrick Bogaert, Bernadette Govaerts 22.5h+7.5h  5 credits 2q x x