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Core courses for the Master's degree in computer science engineering [30.0]LINFO2992 Graduation project/End of studies projectThe 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.
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q1+q2 25 credits
LEPL2020 Professional integration workLes 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-friendlyTeacher(s):
> Myriam Banaï
> Francesco Contino (coord.)
> Delphine Ducarme
> Jean-Pierre Raskin
Myriam Banaï
Computer science seminarsThe student shall select 3 credits from amongst
Students may choose 3 credits among
LINFO2349 Networking and security seminarEN
q1 30h 3 credits > French-friendlyTeacher(s):
> Etienne Riviere
> Ramin Sadre
Etienne Riviere
EN
q1 30h 3 credits > French-friendlyTeacher(s):
> Sébastien Jodogne
> Siegfried Nijssen
Sébastien Jodogne
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Professional Focus [30.0]Content:Computer science coursesLINFO2132 Languages and translatorsLINFO2172 DatabasesLINFO2255 Software engineering project
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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 algortihmsLINFO2263 Computational LinguisticsLINFO2266 Advanced Algorithms for OptimizationLINFO2365 Constraint programmingLINFO2364 Mining Patterns in DataElective courses in Artificial ItelligenceThe student select 10 credits among
EN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> John Lee
> John Lee (compensates Michel Verleysen)
> Michel Verleysen
John Lee
LELEC2885 Image processing and computer visionEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Christophe De Vleeschouwer (coord.)
> Laurent Jacques
Christophe De Vleeschouwer (coord.)
LGBIO2010 BioinformaticsEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Vincent Branders (compensates Pierre Dupont)
Vincent Branders (compensates Pierre Dupont)
LINFO2145 Cloud ComputingFR
q1 30h+22.5h 5 creditsTeacher(s):
> Vincent Blondel
> Jean-Charles Delvenne
Vincent Blondel
LINMA1702 Optimization models and methods ILINMA2450 Combinatorial optimizationEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
Julien Hendrickx
LINMA2472 Algorithms in data scienceEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Jean-Charles Delvenne (coord.)
> Gautier Krings (compensates Vincent Blondel)
Jean-Charles Delvenne (coord.)
LINFO2275 Data mining & decision makingLINFO2381 Health Informatics -
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 systemsLINFO2143 Concurrent systems : models and analysisLINFO2251 Software Quality AssuranceLINFO2252 Software Maintenance and EvolutionElective courses in Software Engineering and Programming SystemsThe student can select 10 credits among
LINFO2145 Cloud ComputingLINFO2347 Computer system securityLINFO2355 Multicore programmingLINFO2364 Mining Patterns in DataLINFO2365 Constraint programmingLINFO2335 Programming paradigmsLINFO2381 Health InformaticsLINFO2382 Computer supported collaborative work -
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 MathematicsLINMA2472 Algorithms in data scienceEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Jean-Charles Delvenne (coord.)
> Gautier Krings (compensates Vincent Blondel)
Jean-Charles Delvenne (coord.)
LINMA2710 Scientific computingEN
q2 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Pierre-Antoine Absil
> Karl Meerbergen
Pierre-Antoine Absil
LINFO2275 Data mining & decision makingLINFO2364 Mining Patterns in DataElective courses in computing and applied mathematicsThe student can select 10 credits amongst
EN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> John Lee
> John Lee (compensates Michel Verleysen)
> Michel Verleysen
John Lee
LINFO2266 Advanced Algorithms for OptimizationLINGI2348 Information theory and codingEN
q2 30h+15h 5 credits > French-friendlyTeacher(s):
> Jérôme Louveaux
> Jérôme Louveaux (compensates Olivier Pereira)
> Benoît Macq
Jérôme Louveaux
LINFO2365 Constraint programmingLINFO2381 Health InformaticsLINMA2450 Combinatorial optimizationEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
Julien Hendrickx
LINMA2470 Stochastic modellingEN
q2 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Philippe Chevalier
> Mehdi Madani (compensates Philippe Chevalier)
Philippe Chevalier
LINMA2471 Optimization models and methods IIEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> François Glineur
> Geovani Nunes Grapiglia
François Glineur
LMAT2450 CryptographyEN
q1 30h+15h 5 credits > French-friendlyTeacher(s):
> Thomas Peters (compensates Olivier Pereira)
Thomas Peters (compensates Olivier Pereira)
LMECA2170 Numerical GeometryEN
q1 30h+30h 5 credits > French-friendlyTeacher(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 CybersecurityLINFO2347 Computer system securityLINFO2145 Cloud ComputingLINFO2144 Secured systems engineeringLELEC2770 Privacy Enhancing technologyEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Thomas Peters (compensates Olivier Pereira)
> François-Xavier Standaert
Thomas Peters (compensates Olivier Pereira)
Elective courses in CybersecurityLINFO2143 Concurrent systems : models and analysisLMAT2450 CryptographyEN
q1 30h+15h 5 credits > French-friendlyTeacher(s):
> Thomas Peters (compensates Olivier Pereira)
Thomas Peters (compensates Olivier Pereira)
LINFO2146 Mobile and Embedded ComputingLINGI2348 Information theory and codingEN
q2 30h+15h 5 credits > French-friendlyTeacher(s):
> Jérôme Louveaux
> Jérôme Louveaux (compensates Olivier Pereira)
> Benoît Macq
Jérôme Louveaux
LINFO2315 Design of Embedded and real-time systemsLINFO2381 Health Informatics -
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 systemsLINFO2146 Mobile and Embedded ComputingLINFO2315 Design of Embedded and real-time systemsLINFO2355 Multicore programmingElective courses in Networks and SystemsLINFO2347 Computer system securityLINFO2145 Cloud ComputingLINFO2144 Secured systems engineeringLINFO2143 Concurrent systems : models and analysisLINFO2381 Health InformaticsLELEC2760 Secure electronic circuits and systemsEN
q2 30h+30h 5 credits > French-friendlyTeacher(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 médicaleLGBIO2050 Medical ImagingEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Greet Kerckhofs
> John Lee
> Benoît Macq
> Frank Peeters
Greet Kerckhofs
LGBIO2010 BioinformaticsEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Vincent Branders (compensates Pierre Dupont)
Vincent Branders (compensates Pierre Dupont)
LINFO2381 Health InformaticsLSTAT2330 Statistics in clinical trials.FR
q2 22.5h+7.5h 5 creditsTeacher(s):
> Catherine Legrand
> Annie Robert
Catherine Legrand
Cours aux choix en Informatique médicaleLDATA2010 Information visualisationLELEC2770 Privacy Enhancing technologyEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Thomas Peters (compensates Olivier Pereira)
> François-Xavier Standaert
Thomas Peters (compensates Olivier Pereira)
LEPL2210 Ethics and ICTEN
q2 30h 3 credits > French-friendlyTeacher(s):
> Maxime Lambrecht (compensates Axel Gosseries)
> Maxime Lambrecht (compensates Olivier Pereira)
Maxime Lambrecht (compensates Axel Gosseries)
LGBIO2020 BioinstrumentationEN
q2 30h+30h 5 credits > French-friendlyTeacher(s):
> André Mouraux
> Dounia Mulders (compensates Michel Verleysen)
André Mouraux
LGBIO2060 Modelling of biological systemsLGBIO2072 Mathematical models in neuroscienceLGBIO2110 Introduction to Clinical EngineeringEN
q2 30h 3 credits > French-friendlyTeacher(s):
> Benoit Delhaye
> Philippe Lefèvre
Benoit Delhaye
LINFO2251 Software Quality AssuranceLINFO2263 Computational LinguisticsLINFO2347 Computer system securityLINFO2364 Mining Patterns in DataLINMA2472 Algorithms in data scienceEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Jean-Charles Delvenne (coord.)
> Gautier Krings (compensates Vincent Blondel)
Jean-Charles Delvenne (coord.)
LMAT2450 CryptographyEN
q1 30h+15h 5 credits > French-friendlyTeacher(s):
> Thomas Peters (compensates Olivier Pereira)
Thomas Peters (compensates Olivier Pereira)
WESP2123 Principles of clinical trialsFR
q1 20h+10h 4 creditsTeacher(s):
> Diego Castanares Zapatero
> Philippe Lysy
> Annie Robert (coord.)
> Françoise Smets
Diego Castanares Zapatero
WFARM2177 BiostatisticsWSBIM2122 Omics data analysis -
Cours au choix disciplinaires
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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:LEPL2211 Business issues introductionLEPL2212 Financial performance indicatorsEN
q2 30h+5h 4 credits > French-friendlyTeacher(s):
> Anne-Catherine Provost
Anne-Catherine Provost
LEPL2214 Law, Regulation and Legal ContextFR
q1 30h+5h 4 creditsTeacher(s):
> Vincent Cassiers
> Werner Derycke
Vincent Cassiers
One course between
From 3 to 5credit(s)LEPL2210 Ethics and ICTEN
q2 30h 3 credits > French-friendlyTeacher(s):
> Maxime Lambrecht (compensates Axel Gosseries)
> Maxime Lambrecht (compensates Olivier Pereira)
Maxime Lambrecht (compensates Axel Gosseries)
Cours en marketingMGEST1108 MarketingMLSMM2136 Trends in Digital MarketingMLSMM2134 e-Consumer BehaviorFR
q2 30h 5 creditsTeacher(s):
> Nicolas Kervyn (compensates Karine Charry)
Nicolas Kervyn (compensates Karine Charry)
Cours en Sourcing and ProcurementLLSMS2036 Supply Chain ProcurementEN
q1 30h 5 creditsTeacher(s):
> Per Joakim Agrell
> Antony Paulraj
Per Joakim Agrell
LLSMS2038 Procurement Organisation and ScopeEN
q1 30h 5 creditsTeacher(s):
> Constantin Blome
> Canan Kocabasoglu Hillmer
Constantin Blome
LLSMS2037 Sourcing StrategyAlternative to the major in business risks and opportunities for computer science studentsComputer 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 coursesLINEO2001 Théorie de l'entrepreneuriatLINEO2003 Plan d'affaires et étapes-clefs de la création d'entrepriseLes 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 coursesStudent who have not taken management courses during their previous studies must enroll in LINEO2021.
LINEO2021 Financer son projetFR
q2 30h+15h 5 creditsTeacher(s):
> Yves De Rongé
> Philippe Grégoire (compensates Yves De Rongé)
Yves De Rongé
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Cours au choix en connaissances socio-économiquesContent:LFSA2995 Company Internship
FR
q1+q2 30h 10 creditsTeacher(s):
> Dimitri Lederer
> Jean-Pierre Raskin
Dimitri Lederer
LFSA2212 Innovation classesEN
q1 30h+15h 5 credits > French-friendlyTeacher(s):
> Benoît Macq
> Jean-Pierre Raskin
> Benoît Raucent
Benoît Macq
LINFO2399 Industrial seminar in computer scienceEN
q2 30h 3 credits > French-friendlyTeacher(s):
> Yves Deville
> Bernard Geubelle
Yves Deville
LINFO2402 Open Source Project
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Others Elective courses
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Others elective coursesContent: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.
LanguagesStudents may select from any language course offered at the ILV. Special attention is placed on the following seminars in professional development:
LALLE2500 Professional development seminar GermanLALLE2501 Professional development seminar-GermanNL
q1 or q2 30h 3 creditsTeacher(s):
> Isabelle Demeulenaere (coord.)
Isabelle Demeulenaere (coord.)
NL
q1 or q2 30h 3 creditsTeacher(s):
> Isabelle Demeulenaere (coord.)
> Dag Houdmont
Isabelle Demeulenaere (coord.)
Group dynamicsLEPL2351 Become a tutorFR
q1 15h+30h 3 creditsTeacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
Jean-Charles Delvenne (coord.)
LEPL2352 Become a tutorFR
q2 15h+30h 3 creditsTeacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
Jean-Charles Delvenne (coord.)
Autres UEs hors-EPLL'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.LINFO1114 Discrete MathematicsCours alternatifs Probabilités et statistiquesL'étudiant·e choisit un cours parmi:
LBIR1212 Probabilities and statistics (I)LSINC1211 Probability and StatisticsFR
q2 30h+30h 5 credits
Cours alternatifs Intelligence artificielleL'étudiant·e choisit un cours parmi:
LINFO1361 Artificial intelligenceFR
q2 30h+30h 5 creditsTeacher(s):
> Eric Piette (compensates Yves Deville)
Eric Piette (compensates Yves Deville)
LSINC1361 Artificial intelligenceFR
q2 30h+30h 5 credits
Cours alternatifs Systèmes informatiquesL'étudiant·e choisit un cours parmi:
LINFO1252 Informatic SystemsLSINC1252 Informaticals SystemsCours alternatifs Réseaux informatiquesL'étudiant·e choisit un cours parmi:
LINFO1341 Computer networksLSINC1341 Computer networksFR
q2 30h+30h 5 credits
Cours alternatifs Algorithmique et structures de donnéesL'étudiant·e choisit un cours parmi:
LINFO1121 Algorithms and data structuresLSINC1121 Algorithms and data structureFR
q1 30h+30h 5 credits
Cours alternatifs Concepts des langages de programmationL'étudiant·e choisit un cours parmi:
LINFO1104 Programming language conceptsLSINC1104 Programming Paradigms and ConcurrencyLEPL1509 Project 4 (in informatics)FR
q2 30h+22.5h 5 creditsTeacher(s):
> Marc Lainez (compensates Yves Deville)
Marc Lainez (compensates Yves Deville)
Cours alternatifs Calculabilité, logique et complexitéL'étudiant·e choisit un cours parmi:
LINFO1123 Calculability, Logic and ComplexityLSINC1123 Calculability, Logic and Complexity