Major in Artificial Intelligence: big data, optimization and algorithms

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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Mandatory Optional
Course not taught in 2020-2021 Periodic course not taught in 2020-2021
Periodic course taught in 2020-2021 Activity with prerequisites
Click on the course title to see detailed informations (objectives, teaching methods, evaluation...)
Students shall select 20 to 30 credits among
Annual unit
  1 2

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