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Common core [46.0]
LDATE2990
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.
LEPL2020
Professional integration work
The modules of LEPL2020 course are organized over the two annual blocks of the master's degree. It is strongly recommended that students take them from year 1, but they will only be able to register for the course at the earliest the year in which they present their final graduation project.
Students who have other professional integration activities in their personal programme, or who can demonstrate an equivalent activity could be exempted from this course. This equivalence is at the discretion of the examination board. Another activity should then be chosen to reach the number of ECTS required for their graduation.
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
> Estelle Massart (coord.)
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers, Estelle Massart (coord.), 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):
> Jean-Charles Delvenne (coord.)
> Benoît Legat (compensates Vincent Blondel)
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
q1
30h+30h
5
credits
> French-friendly
Teacher(s):
> Olivier Pereira
> François-Xavier Standaert
EN
q2
30h+15h
5
credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
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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.
Dans la rubrique "Options et cours au choix en connaissances socioéconomiques", l'étudiant·e valide une des deux options ou choisit obligatoirement au minimum 3 crédits parmi les cours au choix ou les cours de l’option en enjeux de l’entreprise.-
Majors in data science
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Major in computer systems
Content:
Compulsory courses :
Elective courses
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Major in numerical methods and optimisation
The student who wishes to validate this option chooses 15 credits among:
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
q2
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> Philippe Chevalier
> Mehdi Madani (compensates Philippe Chevalier)
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
> Estelle Massart (coord.)
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers, Estelle Massart (coord.), Geovani Nunes Grapiglia
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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 (coord.)
> Laurent Jacques
EN
q1
30h+30h
5
credits
> French-friendly
Teacher(s):
> Vincent Branders (compensates Pierre Dupont)
EN
q2
30h+15h
5
credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Data structures and algorithms for data analysis
EN
q1
30h+30h
5
credits
> French-friendly
Teacher(s):
> Olivier Pereira
> 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:
One course between
From 3 to 5credit(s)
Cours en marketing
Cours en Sourcing and Procurement
EN
q1
30h
5
credits
Teacher(s):
> Constantin Blome
> Canan Kocabasoglu Hillmer (compensates Constantin Blome)
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 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 /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:
Required courses
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.
Prerequisite courses
Student who have not taken management courses during their previous studies must enroll in LINEO2021.
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Cours au choix en connaissances socio-économiques
Content:
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
> Estelle Massart (coord.)
> Geovani Nunes Grapiglia
Pierre-Antoine Absil, Gianluca Bianchin, Frédéric Crevecoeur, Jean-Charles Delvenne, François Glineur, Julien Hendrickx, Laurent Jacques, Raphaël Jungers, Estelle Massart (coord.), Geovani Nunes Grapiglia
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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:
DE
q1+q2
30h
3
credits
Teacher(s):
> Caroline Klein (coord.)
> Mélanie Mottin (compensates Caroline Klein)
DE
q1+q2
30h
5
credits
Teacher(s):
> Caroline Klein (coord.)
> Mélanie Mottin (compensates Caroline Klein)
Group dynamics
FR
q1
15h+30h
3
credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
FR
q2
15h+30h
3
credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
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.
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 :
EN
q1
30h+22.5h
5
credits
> French-friendly
Teacher(s):
> Jean-Charles Delvenne
> Jean-Charles Delvenne (compensates Vincent Blondel)
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.
