- Academic programs
Master in Data Science for Social Sciences (2nd Year)
General information
- Prerequisites for enrolment
- Bac + 4
- Length of studies
- 1 year
- City
- International
- Internships
- Yes
- Cost and financial aid
- For Enrollment and Fees, please see the Admission section. Scholarships: Some Master scholarships will be awarded to Master students according to academic and individual criteria, see Admission section
- Diplôme national
- Accessible as
-
- Initial Training
- Alternate training (program where the time is shared between courses and professional experience)
- Teaching languages
- English
- What next?
The master's program « Econometrics, Statistics » aims to give the students intending to pursue advanced professional careers or doctoral research a solid culture in economics and statistics, as well as in various related fields of applied mathematics.
- The first year of the international track « Data Science for Social Sciences » offers compulsory general courses in theoretical economics, econometrics, mathematical statistics and statistical software for data scientists, as well as optional specialization courses in mathematics and their applications such as, for instance, finance, data bases, optimization, Markov chains, martingales theory, probability modeling, and big data.
- The second year of this master emphasizes advanced and applied techniques in data science, statistics and econometrics. It offers deeper courses in data science, particularly in mathematics of machine and deep learning algorithms, data mining, big data, regulation of data spreading and data protection, as well as specialized courses in different fields of application of statistics to social sciences, such as spatial statistics and econometrics, graph theory and graph analytics, geomarketing, scoring, and web mining. Moreover, this second year of the program offers higher level courses of statistical software, namely R, Python and SAS, and of massive databases management. The different courses allow students to acquire versatile skills in the processing of complex data (panel, survey, survival, graph, spatial) with modern parametric, non-parametric, and learning statistical methods.
Goals
For more information, please refer to the TSE website.
Publics
Prerequisites for enrolment : Bac + 4
Required former training
Second year - Acceptance criteria and enrollment
Students majored in the M1 program "Data Science for Social Sciences" are eligible to enroll in the M2 program.
Or by application review:
- Holders of a master's degree in an economics or mathematics field;
- French or foreign students with a degree and credits considered equivalent, and who are able to justify a good English level as well as a good Mathematics Level (GRE required for foreign students).
Application:
To apply to this master, select on eCandidatures platform:
- First year: M1 Econometrics, Statistics - Data science for social sciences International track
- Second year: M2 Econometrics, Statistics - Data science for social sciences International track
For more details about requirement documents and application process, please see the Admission section.
Alternate training (program where the time is shared between courses and professional experience)
Apprenticeship
For prospective students interested in more on-the-job experience, the program can be adapted to allow following an apprenticeship (alternance) alongside the master's degree. From September to March, apprentices spend 3 days at the university (M-T-W) and 2 days in the company (Th-F). From April to August, they mainly work in the company.
Admission conditions
To apply to this master, select on eCandidatures platform:
- First year: M1 Econometrics, Statistics - Data science for social sciences International track
- Second year: M2 Econometrics, Statistics - Data science for social sciences International track
For more details about requirement documents and application process, please see the Admission section.
Cost and financial aid :
For Enrollment and Fees, please see the Admission section. Scholarships: Some Master scholarships will be awarded to Master students according to academic and individual criteria, see Admission section
- Data Mining
- Mathematics of Machine and Deep Learning Algorithms: Part 1
- Mathematics of Machine and Deep Learning Algorithms: Part 2
- Statistical Consulting
- Statistical Software : SAS, R, Python and Excel
- Datanomics
Optional 2 among 3:
Option 1:
Option 2:
Option 3:
Non-Mandatory:
- Professional Development
- Algebra Refresher
- Probability Refresher
- Dynamic Optimization Refresher
- Datanomics : regulating to data spreading and data protection
- Statistical Consulting
- Big Data
- Scoring
- English or French as a Foreign Student
- Internship or master thesis
Optional 2 among 3:
Option 1:
Option 2:
Option 3:
- Data Mining
- Mathematics of Machine and Deep Learning Algorithms: Part 1
- Mathematics of Machine and Deep Learning Algorithms: Part 2
- Non-parametric models
- Survey Sampling
- Statistical Software : SAS, R, Python and Excel
- Professional Development (if not done in M1)
One elective out ot:
- Econometrics of Marketing & Lifetime Data Analysis
- Econométrie des variables qualitatives and Données de Panel (in French)
Optional 2 among 3:
Option 1:
Option 2:
- Year of highschool graduation
- Bac + 5
Career Opportunities
Download the skills' brochure to find out more about skills acquired by the end of the master.
Also, visit our career section where you can read and see experiences from Alumni.
