Overview

The M.Sc. in Data Science for Social Sciences at Toulouse 1 Capitole University 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.

Key facts

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.

Programme Structure

Courses include:

Mathematical Statistics

Statistical Software for data scientists (R, Python, SAS)

Intermediate econometrics

Applied econometrics

Introduction to Convex Optimization for Machine Learning

Professional Development

FLE

Key information

Duration

Full-time
- 24 months

Start dates & application deadlines

Starting 2027-09-01 00:00:00
- Apply before 2027-02-03 00:00:00 , International
- Apply before 2027-03-24 00:00:00 , National
- Apply before 2027-03-24 00:00:00 , EEA/EU

Language

English

TOEFL^® IBT

OR

79

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Credits

120 ECTS

Delivered

On Campus

Campus Location

Toulouse, France

Disciplines

Liberal Arts Data Science & Big Data View 58 other Masters in Data Science & Big Data in France

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Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

TOEFL^® IBT

OR

79

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Other requirements

General requirements

Students with an undergraduate degree who majored in Economics or Economics and Mathematics at the Toulouse School of Economics, and who are able to justify a good English level, are eligible to enroll in the M1 program "Data Science for Social Sciences", international track entirely taught in English.
Or by application review:
Students with an undergraduate 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).

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Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.

International Applies to you

Applies to you

Non-residents

3941 EUR / year

≈ 3941 EUR / year
Domestic Applies to you

Applies to you

Citizens or residents

254 EUR / year

≈ 254 EUR / year

Living costs

Toulouse

France

799 - 1154 EUR / month

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

Funding

Win a €10000 Scholarship! Deadline: 30 June 2020

Embark on your journey with the Studyportals Scholarship! We're giving away a total of 20,000 euros to help you achieve your dream of studying abroad.

Win a €10000 Scholarship! Deadline: 30 June 2020

Embark on your journey with the Studyportals Scholarship! We're giving away a total of 20,000 euros to help you achieve your dream of studying abroad.

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Scholarships Information

Below you will find Master's scholarship opportunities for Data Science for Social Sciences.

Available Scholarships

You are eligible to apply for these scholarships but a selection process will still be applied by the provider.

Data Science for Social Sciences

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