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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Annual unit | |||||||||||||||||||||||||||
1 | 2 | ||||||||||||||||||||||||||
Content: | |||||||||||||||||||||||||||
Required courses in Artificial Intelligence: big data, optimization and algortihms | |||||||||||||||||||||||||||
LINGI2266 | Advanced Algorithms for Optimization | Pierre Schaus | 30h+15h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINGI2263 | Computational Linguistics | Pierre Dupont | , Pierre Dupont (compensates Cédrick Fairon) ,30h+15h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINGI2365 | Constraint programming | Pierre Schaus | , Pierre Schaus (compensates Yves Deville)30h+15h | 5 credits | q2 | x | x | ||||||||||||||||||||
LINGI2364 | Mining Patterns in Data | Siegfried Nijssen | 30h+15h | 5 credits | q2 | x | x | ||||||||||||||||||||
Elective courses in Artificial Itelligence
Student shall select 10 credits among
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LELEC2870 | Machine learning : regression, deep networks and dimensionality reduction | John Lee | , Michel Verleysen30h+30h | 5 credits | q1 | x | x | ||||||||||||||||||||
LELEC2885 | Image processing and computer vision | Christophe De Vleeschouwer (coord.) | , Laurent Jacques30h+30h | 5 credits | q1 | x | x | ||||||||||||||||||||
LGBIO2010 | Bioinformatics | Pierre Dupont | 30h+30h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINGI2145 | Cloud Computing | Etienne Riviere | 30h+15h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINMA1691 | Discrete mathematics - Graph theory and algorithms | Vincent Blondel | , Jean-Charles Delvenne30h+22.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINMA1702 | Optimization models and methods I | François Glineur | 30h+22.5h | 5 credits | q2 | x | x | ||||||||||||||||||||
LINMA2450 | Combinatorial optimization | Jean-Charles Delvenne | , Julien Hendrickx30h+22.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LINMA2472 | Algorithms in data science | Jean-Charles Delvenne (coord.) | , Gautier Krings (compensates Vincent Blondel)30h+22.5h | 5 credits | q1 | x | x | ||||||||||||||||||||
LSINF2275 | Data mining & decision making | Marco Saerens | 30h+15h | 5 credits | q2 | x | x |