Artificial Intelligence [30.0]

Students who have completed the "Artificial Intelligence" option will have to be able to:
• Identify and implement a class of methods and techniques enabling a software system to solve complex problems which, when solved by a human being, would require some form of "intelligence".
• Understand and effectively implement methods and techniques of artificial intelligence such as automated reasoning, search and heuristics, knowledge acquisition and representation, automated learning, constraint satisfaction problems.
• Identify those classes of applications where these methods and tools can be applied; be aware of particular classes of application and their specific techniques – for example, robotics, computer vision, planning, data mining, natural language processing and bioinformatics data processing.
• Formalize and structure complex bodies of knowledge by using a systematic and rigorous approach to develop "intelligent" systems of high quality.

Legend
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...)
						Year
						1	2
The student shall select 30 credits from amongst
Compulsory courses in Artifficial intelligence
LINGI2262	Machine Learning :classification and evaluation	Pierre Dupont	30h + 30h	5credits	1q	x	x
LINGI2263	Computational Linguistics	Pierre Dupont (coord.), Cédrick Fairon	30h + 15h	5credits	2q	x	x
LINGI2264	Automated reasoning	Charles Pecheur	30h + 15h	5credits	1q	x	x
LINGI2365	Constraint programming	Yves Deville	30h + 15h	5credits	2q	x	x
Elective courses in Artificial Itelligence The student shall select 10 credits from amongst
LSINF2275	Data mining & decision making	Marco Saerens	30h + 30h	5credits	2q	x	x
LELEC2885	Image processing and computer vision	Christophe De Vleeschouwer (coord.), Laurent Jacques (supplée Benoît Macq), Benoît Macq	30h + 30h	5credits	1q	x	x
LINGI2368	Computational biology	Pierre Dupont	30h + 15h	5credits	1q	x	x
LGBIO2010	Bioinformatics	Yves Deville, Michel Ghislain	30h + 30h	5credits	2q	x	x
LINMA1702	Applied mathematics : Optimization I	Vincent Blondel, François Glineur (coord.)	30h + 22.5h	5credits	2q	x	x
LINMA1691	Discrete mathematics - Graph theory and algorithms	Vincent Blondel	30h + 22.5h	5credits	1q	x	x
LINMA2111	Discrete mathematics II : Algorithms and complexity	Vincent Blondel	30h + 22.5h	5credits	2q	x	x
LSTAT2110	Data Analysis	Christian Hafner, Cédric Heuchenne (supplée Christian Hafner), Johan Segers	22.5h + 7.5h	5credits	1q	x	x
LSTAT2320	Design of experiment.	Patrick Bogaert, Bernadette Govaerts	22.5h + 7.5h	5credits	2q	x	x
LSTAT2020	Statistical computing	Céline Bugli (supplée Bernadette Govaerts), Bernadette Govaerts	20h + 20h	6credits	1q	x	x
LELEC2870	Machine Learning : regression, dimensionality reduction and data visualization	Michel Verleysen	30h + 30h	5credits	1q	x	x
LINGE1222	Multivariate Statistical Analysis	Johan Segers	30h + 15h	4credits	2q	x	x
LINMA2450	Combinatorial optimization	Jean-Charles Delvenne	30h + 22.5h	5credits	1q	x	x