Econométrie, statistiques. - Mention :Master - Parcours :Master (M2) mention Econométrie, statistiques parcours type Statistics and Econometrics par UT1 Capitole

Program 2019-2020The students must carry out a mandatory internship of at least 4 months from April onwards with an oral academic viva at the beginning of September. All classes are taught in English. SEMESTER 3 SEMESTER 4 Data Mining Survey sampling Time seriesStatistical Consulting**Statistical Software : SAS, R, Python and Excel *FLE (only for foreign students)English (only for french speaking students)Professional development Optional 2 among 4: Option 1: Lifetime data analysisPanel data analysis Option 2: Econometrics of qualitative variablesEconometrics of Marketing Option 3: Non
- parametric modelsOutlier detection and extreme value theory Option 4: Mathematics of deep learning algorithms part 1Mathematics of deep learning algorithms part 2 Non
- Mandatory: Professional Development ***Algebra Refresher ****Probability Refresher ****Dynamic Refresher ****Datanomics : regulation of data spreading and data protection Statistical ConsultingBig DataScoringEnglish (only for french speaking students)Internship or master thesis Optional 2 among 3: Option 1: Graph theoryGraph analytics Option 2: Spatial econometricsGeomarketing Option 3: Data basesWeb Mining * Common course with the 1st year master in Econometrics and Statistics** Groups of 4 students***Students who have already attended these courses in 2018-2019 are exempted**** Maths refresher coursesBonus point:To practice a sport or a musical activity within the University orchestra during the year can give you bous points. Only point above 10/20 are recorded More information: https://www.tse
- fr.eu/master
- 2-statistics
- and
- econometrics
- international
- track

The master 2 "Statistics and econometrics" is open to students who have previously acquired solid skills in economics and mathematical statistics. This MSc program offers general classes in statistics and econometrics including data mining, big data, survey sampling, scoring, spatial econometrics, web mining, ... The objective of the curriculum is first to give the students a solid culture in the big themes of applied statistics. This culture is necessarily developed while learning softwares like R, Python, SAS and Matlab. Furthermore, the students acquire skills in computing when it comes to database management. Some electives allow them to develop applications in various fields mainly in the tertiary sector.Job opportunities are in data science and business analytics in banking, marketing and industry. ApprenticeshipThis master is also available in apprenticeship. For more details, you can download the brochure (in French).
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