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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
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers (coord.)
> Estelle Massart
> Estelle Massart (compensates Jean-Charles Delvenne)
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers (coord.), Estelle Massart, Estelle Massart (compensates Jean-Charles Delvenne), Geovani Nunes Grapiglia
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List of focuses
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Professional Focus : Data Analytics [30.0]
Content:
EN
q1
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> Julien Calbert (compensates Jean-Charles Delvenne)
> Benoît Legat (coord.)
EN
q1
30h+30h
5
credits
> French-friendly
Teacher(s):
> John Lee
> John Lee (compensates Michel Verleysen)
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Professional Focus : Cybersecurity [30.0]
Content:
EN
q2
30h+15h
5
credits
> French-friendly
Teacher(s):
> Charles-Henry Bertrand Van Ouytsel (coord.)
> Gaëtan Cassiers
EN
q2
30h+15h
5
credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
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Options
A minimum of 90 credits must be obtained in each discipline (taught in the EPL or STAT Masters, including the TFE), not including additional credits taken by students who do not have the minimum foundation requirements.
Choosing an option is not compulsory.
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 innovation class 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
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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
> Cristel Pelsser
> Etienne Riviere
> Ramin Sadre (coord.)
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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
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers (coord.)
> Estelle Massart
> Estelle Massart (compensates Jean-Charles Delvenne)
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers (coord.), Estelle Massart, Estelle Massart (compensates Jean-Charles Delvenne), Geovani Nunes Grapiglia
EN
q1+q2
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> Pierre-Antoine Absil
> Pierre-Antoine Absil (compensates Laurent Jacques)
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Elective technical courses
Content:
Statistics
Machine learning, vision and artificial intelligence
EN
q1
30h+30h
5
credits
> French-friendly
Teacher(s):
> Christophe De Vleeschouwer
> Christophe De Vleeschouwer (compensates Laurent Jacques)
EN
q1
30h+30h
5
credits
> French-friendly
Teacher(s):
> Vincent Branders (compensates Pierre Dupont)
Data structures and algorithms for data analysis
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Options and elective courses in socio-economic knowledge
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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.
Innovation classe
Maximum one innovation class can be chosen.
Courses offered by the Program Commission
EN
q1+q2
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> Pierre-Antoine Absil
> Pierre-Antoine Absil (compensates Laurent Jacques)
EN
q1+q2
30h
3
credits
> French-friendly
Teacher(s):
> Pierre-Antoine Absil
> Gianluca Bianchin
> Frédéric Crevecoeur
> François Glineur
> Julien Hendrickx
> Laurent Jacques
> Raphaël Jungers (coord.)
> Estelle Massart
> Estelle Massart (compensates Jean-Charles Delvenne)
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers (coord.), Estelle Massart, Estelle Massart (compensates Jean-Charles Delvenne), Geovani Nunes Grapiglia
EN
q2
30h
5
credits
Teacher(s):
> Daniele Catanzaro
> Daniele Catanzaro (compensates Mathieu Van Vyve)
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Major in Interdisciplinary Program in Entrepreneurship - INEO
The aim of this option, which is common to most EPL masters' programmes, is to familiarise students with the specifics of entrepreneurship and business creation, equipping them with the skills, knowledge, and tools necessary for starting a business.
The interdisciplinary entrepreneurship training (INEO) is an option that spans two years and is integrated into over 30 Master's programmes across 9 faculties/schools at UCLouvain.
Choosing the INEO option requires completing an interfaculty dissertation (in teams) focused on a business creation project. Access to this option, as well as to each of its courses, is limited to students selected based on their application.
Full details are available at https://uclouvain.be/fr/etudier/ineo.
Students who choose this option must select a minimum of 20 credits and a maximum of 25 credits. This option is not available in English and cannot be taken simultaneously with the "Business Risks and Opportunity" option.
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:
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Others elective courses
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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
> Thomas Pardoen (compensates Jean-Charles Delvenne)
Jean-Charles Delvenne (coord.), Delphine Ducarme, Thomas Pardoen, Thomas Pardoen (compensates Jean-Charles Delvenne)
FR
q2
15h+30h
3
credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Thomas Pardoen (compensates Jean-Charles Delvenne)
Jean-Charles Delvenne (coord.), Delphine Ducarme, Thomas Pardoen, Thomas Pardoen (compensates Jean-Charles Delvenne)
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.
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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, 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
FRq1 30h+30h 5 credits
Teacher(s):
> Olivier Pereira
> Olivier Pereira (compensates Jean-Charles Delvenne)
FRq1 30h+30h 5 credits
Teacher(s):
> Donatien Hainaut
> Donatien Hainaut (compensates Laurent Jacques)
Programming and computer science
The student follows one of the following blocks:
Un cours parmi :
ENq1 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Vincent Blondel
> Gaëtan Cassiers (compensates Jean-Charles Delvenne)
> Thomas Peters (compensates Jean-Charles Delvenne)
Vincent Blondel, Gaëtan Cassiers (compensates Jean-Charles Delvenne), Thomas Peters (compensates Jean-Charles Delvenne)
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