Major in Artificial Intelligence: big data, optimization and algorithms

sinf2m  2018-2019  Louvain-la-Neuve

Students completing the major in Artificial Intelligence: big data, optimization and algorithms will be able to: Identify and implement methods and techniques that allow software to solve complex problems that when solved by humans require “intelligence”, Understand and put to good use methods and techniques relating to artificial intelligence such as automatic reasoning, research and heuristics, acquisition and representation of knowledge, automatic learning, problems associated with overcoming constraints, Identify applications and its methods and tools; understand a particular category of applications and its related techniques, for example robotics, computer vision, planning, data mining, computational linguistics and bioinformatics, big data processing, Formalise and structure a body of complex knowledge and use a systematic and rigorous approach to develop quality “intelligence” systems.


 
> Legend

The student shall select

De 20 à 30 credits parmi
Annual block
  1 2

Mandatory Required courses in Artificial Intelligence: big data, optimization and algortihms
Mandatory LINGI2262 Machine Learning :classification and evaluation   Pierre Dupont
30h+30h  5 credits 2q x x
Mandatory LINGI2263 Computational Linguistics   Pierre Dupont
, Cédrick Fairon
30h+15h  5 credits 1q x x
Mandatory LINGI2266 Advanced Algorithms for Optimization   Pierre Schaus
30h+15h  5 credits 1q x x
Mandatory LINGI2365 Constraint programming   Pierre Schaus
, Pierre Schaus (compensates Yves Deville)
30h+15h  5 credits 2q x x
 
Optionnal Elective courses in Artificial Itelligence

The student select 10 credits among  

Optionnal LELEC2870 Machine Learning : regression, dimensionality reduction and data visualization   John Lee (compensates Michel Verleysen)
, Michel Verleysen
30h+30h  5 credits 1q x x
Optionnal LELEC2885 Image processing and computer vision   Christophe De Vleeschouwer (coord.)
, Laurent Jacques
30h+30h  5 credits 1q x x
Optionnal LGBIO2010 Bioinformatics   Pierre Dupont
30h+30h  5 credits 2q x x
Optionnal LINGI2145 Cloud Computing   Etienne Riviere
30h+15h  5 credits 1q x x
Optionnal LINGI2364 Mining Patterns in Data   Siegfried Nijssen
30h+15h  5 credits 1q x x
Optionnal LINMA1691 Discrete mathematics - Graph theory and algorithms   Vincent Blondel
, Jean-Charles Delvenne
, Raphaël Jungers (compensates Jean-Charles Delvenne)
, Raphaël Jungers (compensates Vincent Blondel)
30h+22.5h  5 credits 1q x x
Optionnal LINMA1702 Optimization models and methods I   François Glineur
30h+22.5h  5 credits 2q x x
Optionnal LINMA2450 Combinatorial optimization   Daniele Catanzaro (compensates Jean-Charles Delvenne)
, Daniele Catanzaro (compensates Julien Hendrickx)
, Jean-Charles Delvenne (coord.)
, Julien Hendrickx
30h+22.5h  5 credits 1q x x
Optionnal LINMA2472 Algorithms in data science   Vincent Blondel
, Jean-Charles Delvenne (coord.)
, Gautier Krings (compensates Vincent Blondel)
, Leto Peel (compensates Jean-Charles Delvenne)
30h+22.5h  5 credits 1q x x
Optionnal LSINF2275 Data mining & decision making   Marco Saerens
30h+15h  5 credits 2q x x