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Core courses for the Master's degree in computer science engineering [30.0]
LINFO2992 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 qu’au plus tôt l’année où il.elle présente son travail de fin d’études.
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
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Options
The student completes his program with options and/or elective courses. He/she selects 60 credits 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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Options en sciences informatiques
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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 implement methods and techniques that allow software to solve complex problems that when solved by humans require “intelligence”,
- Understand and put to good use methods and techniques relating to artificial intelligence such as automatic reasoning, research and heuristics, acquisition and representation of knowledge, automatic learning, problems associated with overcoming constraints,
- Identify applications and its methods and tools; understand a particular category of applications and its related techniques, for example robotics, computer vision, planning, data mining, computational linguistics and bioinformatics, big data processing,
- Formalise and structure a body of complex knowledge and use a systematic and rigorous approach to develop quality “intelligence” systems.
From 20 to 30credit(s)Content:
Required courses in Artificial Intelligence: big data, optimization and algortihms
Elective courses in Artificial Itelligence
The student select 10 credits among
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> John Lee
> John Lee (compensates Michel Verleysen)
> 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
Students completing the major “Software engineering and programming systems” will be able to:
- Understand and explain problems that come up during large scale software projects as well as the long-term critical impact that their choice of solutions may have (construction dimensions as well as validation, documentation, communication and management of a project involving large teams as well as costs and deadlines),
- Select and apply methods and tools of software engineering to develop complex software systems and meet strict quality standards: reliability, adaptability, scalability, performance, security, usefulness,
- Model the products and processes necessary to obtain such systems and analyse these models,
- Develop and implement analytical programmes focused on conversion and optimisation as well as computer representations,
- Put to good use different programming paradigms and languages, in particular those that deal with functional, object-oriented and competing programmes,
- Understand the issues associated with different and competing programming models and use the appropriate model,
- Define a new language (syntax and semantics) suitable to a specific context.
From 20 to 30credit(s)Content:
Required courses in software engineering and programming systems
Elective courses in Software Engineering and Programming Systems
The student can select 10 credits among
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Option in Data science and Applied Mathematics
Students completing the major “Data science and Applied Mathematics” must be able to:
- Understand engineering fields requiring synergy between applied mathematics and computer science such as algorithms, scientific calculations, modelling computer systems, optimisation, machine learning or data mining;
- Understand and put to good use algorithms and techniques used in data science;
- Identify and implement models and techniques relating to statistics, machine learning and data mining;
- Learn classes of applications such as the treatment of noisy data, pattern recognition or automatic extraction in large data collections.
This option is limited to students who have taken the INFO/MAP pairing or the SINF Bachelor's degree program with the equivalent of a minor in mathematics.
From 20 to 30credit(s)Content:
Required courses in Computing and Applied Mathematics
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
Pierre-Antoine Absil
Elective courses in computing and applied mathematics
The student can select 10 credits amongst
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> John Lee
> John Lee (compensates Michel Verleysen)
> Michel Verleysen
John Lee
EN
q2 30h+15h 5 credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Jérôme Louveaux (compensates Olivier Pereira)
> Benoît Macq
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+15h 5 credits
> French-friendly
Teacher(s):
> Thomas Peters (compensates Olivier Pereira)
Thomas Peters (compensates Olivier Pereira)
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Vincent Legat
> Jean-François Remacle
Vincent Legat
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Option en Cybersecurity
Students who have completed the "Cybersecurity and Information Technology" track should be able to:
• Understand areas of engineering that require synergy between computer security, networks, and systems, such as cryptography, data protection, application security, security architecture, or programming,
• Comprehend and appropriately apply methods and techniques related to cybersecurity, including prevention, detection, and response to cyber threats,
• Identify and implement security practices and standards to protect the infrastructure, systems, and data of organizations,
• Apply their knowledge to real-life scenarios through projects.
Students shall select 20 to 30 credits among:
Content:
Students shall select 20 to 30 credits among:
Required courses in Cybersecurity
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Thomas Peters (compensates Olivier Pereira)
> François-Xavier Standaert
Thomas Peters (compensates Olivier Pereira)
Elective courses in Cybersecurity
EN
q1 30h+15h 5 credits
> French-friendly
Teacher(s):
> Thomas Peters (compensates Olivier Pereira)
Thomas Peters (compensates Olivier Pereira)
EN
q2 30h+15h 5 credits
> French-friendly
Teacher(s):
> Jérôme Louveaux
> Jérôme Louveaux (compensates Olivier Pereira)
> Benoît Macq
Jérôme Louveaux
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Option Networks and systems
Students who have completed the “Networks and Systems" track should be able to:
- Understand and explain different devices and protocols used in computer and cellular networks;
- Design, configure and manage computer networks while taking into account application needs;
- Understand the operation of IoT and cellular networks;
- Explain the problems that affect cellular and IoT networks and develop solutions to cope with them;
- Understand how to optimise applications to efficiently use parallel cores;
- Understand, implement and use lock-free data structures;
- Understand the interactions between real-time operating systems and hardware;
- Design and implement applications running on embedded systems
Students shall select 20 to 30 credits among:
Content:
Required courses in Networks and systems
Elective courses in Networks and Systems
EN
q2 30h+30h 5 credits
> French-friendly
Teacher(s):
> François-Xavier Standaert
François-Xavier Standaert
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Option en Informatique médicale
Students completing the major in "Health informatics" will be able to:
- Identify and use methods and techniques that provide software-based solutions to complex problems encountered in hospitals, in bio-pharmaceutical environments, in life sciences, or in digital health.
- Take part in multidisciplinary projects bringing together medical, biological and engineering expertise to the benefit of patient health.
- Understand and put to good use the methods and techniques pertaining to medical informatics and bioinformatics, such as artificial intelligence, health interoperability, clinical knowledge structuring, applied statistics, information security, software quality, as well as the effective management and processing of large volumes of data.
- Understand specific categories of applications where these methods and techniques can be applied, such as diagnostic support, therapeutic assistance, hospital information systems, medical and biomedical imaging, smart devices, clinical trials, health data mining, as well as automated processing of the medical language.
- Formalize and structure a body of complex knowledge by using a systematic and rigorous approach to the development of high-quality medical and biomedical information systems.
Students shall select 20 to 30 credits among:
Content:
Cours obligatoires en Informatique médicale
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Greet Kerckhofs
> John Lee
> Benoît Macq
> Frank Peeters
Greet Kerckhofs
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Vincent Branders (compensates Pierre Dupont)
Vincent Branders (compensates Pierre Dupont)
FR
q2 22.5h+7.5h 5 credits
Teacher(s):
> Catherine Legrand
> Annie Robert
Catherine Legrand
Cours aux choix en Informatique médicale
EN
q1 30h+30h 5 credits
> French-friendly
Teacher(s):
> Thomas Peters (compensates Olivier Pereira)
> François-Xavier Standaert
Thomas Peters (compensates Olivier Pereira)
EN
q2 30h 3 credits
> French-friendly
Teacher(s):
> Maxime Lambrecht (compensates Axel Gosseries)
> Maxime Lambrecht (compensates Olivier Pereira)
Maxime Lambrecht (compensates Axel Gosseries)
EN
q2 30h+30h 5 credits
> French-friendly
Teacher(s):
> André Mouraux
> Dounia Mulders (compensates Michel Verleysen)
André Mouraux
EN
q2 30h 3 credits
> French-friendly
Teacher(s):
> Benoit Delhaye
> Philippe Lefèvre
Benoit Delhaye
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
q1 30h+15h 5 credits
> French-friendly
Teacher(s):
> Thomas Peters (compensates Olivier Pereira)
Thomas Peters (compensates Olivier Pereira)
FR
q1 20h+10h 4 credits
Teacher(s):
> Diego Castanares Zapatero
> Philippe Lysy
> Annie Robert (coord.)
> Françoise Smets
Diego Castanares Zapatero
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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:
EN
q2 30h+5h 4 credits
> French-friendly
Teacher(s):
> Anne-Catherine Provost
Anne-Catherine Provost
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):
> Maxime Lambrecht (compensates Axel Gosseries)
> Maxime Lambrecht (compensates Olivier Pereira)
Maxime Lambrecht (compensates Axel Gosseries)
Cours en marketing
FR
q2 30h 5 credits
Teacher(s):
> Nicolas Kervyn (compensates Karine Charry)
Nicolas Kervyn (compensates Karine Charry)
Cours en Sourcing and Procurement
EN
q1 30h 5 credits
Teacher(s):
> Per Joakim Agrell
> Antony Paulraj
Per Joakim Agrell
EN
q1 30h 5 credits
Teacher(s):
> Constantin Blome
> Canan Kocabasoglu Hillmer
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 entrepreneuriat (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 (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:
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.
FR
q2 30h+15h 5 credits
Teacher(s):
> Yves De Rongé
> Philippe Grégoire (compensates Yves De Rongé)
Yves De Rongé
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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·e·s 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:
NL
q1 or q2 30h 3 credits
Teacher(s):
> Isabelle Demeulenaere (coord.)
Isabelle Demeulenaere (coord.)
NL
q1 or q2 30h 3 credits
Teacher(s):
> Isabelle Demeulenaere (coord.)
> Dag Houdmont
Isabelle Demeulenaere (coord.)
Group dynamics
FR
q1 15h+30h 3 credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
Jean-Charles Delvenne (coord.)
FR
q2 15h+30h 3 credits
Teacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
Jean-Charles Delvenne (coord.)
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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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, students must take supplementary classes chosen by the faculty to satisfy course prerequisites.
Courses for students coming from bachelor in "informatique de gestion" or "informatique et systèmes".These students will have to take at least 150 credits to obtain the master in computer science.Cours alternatifs Probabilités et statistiques
L'étudiant·e choisit un cours parmi:
FR
q2 30h+30h 5 credits
Cours alternatifs Intelligence artificielle
L'étudiant·e choisit un cours parmi:
FR
q2 30h+30h 5 credits
Teacher(s):
> Eric Piette (compensates Yves Deville)
Eric Piette (compensates Yves Deville)
FR
q2 30h+30h 5 credits
Cours alternatifs Systèmes informatiques
L'étudiant·e choisit un cours parmi:
Cours alternatifs Réseaux informatiques
L'étudiant·e choisit un cours parmi:
FR
q2 30h+30h 5 credits
Cours alternatifs Algorithmique et structures de données
L'étudiant·e choisit un cours parmi:
FR
q1 30h+30h 5 credits
Cours alternatifs Concepts des langages de programmation
L'étudiant·e choisit un cours parmi:
FR
q2 30h+22.5h 5 credits
Teacher(s):
> Marc Lainez (compensates Yves Deville)
Marc Lainez (compensates Yves Deville)
Cours alternatifs Calculabilité, logique et complexité
L'étudiant·e choisit un cours parmi: