The objective of this major is to provide students with the necessary body of knowledge to acquire and analyze biomedical data, i.e. either raw signal data or large bases of pre-processed data. This major is especially well-suited for students holding a bachelor in computer science, electricity or applied mathematic
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Students selecting this major may choose
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From 20 to 30 credits | |||||||||||||||||||||||||||
Annual unit | |||||||||||||||||||||||||||
1 | 2 | ||||||||||||||||||||||||||
Content: | |||||||||||||||||||||||||||
Required courses (10 credits) | |||||||||||||||||||||||||||
LELEC2531 | Design and Architecture of digital electronic systems | Jean-Didier Legat | 30h+30h | 5 credits | q1 | x | x | ||||||||||||||||||||
LELEC2900 | Signal processing | Laurent Jacques | , Benoît Macq , Luc Vandendorpe30h+30h | 5 credits | q2 | x | x | ||||||||||||||||||||
Elective courses | |||||||||||||||||||||||||||
LELEC2532 | Design and Architecture of analog electronic systems | David Bol | , Denis Flandre30h+30h | 5 credits | q2 | x | x | ||||||||||||||||||||
LELEC2811 | Instrumentation and sensors | David Bol (coord.) | , Laurent Francis30h+30h | 5 credits | q1 | x | x | ||||||||||||||||||||
LELEC2870 | Machine learning : regression, deep networks and dimensionality reduction | John Lee | , Michel Verleysen30h+30h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINGI2251 | Software Quality Assurance | Charles Pecheur | 30h+15h | 5 credits | q2 | x | x | ||||||||||||||||||||
LINGI2261 | Artificial intelligence | Yves Deville | 30h+30h | 6 credits | q2 | x | x | ||||||||||||||||||||
LINGI2262 | Machine Learning :classification and evaluation | Pierre Dupont | 30h+30h | 5 credits | q2 | x | x | ||||||||||||||||||||
LINMA2361 | Nonlinear dynamical systems | Pierre-Antoine Absil | 30h+22.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINMA2370 | Modelling and analysis of dynamical systems | Jean-Charles Delvenne (coord.) | , Denis Dochain30h+22.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINMA2471 | Optimization models and methods II | François Glineur | 30h+22.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINMA2875 | System Identification | Julien Hendrickx | 30h+30h | 5 credits | q2 | x | x | ||||||||||||||||||||
LSTAT2320 | Design of experiment. | Patrick Bogaert | , Bernadette Govaerts22.5h+7.5h | 5 credits | q2 | x | x | ||||||||||||||||||||
LSTAT2110 | Data Analysis | Johan Segers | 30h+7.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LBIRA2110B | Applied Econometrics | Xavier Draye | , Frédéric Gaspart , Bernadette Govaerts27.5h+7.5h | 3 credits | q1 | x | x | ||||||||||||||||||||
LSTAT2120 | Linear models | Christian Hafner | 30h+7.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LGBIO2072 | Mathematical models in neuroscience | Frédéric Crevecoeur | 30h+30h | 5 credits | q1 | x | x |
From 10 to 20 credits