-
Common core [44.0]
LDATI2990
Master thesis
The graduation project can be written and presented in French or English, in consultation with the supervisor. It may be accessible to exchange students by prior agreement between the supervisors and/or the two universities.
One course to choose from
EN
q1+q2
30h
3
credits
> French-friendly
Teacher(s):
> Pierre-Antoine Absil
> Gianluca Bianchin
> Frédéric Crevecoeur
> Jean-Charles Delvenne
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers (coord.)
> Estelle Massart
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers (coord.), Estelle Massart, Geovani Nunes Grapiglia
-
List of focuses
-
Professional Focus : Data Analytics [30.0]
Content:
EN
q1
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> Vincent Blondel
> Jean-Charles Delvenne (coord.)
-
Professional Focus : Cybersecurity [30.0]
Content:
EN
q2
30h+15h
5
credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
-
-
Options
L'étudiant·e complète son programme pour arriver à min. 90 crédits disciplinaires (dispensés dans les Masters EPL ou sigle STAT, y compris le TFE) en ce non compris les éventuels compléments pris par certains étudiants qui manqueraient de base. Il n'est pas obligatoire de valider une option.
In the "Options and elective courses in socio-economic knowledge" section, the student validates one of the two options or must choose at least 6 credits from the courses in the option in business issues (maximum one class of innovation may be chosen, maximum one course among those offered by the CPs may be taken into account in these 6 credits).-
Majors in Data Science: Information technology
-
Major in computer systems
Students wishing to take this option must choose a minimum of 16 credits:
Content:
Compulsory courses :
Elective courses
EN
q1
30h
3
credits
> French-friendly
Teacher(s):
> Tom Barbette
> Etienne Riviere
> Ramin Sadre (coord.)
-
Major in numerical methods and optimisation
The student who wishes to validate this option chooses a minimum of 15 credits:
Content:
Compulsory courses
EN
q1
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> François Glineur
> Geovani Nunes Grapiglia
One course between
EN
q1
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
Elective courses
EN
q1+q2
30h
3
credits
> French-friendly
Teacher(s):
> Pierre-Antoine Absil
> Gianluca Bianchin
> Frédéric Crevecoeur
> Jean-Charles Delvenne
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers (coord.)
> Estelle Massart
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers (coord.), Estelle Massart, Geovani Nunes Grapiglia
-
Elective technical courses
Content:
Statistics
EN
q1
15h+5h
4
credits
Machine learning, vision and artificial intelligence
EN
q1
30h+30h
5
credits
> French-friendly
Teacher(s):
> Christophe De Vleeschouwer
> Laurent Jacques
Data structures and algorithms for data analysis
-
-
Options et cours au choix en connaissances socio-économiques
-
Business risks and opportunities
The student who wishes to validate this option must select at least 15 credits among the courses offered (maximum one course among those offered by the CPs can be taken into account in these 15 credits).
This option cannot be taken simultaneously with the “Interdisciplinary training in entrepreneurship - INEO” option.
Content:
Cours spécifiques aux enjeux de l'entreprise
LFSA2995
Company Internship
This course cannot be chosen by GCE Masters students as part of the business issues option, as part of their compulsory courses.
LEPL1805
People management
This course cannot be chosen if it has already been validated in the bachelor's degree.
LEPL2210
Ethics and ICT
This course cannot be chosen if the LLSMS2280 course has already been validated.
FR
q1
30h+0h
3
credits
LLSMS2280
Business Ethics and Compliance Management
Ce cours ne peut être choisi si le cours LEPL2210 a déjà été validé.
EN
q1
30h
5
credits
Innovation classe
Maximum one innovation class can be chosen.
Courses offered by the Program Commission
EN
q1+q2
30h
3
credits
> French-friendly
Teacher(s):
> Pierre-Antoine Absil
> Gianluca Bianchin
> Frédéric Crevecoeur
> Jean-Charles Delvenne
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers (coord.)
> Estelle Massart
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers (coord.), Estelle Massart, Geovani Nunes Grapiglia
-
Major in Interdisciplinary Program in Entrepreneurship - INEO
Commune à la plupart des masters de l'EPL, cette option a pour objectif de familiariser l'étudiant·e avec les spécificités de l'entreprenariat et de la création d’entreprise afin de développer chez lui les aptitudes, connaissances et outils nécessaires à la création d'entreprise.
Cette option rassemble des étudiants de différentes facultés en équipes interdisciplinaires afin de créer un projet entrepreneurial. La formation interdisciplinaire en entrepeneuriat (INEO) est une option qui s’étend sur 2 ans et s’intègre dans plus de 30 Masters de 9 facultés/écoles de l’UCLouvain. Le choix de l’option INEO implique la réalisation d’un mémoire interfacultaire (en équipe) portant sur un projet de création d’entreprise. L’accès à cette option, ainsi qu'à chacun des cours, est limité aux étudiant·es sélectionnés sur dossier. Toutes les informations sur https://uclouvain.be/fr/etudier/ineo.
L'étudiant.e qui choisit de valider cette option doit sélectionner au minimum 20 crédits et au maximum 25 crédits. Cette option n'est pas accessible en anglais et ne peut être prise simultanément avec l'option « Enjeux de l'entreprise ».
Content:
Cours obligatoires:
LINEO2003
Plan d'affaires et étapes-clefs de la création d'entreprise
Les séances du cours LINEO2003 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.
Cours préalable:
FR
q2
30h+15h
5
credits
-
-
Others elective courses
-
Others elective courses
Content:
The elective courses recommended and available for Master students in Data Science Engineering are listed here above and in the courses of EPL. 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 programme.
Languages
Students may select from any language course offered at the ILV. Special attention is placed on the following seminars in professional development:
Group dynamics
FR
q1
15h+30h
3
credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
FR
q2
15h+30h
3
credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
Autres UEs hors-EPL
L'étudiant·e peut choisir maximum 8 crédits de cours hors EPL, considérés comme non-disciplinaires par la commission de programme.
-
-
-
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, in the first annual block of their Masters programme, students must take supplementary classes chosen by the faculty to satisfy course prerequisites.
To enter the Master in Data Science, Information Technology orientation, the student must have a minimum of previous skills in mathematics, computer science, algorithms and probability-statistics. If this is not the case, he/she must add additional courses to his/her Master's program. The content of this additional training is determined by the program commission. The skills to be mastered correspond to those of the following courses:
Mathematics - Calculus and linear algebra
The student follows one of the following blocks:
Module 1
Module 2
Probability and statistics
The student follows one of the following blocks:
Module 1
Module 2
Programming and computer science
The student follows one of the following blocks:
Un cours parmi :
Computer systems:
The student follows one of the following blocks:
Numerical methods and optimisation:
The student follows one of the following blocks:
Un cours parmi :
Other 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 other UEs in order to acquire the necessary prerequisites for the program.
DATI2M - Louvain-la-Neuve