Students completing the major in artificial intelligence: big data, optimization and algorithms will be able to: Identify and use methods and techniques that create software-based solutions to complex problems, Understand and put to good use the methods and techniques pertaining to artificial intelligence such as automated reasoning, heuristic research, knowledge acquisition, automated learning, problems related to constraint satisfaction, Identify a category of applications and how to use its methods and tools; understand specific categories of applications and their specific techniques-for example computer vision, scheduling, data mining, natural language processing, bioinformatics, big data processing; Formalise and structure a body of complex knowledge by using a systematic and rigorous approach to develop quality “intelligent” systems.
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Students shall select 20 to 30 credits among |
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Required courses in Artificial Intelligence: big data, optimization and algortihms | ||||||||
LINGI2262 | Machine Learning :classification and evaluation | Pierre Dupont | 30h+30h | 5 credits | 2q | x | x | |
LINGI2263 | Computational Linguistics | Pierre Dupont , Cédrick Fairon | 30h+15h | 5 credits | 1q | x | x | |
LINGI2266 | Advanced Algorithms for Optimization | Pierre Schaus | 30h+15h | 5 credits | 1q | x | x | |
LINGI2365 | Constraint programming | Yves Deville , Pierre Schaus , Pierre Schaus (compensates Yves Deville) | 30h+15h | 5 credits | 2q | x | x | |
Elective courses in Artificial Itelligence
Student shall select 10 credits among |
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LELEC2870 | Machine Learning : regression, dimensionality reduction and data visualization | John Lee (compensates Michel Verleysen) , Michel Verleysen | 30h+30h | 5 credits | 1q | x | x | |
LELEC2885 | Image processing and computer vision | Christophe De Vleeschouwer (coord.) , Laurent Jacques | 30h+30h | 5 credits | 1q | x | x | |
LGBIO2010 | Bioinformatics | Pierre Dupont | 30h+30h | 5 credits | 1q | x | x | |
LINGI2145 | Cloud Computing | Etienne Riviere | 30h+15h | 5 credits | 1q | x | x | |
LINGI2364 | Mining Patterns in Data | Siegfried Nijssen | 30h+15h | 5 credits | 2q | x | x | |
LINMA1691 | Discrete mathematics - Graph theory and algorithms | Vincent Blondel , Jean-Charles Delvenne | 30h+22.5h | 5 credits | 1q | x | x | |
LINMA1702 | Optimization models and methods I | François Glineur | 30h+22.5h | 5 credits | 2q | x | x | |
LINMA2450 | Combinatorial optimization | Jean-Charles Delvenne (coord.) , Julien Hendrickx | 30h+22.5h | 5 credits | 1q | x | x | |
LINMA2472 | Algorithms in data science | Vincent Blondel , Jean-Charles Delvenne (coord.) , Gautier Krings (compensates Vincent Blondel) | 30h+22.5h | 5 credits | 1q | x | x | |
LSINF2275 | Data mining & decision making | Marco Saerens | 30h+15h | 5 credits | 2q | x | x |