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.
|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...)
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|