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Tronc communStatistical modellingLSTAT2120 Linear modelsLSTAT2130 Introduction to Bayesian statisticsCours au choixAt least 2 courses among the 5 following.LSTAT2100 Discrete data analysis.LSTAT2170 Times seriesLSTAT2180 Resampling methods with applicationsLSTAT2210 Advenced linear models
FR
q1 15h+5h 4 creditsTeacher(s):
> Lieven Desmet (compensates Catecoine Legrand)
Lieven Desmet (compensates Catecoine Legrand)
Machine learning and Data miningLSTAT2110 Data AnalysisCours au choixChoose at least 2 courses among the 3 following.
LINFO2275 Data mining & decision makingStatistical computing, data structures and algorithms for data analysisLDATS2360 Seminar in data management: basicLINFO2172 DatabasesCours au choixLINMA2472 Algorithms in data scienceEN
q1 30h+22.5h 5 creditsTeacher(s):
> Jean-Charles Delvenne (coord.)
> Gautier Krings (compensates Vincent Blondel)
Jean-Charles Delvenne (coord.)
PhilosophieMaximum one course among:
LSC2220 Philosophy of scienceEN
q2 30h 2 creditsTeacher(s):
> Pieter Thyssen (compensates Alexandre Guay)
Pieter Thyssen (compensates Alexandre Guay)
LFILO2003E Ethics in the Sciences and technics (sem)FR
q2 15h+15h 2 creditsTeacher(s):
> Hervé Jeanmart
> Charles Pence
> René Rezsohazy
Hervé Jeanmart
Activités de baseThe student chooses, for a maximum of 10 credits, the courses in the list below for which it did not acquire equivalent skills in its previous formation. This choice is discussed with the advisor of the master and next approved by the restricted jury.
Mathématique - Analyse et algèbre linéaireEach of the following three modules of two courses allows acquiring similar skills:
Module 1LINFO1111 AnalysisFR
q1 45h+37.5h 7 creditsTeacher(s):
> François Glineur
Roland Keunings
François Glineur
LINFO1112 AlgebraFR
q2 30h+30h 5 creditsTeacher(s):
> Christophe Craeye
> Thomas Peters (compensates Enrico Vitale)
Christophe Craeye
Module 2LINGE1114 Mathematics I: analysisModule 3LMAT1101 Mathematics 1FR
q1 30h+20h 4 creditsTeacher(s):
> Pedro Dos Santos Santana Forte Vaz
Pedro Dos Santos Santana Forte Vaz
LMAT1102 Mathematics 2Probabilités et StatistiqueEach of the following four modules of two courses allows acquiring similar skills:
Module 1Module 2LBIR1212 Probabilities and statistics (I)LBIR1315 Probability and statistics IIModule 3LINGE1113 ProbabilityLINGE1214 Furteco StatisticsModule 4Programmation et informatiqueThe student must acquire the skills bound to these three courses:
LINFO1101 Introduction to programmingFR
q1 30h+30h 5 creditsTeacher(s):
> Kim Mens
> Siegfried Nijssen
> Charles Pecheur
Kim Mens
LEPL1402 Informatics 2FR
q1 30h+30h 5 creditsTeacher(s):
> Sébastien Jodogne
> Ramin Sadre
> Pierre Schaus
Sébastien Jodogne
LEPL1509 Project 4 (in informatics)FR
q2 30h+22.5h 5 creditsTeacher(s):
> Marc Lainez (compensates Yves Deville)
Marc Lainez (compensates Yves Deville)
Oteco pre-requisite activitiesThe teaching units below may be added to the student's program if they are admitted on a case-by-case basis. The choice of these units will be made in consultation with the study advisor.
FR
q1 22.5h+15h 4 creditsTeacher(s):
> Aurélie Bertrand (compensates Eugen Pircalabelu)
> Aurélie Bertrand (compensates Bernadette Govaerts)
Aurélie Bertrand (compensates Eugen Pircalabelu)
FR
q2 30h+15h 4 creditsTeacher(s):
> Nathalie Lefèvre
> Cédric Taverne
Nathalie Lefèvre
LINGE1222 Multivariate Statistical AnalysisFR
q2 30h+15h 4 creditsTeacher(s):
> Nathan Uyttendaele (compensates Johan Segers)
Nathan Uyttendaele (compensates Johan Segers)
LANGL1330 English intermediate level - 1st partEN
q1 or q2 20h 3 creditsTeacher(s):
> Stéphanie Brabant
> Jean-Luc Delghust
> Aurélie Deneumoustier
> Fanny Desterbecq
Charlotte Diaz
> Marie Duelz
Jérémie Dupal
Ilenia Gallo
> Adrien Kefer (compensates Laura Lievens)
> Sandrine Mulkers (coord.)
> Marc Piwnik (coord.)
> Nevin Serbest
> Françoise Stas
> Anne-Julie Toubeau
Stéphanie Brabant
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Professional Focus [30.0]Content:LDATS2840 Master thesis in data analytics
FR
q1 or q2 20 credits
LDATS2350 Data MiningOptionnal courseChoose 1 course among the 2 following.
LDATA2010 Information visualisationLINFO2364 Mining Patterns in Data -
Options
The student completes his program with elective courses reported in the list below. With the agreement of the restricted jury, the student can also complete his program by oteco courses that he would consider relevant and taught at the UCLouvain. The student may include a maximum of 5 language course credits in his or her program, provided that the level is appropriate and consistent with the student's and the program's profile.
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Data in actionContent:LDATS2310 Data science for insurance and financeLSTAT2200 Survey and SamplingLSTAT2320 Design of experiment.
FR
q2 22.5h+7.5h 5 creditsTeacher(s):
> Patrick Bogaert
> Bernadette Govaerts
Patrick Bogaert
LSTAT2340 Statistical Analyses of ¿omics DataFR
q2 15h 4 creditsTeacher(s):
> Céline Bugli
> Bernadette Govaerts
Céline Bugli
LSTAT2380 Statistical consultingLSTAT2390 Applied statistics workshopsEN
q1+q2 15h 3 creditsTeacher(s):
> Catherine Legrand
> Christian Ritter
Catecoine Legrand
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Data sciences en linguistique et Text Mining
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Algorithme, informatique, optimisation, recherche opérationnelleContent:Cours au choixMaximum one course among the two courses (As they are bachelor course, the amount of credits is reduced to 5)
LINFO1113 Numerical algorithmicLINFO1114 Discrete mathematicsLINFO1252 Informatic SystemsLINFO2266 Advanced Algorithms for OptimizationLINFO2145 Cloud Computing -
Stage1 internship maximum, chosen among the two following (optional):Content:LDATS2940 Stage en science des données
FR
q1 or q2 10 credits
FR
q1 or q2 5 credits
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Data Sciences appliquées à la gestionThe following courses are taught on two-month periods and the first three ones are taught on the Campus of UCL Mons. Thus, we ask to students to check that this choice is compatible with their schedule, before inscription.Content:MLSMM2152 New Technologies & Emerging PracticesMLSMM2153 Web MiningMLSMM2156 Recommender SystemsLLSMS2030 Supply Chain Management (in English)
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Optional coursesThese credits are not counted within the 120 required credits.Content:LSST1001 IngénieuxSud
FR
q1+q2 15h+45h 5 creditsTeacher(s):
> Stéphanie Merle
> Jean-Pierre Raskin (coord.)
Stéphanie Merle
LSST1002M Information and critical thinking - MOOCFR
q2 30h+15h 3 creditsTeacher(s):
> Myriam De Kesel
> Jean-François Rees
Myriam De Kesel
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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, they must add supplementary classes at the beginning of their Master’s programme in order to obtain the prerequisites for these studies.
To access to this Master's degree, the student has to master a minimum of preliminary skills in mathematics, programming, algorithmic and probability-statistics. If it is not the case, additional teachings must be added to his program. He can nevertheless include a maximum of 10 of these credits in the prerequisite module planned in the common-core syllabus of the Master's degree.
Students who do not have a B1 level in English (level obtained at UCLouvain) must take the LANGL1330 (https://uclouvain.be/en-cours-langl1330) English course. A dispensatory test is organized at the beginning of the academic year.
The student is invited to meet the program advisor to decide which courses should be followed. The restricted jury must next approve his program.
Mathématique - Analyse et algèbre linéaireEach of the following three modules allows acquiring similar skills:
Module 1LINFO1111 AnalysisFR
q1 45h+37.5h 7 creditsTeacher(s):
> François Glineur
Roland Keunings
François Glineur
LINFO1112 AlgebraFR
q2 30h+30h 5 creditsTeacher(s):
> Christophe Craeye
> Thomas Peters (compensates Enrico Vitale)
Christophe Craeye
Module 2LINGE1114 Mathematics I: analysisModule 3LMAT1101 Mathematics 1FR
q1 30h+20h 4 creditsTeacher(s):
> Pedro Dos Santos Santana Forte Vaz
Pedro Dos Santos Santana Forte Vaz
LMAT1102 Mathematics 2Probabilités et StatistiqueEach of the following four modules allows acquiring similar skills:
Module 1Module 2LBIR1212 Probabilities and statistics (I)LBIR1315 Probability and statistics IIModule 3LINGE1113 ProbabilityLINGE1214 Furteco StatisticsModule 4Programmation et informatiqueThe student must acquire the skills related to these three courses:
LINFO1101 Introduction to programmingFR
q1 30h+30h 5 creditsTeacher(s):
> Kim Mens
> Siegfried Nijssen
> Charles Pecheur
Kim Mens
LEPL1402 Informatics 2FR
q1 30h+30h 5 creditsTeacher(s):
> Sébastien Jodogne
> Ramin Sadre
> Pierre Schaus
Sébastien Jodogne
LEPL1509 Project 4 (in informatics)FR
q2 30h+22.5h 5 creditsTeacher(s):
> Marc Lainez (compensates Yves Deville)
Marc Lainez (compensates Yves Deville)
Oteco pre-requisite activitiesThe teaching units below may be added to the student's program if they are admitted on a case-by-case basis. The choice of these units will be made in consultation with the study advisor.
FR
q1 22.5h+15h 4 creditsTeacher(s):
> Aurélie Bertrand (compensates Eugen Pircalabelu)
> Aurélie Bertrand (compensates Bernadette Govaerts)
Aurélie Bertrand (compensates Eugen Pircalabelu)
FR
q2 30h+15h 4 creditsTeacher(s):
> Nathalie Lefèvre
> Cédric Taverne
Nathalie Lefèvre
LINGE1222 Multivariate Statistical AnalysisFR
q2 30h+15h 4 creditsTeacher(s):
> Nathan Uyttendaele (compensates Johan Segers)
Nathan Uyttendaele (compensates Johan Segers)
LANGL1330 English intermediate level - 1st partEN
q1 or q2 20h 3 creditsTeacher(s):
> Stéphanie Brabant
> Jean-Luc Delghust
> Aurélie Deneumoustier
> Fanny Desterbecq
Charlotte Diaz
> Marie Duelz
Jérémie Dupal
Ilenia Gallo
> Adrien Kefer (compensates Laura Lievens)
> Sandrine Mulkers (coord.)
> Marc Piwnik (coord.)
> Nevin Serbest
> Françoise Stas
> Anne-Julie Toubeau
Stéphanie Brabant
Oteco EU to be determined with the Study AdvisorDepending on his / her previous academic background, the student (in consultation with the study advisor) can add oteco UEs in order to acquire the necessary prerequisites for the program.