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Artificial Intelligence [30.0]

Students who have attended the "Artificial Intelligence" option will have to be able to:
• Identify and implement a class of methods and techniques enabling a software to solve complex problems which, if solved by a human being, requires "intelligence".
• Understand and effectively implement methods and techniques of artificial intelligence such as automated reasoning, research and heuristic, acquisition and representation of knowledge, automatic learning, problems of constraints satisfaction.
• Identify classes of applications where these methods and tools can be applied; apprehend particular classes of application and their specific techniques – for example, robotics, computer vision, planning, search of data, natural language processing and bioinformatics data
• Formalize and structure bodies of complex knowledge by using a systematic and rigorous approach to develop "intelligent" systems of quality.
Mandatory Optional
Courses not taught this academic year Periodic courses not taught this academic year
Periodic courses taught this academic year Two year courses

Click on the course code to see detailed informations (objectives, methods, evaluation...)
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The student shall select 30 credits from amongst

MandatoryCompulsory courses in Artifficial intelligence
Mandatory LINGI2262

Machine Learning :classification and evaluation  Pierre Dupont 30h + 30h  5credits  1q  x x
Mandatory LINGI2263

Computational Linguistics  Pierre Dupont, Pierre Dupont (coord.), Pierre Dupont (supplée Cédrick Fairon), Cédrick Fairon 30h + 15h  5credits  2q  x x
Mandatory LINGI2264

Automated reasoning  Charles Pecheur 30h + 15h  5credits  1q  x x
Mandatory LINGI2365

Constraint programming  Yves Deville 30h + 15h  5credits  2q  x x

MandatoryElective courses in Artificial Itelligence
The student shall select 10 credits from amongst
Optional LSINF2275

Data mining & decision making  Marco Saerens 30h + 30h  5credits  2q  x x
Optional LELEC2885

Image processing and computer vision  Christophe De Vleeschouwer (coord.), Laurent Jacques (supplée Benoît Macq), Benoît Macq 30h + 30h  5credits  1q  x x
Optional LINGI2368

Computational biology  Pierre Dupont 30h + 15h  5credits  1q  x x
Optional LGBIO2010

Bioinformatics  Yves Deville, Michel Ghislain 30h + 30h  5credits  2q  x x
Optional LINMA1702

Applied mathematics : Optimization  (in French) Vincent Blondel, François Glineur, François Glineur (coord.), François Glineur (supplée Vincent Blondel) 30h + 22.5h  5credits  2q  x x
Optional LINMA1691

Discrete mathematics - Graph theory and algorithms   (in French) Vincent Blondel, Jean-Charles Delvenne (supplée Vincent Blondel) 30h + 22.5h  5credits  1q  x x
Optional LINMA2111

Discrete mathematics II : Algorithms and complexity   Vincent Blondel 30h + 22.5h  5credits  2qCourses not taught this academic year  x x
Optional LSTAT2110

Data Analysis  Christian Hafner, Johan Segers 22.5h + 7.5h  5credits  1q  x x
Optional LSTAT2320

Design of experiment.  Patrick Bogaert, Bernadette Govaerts 22.5h + 7.5h  5credits  2q  x x
Optional LSTAT2020

Statistical computing  Céline Bugli (supplée Bernadette Govaerts), Bernadette Govaerts 20h + 20h  6credits  1q  x x
Optional LELEC2870

Machine Learning : regression, dimensionality reduction and data visualization  Michel Verleysen 30h + 30h  5credits  1q  x x
Optional LINGE1222

Multivariate Statistical Analysis  (in French) Cédric Heuchenne (supplée Johan Segers), Johan Segers 30h + 15h  4credits  2q  x x
Optional LINMA2450

Combinatorial optimization   Jean-Charles Delvenne 30h + 22.5h  5credits  1q  x x
| 15/07/2010 |