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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.
EN
q1+q2 25 credits
LEPL2020 Professional integration workEN
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 Databases
EN
q2 30h+30h 6 credits > French-friendlyTeacher(s):
> Thibault Helleputte (compensates Pierre Dupont)
Thibault Helleputte (compensates Pierre Dupont)
LINFO2255 Software engineering project -
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 LinguisticsEN
q1 30h+15h 5 credits > French-friendlyTeacher(s):
> Anaïs Tack (compensates Pierre Dupont)
Anaïs Tack (compensates Pierre Dupont)
LINFO2266 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
> 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 making -
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 paradigmsLINFO2382 Computer supported collaborative work -
Major in Security and Networking
Students completing the major “Security and Networking” will be able to:
- Understand and explain different devices and protocols used in computer networking;
- Design, configure and manage computer networks while taking into account application needs;
- Identify large scale distributed and parallel applications, the problems occurring with these applications and propose solutions;
- Carry out distributed applications by implementing the appropriate techniques;
- Understand the characteristics of distributed systems: parallelism, synchronisation, communication, error and threat models;
- Use appropriate techniques, algorithms and languages to design, model and analyse distributed applications;
- Understand and implement mechanisms (cryptography, protocols) to secure networks and distributed systems.
From 20 to 30credit(s)Content:Required courses in Networking and SecurityLINFO2145 Cloud ComputingLINFO2146 Mobile and Embedded ComputingLINFO2347 Computer system securityElective courses in Networking and SecurityThe student can select 10 credits amongst
LINFO2143 Concurrent systems : models and analysisLINFO2144 Secured systems engineeringLINFO2315 Design of Embedded and real-time systemsLINGI2348 Information theory and codingEN
q2 30h+15h 5 credits > French-friendlyTeacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Jérôme Louveaux
LINMA2470 Stochastic modellingEN
q2 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Philippe Chevalier
> Mehdi Madani (compensates Philippe Chevalier)
Philippe Chevalier
LMAT2450 CryptographyLINFO2355 Multicore programmingLELEC2770 Privacy Enhancing technologyEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Olivier Pereira
> François-Xavier Standaert
Olivier Pereira
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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 (compensates Anthony Papavasiliou)
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
> Michel Verleysen
John Lee
LINFO2266 Advanced Algorithms for OptimizationLINGI2348 Information theory and codingEN
q2 30h+15h 5 credits > French-friendlyTeacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
Jérôme Louveaux
LINFO2365 Constraint programmingLINMA2450 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 CryptographyLMECA2170 Numerical GeometryEN
q1 30h+30h 5 creditsTeacher(s):
> Vincent Legat
> Jean-François Remacle
Vincent Legat
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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 indicatorsLEPL2214 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):
> Axel Gosseries
> Olivier Pereira
Axel Gosseries
Cours en marketingMGEST1108 MarketingMLSMM2136 Trends in Digital MarketingMLSMM2134 e-Consumer BehaviorCours en Sourcing and ProcurementLLSMS2036 Supply Chain ProcurementEN
q1 30h 5 creditsTeacher(s):
> Constantin Blome
> Antony Paulraj (compensates Per Joakim Agrell)
Constantin Blome
LLSMS2038 Procurement Organisation and ScopeLLSMS2037 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 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 businessesLCPME2001 Théorie de l'entrepreneuriatLCPME2003 Plan d'affaires et étapes-clefs de la création d'entrepriseLes 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 coursesStudent who have not taken management courses during their previous studies must enroll in LCPME2021.
LCPME2021 Financer son projet -
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-GermanES
q1 30h 3 creditsTeacher(s):
> Rocio Cuberos Vicente
> Paula Lorente Fernandez (coord.)
Rocio Cuberos Vicente
ES
q1 30h 5 creditsTeacher(s):
> Rocio Cuberos Vicente
> Paula Lorente Fernandez (coord.)
Rocio Cuberos Vicente
NL
q1 or q2 30h 3 creditsTeacher(s):
> Marie-Laurence Lambrecht (coord.)
Marie-Laurence Lambrecht (coord.)
NL
q1 or q2 30h 3 creditsTeacher(s):
> Dag Houdmont
> Marie-Laurence Lambrecht (coord.)
Dag Houdmont
Group dynamicsLEPL2351 Group dynamics - Q1FR
q1 15h+30h 3 creditsTeacher(s):
> Delphine Ducarme
> Claude Oestges (coord.)
> Thomas Pardoen
> Benoît Raucent
Delphine Ducarme
LEPL2352 Group dynamics - Q2FR
q2 15h+30h 3 creditsTeacher(s):
> Delphine Ducarme
> Claude Oestges (coord.)
> Thomas Pardoen
> Benoît Raucent
Delphine Ducarme
Autres UEs hors-EPLL'étudiant·e peut choisir maximum 8 ects de cours hors EPL considérés 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 intelligenceLSINC1361 Artificial intelligenceCours 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 networksCours alternatifs Algorithmique et structures de donnéesL'étudiant·e choisit un cours parmi:
LINFO1121 Algorithms and data structuresLSINC1121 Algorithms and data structureCours 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