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Tronc commun
Data structures and algorithms for data analysis
EN
q1
30h+22.5h
5
credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Gautier Krings (compensates Vincent Blondel)
Jean-Charles Delvenne (coord.), Gautier Krings (compensates Vincent Blondel)
Machine learning
Statistics
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Professional Focus
Content:
L'étudiant·e sélectionne 30 crédits parmi:
EN
q1
30h
3
credits
Teacher(s):
> Sébastien Jodogne
> Siegfried Nijssen
Sébastien Jodogne, Siegfried Nijssen
EN
q1+q2
30h
3
credits
Teacher(s):
> Pierre-Antoine Absil
> Frédéric Crevecoeur (coord.)
> Jean-Charles Delvenne
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers
> Geovani Nunes Grapiglia
> Anthony Papavasiliou
Pierre-Antoine Absil, Frédéric Crevecoeur (coord.), Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers, Geovani Nunes Grapiglia, Anthony Papavasiliou
EN
q1+q2
15h
3
credits
Teacher(s):
> Catherine Legrand
> Christian Ritter
Catecoine Legrand, Christian Ritter
EN
q1+q2
25
credits
LEPL2020
Professional integration work
« Les modules du cours LEPL2020 sont organisés sur les deux blocs annuels du master. Il est fortement recommandé à l’étudiant.e de les suivre dès le bloc annuel 1, mais il.elle ne pourra inscrire le cours que dans son programme de bloc annuel 2.
EN
q1+q2
30h+15h
2
credits
Teacher(s):
> Myriam Banaï
> Francesco Contino (coord.)
> Delphine Ducarme
> Jean-Pierre Raskin
Myriam Banaï, Francesco Contino (coord.), Delphine Ducarme, Jean-Pierre Raskin
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Options
The student completes his program to reach at least 60 technical credits (in the Masters EPL or witha STAT acronym) not including the Master thesis and the eventual complements taken by some students who would lack basic knowledge. It is not compulsory to validate an option.
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Majors in Data Science: Information technology
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Major in computer systems
Content:
Compulsory courses :
Elective courses
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Major in numerical methods and optimization
Content:
Compulsory courses
EN
q1
30h+22.5h
5
credits
Teacher(s):
> François Glineur
> Geovani Nunes Grapiglia
François Glineur, Geovani Nunes Grapiglia
One course between
EN
q1
30h+22.5h
5
credits
Teacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
Julien Hendrickx, Geovani Nunes Grapiglia
Elective courses
EN
q2
30h+22.5h
5
credits
Teacher(s):
> Mehdi Madani (compensates Anthony Papavasiliou)
Mehdi Madani (compensates Anthony Papavasiliou)
EN
q2
30h+30h
5
credits
Teacher(s):
John Lataire
John Lataire
EN
q1+q2
30h
3
credits
Teacher(s):
> Pierre-Antoine Absil
> Frédéric Crevecoeur (coord.)
> Jean-Charles Delvenne
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers
> Geovani Nunes Grapiglia
> Anthony Papavasiliou
Pierre-Antoine Absil, Frédéric Crevecoeur (coord.), Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers, Geovani Nunes Grapiglia, Anthony Papavasiliou
EN
q1+q2
30h+22.5h
5
credits
Teacher(s):
> Pierre-Antoine Absil
> Laurent Jacques (compensates Anthony Papavasiliou)
Pierre-Antoine Absil, Laurent Jacques (compensates Anthony Papavasiliou)
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Major in Cryptography and information security
As with the Master’s degree engineering programmes in electricity, computer sciences and applied mathematics, this major provides students with the knowledge of fundamental algorithms and mathematics in order to better understand information security as well as the design and implementation of solutions for problems related to electronic circuits and information systems.
Content:
Elective courses
In order to validate this option INFO and MAP students have to take at least 20 credits and the ELEC, DATE and DATI students have to take at least 15 credits among:
EN
q2
30h+15h
5
credits
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Jérôme Louveaux, Benoît Macq, Olivier Pereira
FR
q1
30h+15h
5
credits
Teacher(s):
> Olivier Pereira
> Jean-Pierre Tignol
Olivier Pereira, Jean-Pierre Tignol
EN
q1
30h+30h
5
credits
Teacher(s):
> Olivier Pereira (coord.)
> François-Xavier Standaert
Olivier Pereira (coord.), François-Xavier Standaert
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Cours au choix disciplinaires
Content:
Statistics
EN
q1+q2
15h
3
credits
Teacher(s):
> Catherine Legrand
> Christian Ritter
Catecoine Legrand, Christian Ritter
Machine learning, vision and artificial intelligence
EN
q1
30h+30h
5
credits
Teacher(s):
> Christophe De Vleeschouwer (coord.)
> Laurent Jacques
Christophe De Vleeschouwer (coord.), Laurent Jacques
EN
q2
30h+15h
5
credits
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Jérôme Louveaux, Benoît Macq, Olivier Pereira
EN
q1
30h
3
credits
Teacher(s):
> Sébastien Jodogne
> Siegfried Nijssen
Sébastien Jodogne, Siegfried Nijssen
Data structures and algorithms for data analysis
EN
q1
30h+30h
5
credits
Teacher(s):
> Olivier Pereira (coord.)
> François-Xavier Standaert
Olivier Pereira (coord.), François-Xavier Standaert
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Options et cours au choix en connaissances socio-économiques
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Business risks and opportunities
Content:
FR
q1
30h+5h
4
credits
Teacher(s):
> Vincent Cassiers
> Werner Derycke (coord.)
> Bénédicte Inghels
Vincent Cassiers, Werner Derycke (coord.), Bénédicte Inghels
One course between
From 3 to 5credit(s)
Cours de fondements en marketing
Les cours MLSMM2136 Tendances en Digital Marketing Ou MLSMM2134 E-comportement du consommateur sont optionnels suite à la réussite du cours MGEST1220 lors du premier bloc annuel.
Alternative to the major in business risks and opportunities for computer science students
Computer science students who have already taken courses in this field while pursuing their Bachelor's degree may choose between 16-20 credits from the courses offered in the management minor for computer sciences.
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Major in small and medium sized business creation
Content:
Required courses for the major in small and medium sized businesses
LCPME2003
Plan d'affaires et étapes-clefs de la création d'entreprise
Les séances du cours LCPME2003 sont réparties sur les deux blocs annuels du master. L'étudiant doit les suivre dès le bloc annuel 1, mais ne pourra inscrire le cours que dans son programme de bloc annuel 2.
Prerequisite CPME courses
Student who have not taken management courses during their previous studies must enroll in LCPME2000.
FR
q1
30h+15h
5
credits
Teacher(s):
> Yves De Rongé
> Olivier Giacomin
Yves De Rongé, Olivier Giacomin
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Cours au choix en connaissances socio-économiques [3.0]
Content:
FR
q1+q2
30h
10
credits
Teacher(s):
> Dimitri Lederer
> Jean-Pierre Raskin
Dimitri Lederer, Jean-Pierre Raskin
EN
q1
30h+15h
5
credits
Teacher(s):
> Benoît Macq
> Jean-Pierre Raskin
> Benoît Raucent
Benoît Macq, Jean-Pierre Raskin, Benoît Raucent
EN
q1+q2
15h
3
credits
Teacher(s):
> Catherine Legrand
> Christian Ritter
Catecoine Legrand, Christian Ritter
EN
q1+q2
30h+22.5h
5
credits
Teacher(s):
> Pierre-Antoine Absil
> Laurent Jacques (compensates Anthony Papavasiliou)
Pierre-Antoine Absil, Laurent Jacques (compensates Anthony Papavasiliou)
EN
q1+q2
30h
5
credits
Teacher(s):
> Pierre-Antoine Absil
> Frédéric Crevecoeur (coord.)
> Jean-Charles Delvenne
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers
> Geovani Nunes Grapiglia
> Anthony Papavasiliou
Pierre-Antoine Absil, Frédéric Crevecoeur (coord.), Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers, Geovani Nunes Grapiglia, Anthony Papavasiliou
EN
q1+q2
0h
5
credits
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-
Otecos elective courses
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Otecos elective courses
Content:
The elective courses being recommended and available for Master students in Data Sciences Engineering are listed here above, in the majors and oteco lists of elective courses. However, a student can further suggest other courses that would be relevant for his.her personal curriculum, pending that this is compliant with the rules for setting up a personal Master program.
Languages
Students may select from any language course offered at the ILV. Special attention is placed on the following seminars in professional development:
NL
q1 or q2
30h
3
credits
Teacher(s):
> Isabelle Demeulenaere (coord.)
> Marie-Laurence Lambrecht
Isabelle Demeulenaere (coord.), Marie-Laurence Lambrecht
NL
q1 or q2
30h
3
credits
Teacher(s):
> Isabelle Demeulenaere (coord.)
> Dag Houdmont
Isabelle Demeulenaere (coord.), Dag Houdmont
Group dynamics
FR
q1
15h+30h
3
credits
Teacher(s):
> Claude Oestges (coord.)
> Benoît Raucent
> Vincent Wertz (compensates Thomas Pardoen)
Claude Oestges (coord.), Benoît Raucent, Vincent Wertz (compensates Thomas Pardoen)
FR
q2
15h+30h
3
credits
Teacher(s):
> Claude Oestges (coord.)
> Benoît Raucent
> Vincent Wertz (compensates Thomas Pardoen)
Claude Oestges (coord.), Benoît Raucent, Vincent Wertz (compensates Thomas Pardoen)
Autres UEs hors-EPL
L'étudiant·e peut choisir maximum 8 ects de cours hors EPL considérées comme non-disciplinaires par la commission de diplôme
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-
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Preparatory Module
(only for students who qualify for the course via complementary coursework)
To access this Master, students must have a good command of certain subjects. If this is not the case, they must add supplementary classes at the beginning of their Master’s programme in order to obtain the prerequisites for these studies.
Mathématique - Analyse et algèbre linéaire
L'étudiant choisit un des modules suivants :
Module 1
FR
q1
45h+37.5h
7
credits
Teacher(s):
> François Glineur
Roland Keunings
François Glineur, Roland Keunings
FR
q2
30h+30h
5
credits
Teacher(s):
> Christophe Craeye
> Thomas Peters (compensates Enrico Vitale)
Christophe Craeye, Thomas Peters (compensates Enrico Vitale)
Module 2
Probabilités et statistique
L'étudiant choisit un des modules suivants :
Module 1
Module 2
FR
q1
30h+30h
5
credits
Teacher(s):
> Jean-Charles Delvenne
> Olivier Pereira
Jean-Charles Delvenne, Olivier Pereira
FR
q1
30h+30h
5
credits
Teacher(s):
> Donatien Hainaut
> Laurent Jacques
Donatien Hainaut, Laurent Jacques
Programmation et informatique
FR
q1
30h+30h
5
credits
Teacher(s):
> Kim Mens
> Siegfried Nijssen
> Charles Pecheur
Kim Mens, Siegfried Nijssen, Charles Pecheur
FR
q1
30h+30h
5
credits
Teacher(s):
> Sébastien Jodogne
> Ramin Sadre
> Pierre Schaus
Sébastien Jodogne, Ramin Sadre, Pierre Schaus
Un cours parmi :
EN
q1
30h+22.5h
5
credits
Teacher(s):
> Jean-Charles Delvenne
> Jean-Charles Delvenne (compensates Vincent Blondel)
Jean-Charles Delvenne, Jean-Charles Delvenne (compensates Vincent Blondel)
Systèmes informatiques :
Méthodes numériques et optimisation :
Un cours parmi :
Oteco EU to be determined with the Study Advisor
Depending on his / her previous academic background, the student (in consultation with the study advisor) can add oteco UEs in order to acquire the necessary prerequisites for the program.
Study programme archive
DATI2M - Louvain-la-Neuve