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Core courses for the Master in computer science and engineering [35.0]
LINFO2990 Graduation project/End of studies project
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.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
> French-friendly
Teacher(s):
> Myriam Banaï
> Francesco Contino (coord.)
> Delphine Ducarme
> Jean-Pierre Raskin
Myriam Banaï
Computer science seminars
The student shall select 3 credits from amongst
Students may choose 3 credits among
EN
q1 30h 3 credits
> French-friendly
Teacher(s):
> Etienne Riviere
> Ramin Sadre
Etienne Riviere
EN
q1 30h 3 credits
> French-friendly
Teacher(s):
> Sébastien Jodogne
> Siegfried Nijssen
Sébastien Jodogne
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Professional Focus [30.0]
Content:
Computer science courses
EN
q2 30h+30h 6 credits
> French-friendly
Teacher(s):
> Thibault Helleputte (compensates Pierre Dupont)
Thibault Helleputte (compensates Pierre Dupont)
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Options
The student must choose one or more options from the following sections. In the section "Options and elective courses in socio-economic knowledge", the student validates one of the two options or chooses at least 3 credits from among the elective courses or the courses of the option in business issues.
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Majors for the Master's degree in computer science and engineering
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Major in Artificial Intelligence: big data, optimization and algorithms
Students completing the major in artificial intelligence: big data, optimization and algorithms will be able to: Identify and use methods and techniques that create software-based solutions to complex problems, Understand and put to good use the methods and techniques pertaining to artificial intelligence such as automated reasoning, heuristic research, knowledge acquisition, automated learning, problems related to constraint satisfaction, Identify a category of applications and how to use its methods and tools; understand specific categories of applications and their specific techniques-for example computer vision, scheduling, data mining, natural language processing, bioinformatics, big data processing; Formalise and structure a body of complex knowledge by using a systematic and rigorous approach to develop quality “intelligent” systems.
Students shall select 20 to 30 credits among
Content:
Required courses in Artificial Intelligence: big data, optimization and algortihms
EN
q1 30h+15h 5 credits
> French-friendly
Teacher(s):
> Anaïs Tack (compensates Pierre Dupont)
Anaïs Tack (compensates Pierre Dupont)
Elective courses in Artificial Itelligence
Student shall select 10 credits among
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> John Lee
> Michel Verleysen
John Lee
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Christophe De Vleeschouwer (coord.)
> Laurent Jacques
Christophe De Vleeschouwer (coord.)
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Vincent Branders (compensates Pierre Dupont)
Vincent Branders (compensates Pierre Dupont)
FR
q1 30h+22.5h 5 credits
Teacher(s):
> Vincent Blondel
> Jean-Charles Delvenne
Vincent Blondel
EN
q1 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
Julien Hendrickx
EN
q1 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Gautier Krings (compensates Vincent Blondel)
Jean-Charles Delvenne (coord.)
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Major in software engineering and programming systems
Student completing the major in Software Engineering and Programming Systems will be able to: Understand and explain problems pertaining to large scale software projects as well as the critical impact of their solutions throughout the duration of the project (construction scope, validation, documentation, communication and large scale project management as well as expense limits and deadlines), Choose and apply engineering methods and tools related to complex software systems to meet strict quality control criteria: reliability, adaptability, upgradeability, performance, security, usability), Model products and processes necessary to obtain such systems and analyse the models in question, Design and create programmes to analyse, convert and optimise computer performance, Put to good use different programming language paradigms, in particular those that deal with competing functional and object oriented programmes, Understand the issues associated with different competing programming models and use the appropriate model, Define a new language (syntax and semantics) appropriate to a specific context.
Students shall select 20 to 30 credits among
Content:
Required courses in software engineering and programming systems
Elective courses in Software Engineering and Programming Systems
Students can select 10 credits among
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Major in Security and Networking
Students shall select 20 to 30 credits among
Content:
Required courses in Networking and Security
Elective courses in Networking and Security
Student can select 10 credits among
EN
q2 30h+15h 5 credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Jérôme Louveaux
EN
q2 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Philippe Chevalier
> Mehdi Madani (compensates Philippe Chevalier)
Philippe Chevalier
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Olivier Pereira
> François-Xavier Standaert
Olivier Pereira
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Major in Data science and Applied Mathematics
This major is available only to students who majored or minored in Applied Mathematics during their bachelor's degree programme. Students completing the major Computing and Applied Mathematics will be able to: Understand both applied mathematics and computing including algorithms, scientific calculations, computer system modelling, optimisation, automated learning or data mining, Understand and use the methods and techniques related to advanced algorithms such as optimisation methods, constraint programming, algorithms of graphs, numerical algorithms or analysis and design of algorithms, Identify and use models and techniques relating to statistics, automated learning and data mining; understand categories of applications used for the processing of raw data as well as automatic forms used to mine information out of large data sets.
The student shall select 20 to 30 credits among
Content:
Required courses in Computing and Applied Mathematics (20 credits)
EN
q1 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Gautier Krings (compensates Vincent Blondel)
Jean-Charles Delvenne (coord.)
EN
q2 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Pierre-Antoine Absil
> Karl Meerbergen (compensates Anthony Papavasiliou)
Pierre-Antoine Absil
Elective courses in computing and applied mathematics
Student shall select max. 10 credits among
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> John Lee
> Michel Verleysen
John Lee
EN
q2 30h+15h 5 credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Jérôme Louveaux
EN
q1 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
Julien Hendrickx
EN
q2 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> Philippe Chevalier
> Mehdi Madani (compensates Philippe Chevalier)
Philippe Chevalier
EN
q1 30h+22.5h 5 credits
> French-friendly
Teacher(s):
> François Glineur
> Geovani Nunes Grapiglia
François Glineur
EN
q1 30h+30h 5 credits
Teacher(s):
> Vincent Legat
> Jean-François Remacle
Vincent Legat
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Option en Cryptography and information security
This major is available only to students who majored or minored in Electricity during their Bachelor’s degree programme. Students completing the major Communication Networks will be able to: Understand and use different devices and protocols used in fixed and wireless networks, Design, configure and manage fixed and wireless networks while taking into account application needs (including multimedia), Understand and effectively use information coding techniques, Understand and design mobile wireless communication systems from start to finish.
Content:
Elective courses
In order to validate this option INFO and MAP students have to take 20 credits at least and ELEC and DATA students 15 credits at least among:
EN
q2 30h+30h 5 credits
> French-friendly
Teacher(s):
> François-Xavier Standaert
François-Xavier Standaert
EN
q2 30h+15h 5 credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Jérôme Louveaux
FR
q1 30h+15h 5 credits
> English-friendly
Teacher(s):
> Pierre-Emmanuel Caprace
> Olivier Pereira
Pierre-Emmanuel Caprace
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Olivier Pereira
> François-Xavier Standaert
Olivier Pereira
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Major in biomedical engineering
This major is available only to students who minored in biomedical engineering during their Bachelor’s degree programme. The objective of the biomedical engineering major is to train engineers who are capable of meeting future technological challenges in the scientific and technical fields related to biomedical engineering. This major provides students with basic knowledge about bioinformatics as well as other biomedical engineering fields such as bioinstrumentation, biomaterials, medical imaging, mathematical modelling, artificial organs and rehabilitation and biomechanics. The collaboration between the Louvain School of Management and the School of Medicine provides an interdisciplinary curriculum where engineering is applied to the complex and varied biomedical field.
Students shall select 20 to 30 credits among:
Content:
Required courses in biomedical engineering
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Vincent Branders (compensates Pierre Dupont)
Vincent Branders (compensates Pierre Dupont)
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> André Mouraux
> Michel Verleysen
André Mouraux
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Sophie Demoustier
> Christine Dupont
Sophie Demoustier
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Greet Kerckhofs
> John Lee
> Benoît Macq
> Frank Peeters
Greet Kerckhofs
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Cours au choix disciplinaires
Content:
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Options et cours au choix en connaissances socio-économiques
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Business risks and opportunities
Les étudiant·es doivent réussir au moins 15 crédits pour valider l’option. Cette option ne peut être prise simultanément avec l'option « Formation interdisciplinaire en création d'entreprise - CPME ».
Content:
FR
q1 30h+5h 4 credits
Teacher(s):
> Vincent Cassiers
> Werner Derycke
Vincent Cassiers
One course between
From 3 to 5credit(s)EN
q2 30h 3 credits
> French-friendly
Teacher(s):
> Axel Gosseries
> Olivier Pereira
Axel Gosseries
Cours en marketing
Cours en Sourcing and Procurement
EN
q1 30h 5 credits
Teacher(s):
> Constantin Blome
> Antony Paulraj (compensates Per Joakim Agrell)
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 small and medium sized business creation
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 création d’entreprise (CPME) 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 CPME 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 www.uclouvain.be/cpme.
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 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 LCPME2021.
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Cours au choix en connaissances socio-économiques
Content:
FR
q1+q2 30h 10 credits
Teacher(s):
> Dimitri Lederer
> Jean-Pierre Raskin
Dimitri Lederer
EN
q1 30h+15h 5 credits
> French-friendly
Teacher(s):
> Benoît Macq
> Jean-Pierre Raskin
> Benoît Raucent
Benoît Macq
EN
q2 30h 3 credits
> French-friendly
Teacher(s):
> Yves Deville
> Bernard Geubelle
Yves Deville
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Others elective courses
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Others elective courses
Content:
Les étudiant·es peuvent également inscrire à leur programme tout cours faisant partie des programmes d'autres masters de l'EPL moyennant l'approbation du jury restreint.
Languages
Students may select from any language course offered at the ILV. Special attention is placed on the following seminars in professional development:
ES
q1 30h 3 credits
Teacher(s):
> Rocio Cuberos Vicente
> Paula Lorente Fernandez (coord.)
Rocio Cuberos Vicente
ES
q1 30h 5 credits
Teacher(s):
> Rocio Cuberos Vicente
> Paula Lorente Fernandez (coord.)
Rocio Cuberos Vicente
NL
q1 or q2 30h 3 credits
Teacher(s):
> Marie-Laurence Lambrecht (coord.)
Marie-Laurence Lambrecht (coord.)
NL
q1 or q2 30h 3 credits
Teacher(s):
> Dag Houdmont
> Marie-Laurence Lambrecht (coord.)
Dag Houdmont
Group dynamics
FR
q1 15h+30h 3 credits
Teacher(s):
> Delphine Ducarme
> Claude Oestges (coord.)
> Thomas Pardoen
> Benoît Raucent
Delphine Ducarme
FR
q2 15h+30h 3 credits
Teacher(s):
> Delphine Ducarme
> Claude Oestges (coord.)
> Thomas Pardoen
> Benoît Raucent
Delphine Ducarme
Autres UEs hors-EPL
L'étudiant·e peut choisir maximum 8 ects de cours hors EPL considérés comme non-disciplinaires par la commission de diplôme
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