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Core courses for the Master in computer science and engineering [35.0]LINFO2990 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
LELEC2531 Digital electronic systemsLEPL2020 Professional integration workThe modules of LEPL2020 course are organized over the two years 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 programme commission jury. Another activity should then be chosen to reach the number of ECTS required for their graduation.
Computer science seminarsThe student shall select 3 credits from amongst
Students may choose 3 credits among
LINFO2349 Networking and security seminar -
Professional Focus [30.0]Content:Computer science coursesLINFO2132 Languages and translatorsLINFO2172 DatabasesLINFO2255 Software engineering project
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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 algortihmsLINFO2263 Computational LinguisticsLINFO2266 Advanced Algorithms for OptimizationLINFO2365 Constraint programmingLINFO2364 Mining Patterns in DataElective courses in Artificial ItelligenceStudent shall select 10 credits among
EN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> John Lee
> John Lee (compensates Michel Verleysen)
LELEC2885 Image processing and computer visionEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Christophe De Vleeschouwer (coord.)
> Laurent Jacques
LGBIO2010 BioinformaticsEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Vincent Branders (compensates Pierre Dupont)
LINFO2145 Cloud ComputingFR
q1 30h+22.5h 5 creditsTeacher(s):
> Jean-Charles Delvenne
> Jean-Charles Delvenne (compensates Vincent Blondel)
LINMA1702 Optimization models and methods ILINMA2450 Combinatorial optimizationEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
LINMA2472 Algorithms in data scienceEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Jean-Charles Delvenne (coord.)
> Benoît Legat (compensates Vincent Blondel)
LINFO2275 Data mining & decision makingLINFO2381 Health Informatics -
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 systemsLINFO2143 Concurrent systems : models and analysisLINFO2251 Software Quality AssuranceLINFO2252 Software Maintenance and EvolutionElective courses in Software Engineering and Programming SystemsStudents 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 -
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 Data Science and Applied Mathematics (20 credits)LINMA2472 Algorithms in data scienceEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Jean-Charles Delvenne (coord.)
> Benoît Legat (compensates Vincent Blondel)
LINMA2710 Scientific computingLINFO2275 Data mining & decision makingLINFO2364 Mining Patterns in DataElective courses in Data Science and applied mathematicsStudent shall select max. 10 credits among
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q1 30h+30h 5 credits > French-friendlyTeacher(s):
> John Lee
> John Lee (compensates Michel Verleysen)
LINFO2266 Advanced Algorithms for OptimizationLELEC2348 Information theory and codingEN
q2 30h+15h 5 credits > French-friendlyTeacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
LINFO2365 Constraint programmingLINFO2381 Health InformaticsLINMA2450 Combinatorial optimizationEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Julien Hendrickx
> Geovani Nunes Grapiglia
LINMA2470 Stochastic modellingEN
q2 30h+22.5h 5 credits > French-friendlyTeacher(s):
> Philippe Chevalier
> Mehdi Madani (compensates Philippe Chevalier)
LINMA2471 Optimization models and methods IIEN
q1 30h+22.5h 5 credits > French-friendlyTeacher(s):
> François Glineur
> Geovani Nunes Grapiglia
LMAT2450 CryptographyLMECA2170 Numerical Geometry -
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 coursesIn 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:
LELEC2760 Secure electronic circuits and systemsLINFO2144 Secured systems engineeringLINFO2347 Computer system securityLELEC2348 Information theory and codingEN
q2 30h+15h 5 credits > French-friendlyTeacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
LMAT2440 Number theoryLMAT2450 CryptographyLELEC2770 Privacy Enhancing technology -
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 engineeringLGBIO2010 BioinformaticsEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Vincent Branders (compensates Pierre Dupont)
LGBIO2020 BioinstrumentationEN
q2 30h+30h 5 credits > French-friendlyTeacher(s):
> André Mouraux
> Dounia Mulders (compensates Michel Verleysen)
LGBIO2030 BiomaterialsLGBIO2040 BiomechanicsLGBIO2050 Medical ImagingLGBIO2060 Modelling of biological systemsEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Hari Teja Kalidindi (compensates Philippe Lefèvre)
> Laurent Opsomer (compensates Philippe Lefèvre)
LGBIO2072 Mathematical models in neuroscienceLINFO2381 Health Informatics -
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 technologyElective courses in CybersecurityLINFO2143 Concurrent systems : models and analysisLMAT2450 CryptographyLINFO2146 Mobile and Embedded ComputingLELEC2348 Information theory and codingEN
q2 30h+15h 5 credits > French-friendlyTeacher(s):
> Jérôme Louveaux
> Benoît Macq
> Olivier Pereira
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 systems -
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 ImagingLGBIO2010 BioinformaticsEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Vincent Branders (compensates Pierre Dupont)
LINFO2381 Health InformaticsLSTAT2330 Statistics in clinical trials.Cours aux choix en Informatique médicaleLDATA2010 Information visualisationLELEC2770 Privacy Enhancing technologyLEPL2210 Ethics and ICTLGBIO2020 BioinstrumentationEN
q2 30h+30h 5 credits > French-friendlyTeacher(s):
> André Mouraux
> Dounia Mulders (compensates Michel Verleysen)
LGBIO2060 Modelling of biological systemsEN
q1 30h+30h 5 credits > French-friendlyTeacher(s):
> Hari Teja Kalidindi (compensates Philippe Lefèvre)
> Laurent Opsomer (compensates Philippe Lefèvre)
LGBIO2072 Mathematical models in neuroscienceLGBIO2110 Introduction to Clinical EngineeringLINFO2251 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.)
> Benoît Legat (compensates Vincent Blondel)
LMAT2450 CryptographyWESP2123 Principles of clinical trialsFR
q1 20h+10h 4 creditsTeacher(s):
> Diego Castanares Zapatero
> Annie Robert (coord.)
> Xavier Stéphenne (compensates Françoise Smets)
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 indicatorsLEPL2214 Law, Regulation and Legal ContextOne course between
From 3 to 5credit(s)LEPL2210 Ethics and ICTCours en marketingMGEST1108 MarketingMLSMM2136 Trends in Digital MarketingMLSMM2134 e-Consumer BehaviorCours en Sourcing and ProcurementLLSMS2036 Supply Chain ProcurementLLSMS2038 Procurement Organisation and ScopeEN
q1 30h 5 creditsTeacher(s):
> Constantin Blome
> Canan Kocabasoglu Hillmer (compensates 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.
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 projet -
Cours au choix en connaissances socio-économiquesContent:LFSA2995 Company InternshipLINFO2399 Industrial seminar in computer scienceLINFO2402 Open Source Project
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Others elective courses
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Others elective coursesContent: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.
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 GermanDE
q1+q2 30h 3 creditsTeacher(s):
> Caroline Klein (coord.)
> Mélanie Mottin (compensates Caroline Klein)
LALLE2501 Professional development seminar-GermanDE
q1+q2 30h 5 creditsTeacher(s):
> Caroline Klein (coord.)
> Mélanie Mottin (compensates Caroline Klein)
Group dynamicsLEPL2351 Become a tutorFR
q1 15h+30h 3 creditsTeacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
LEPL2352 Become a tutorFR
q2 15h+30h 3 creditsTeacher(s):
> Jean-Charles Delvenne (coord.)
> Delphine Ducarme
> Thomas Pardoen
> Benoît Raucent
Autres UEs hors-EPLL'étudiant·e peut choisir maximum 8 crédits de cours hors EPL, considérés comme non-disciplinaires par la commission de programme.
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