Data Science for Social Sciences

Overview

The first year of the international track Data Science for Social Sciences from Toulouse School of Economics 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.

Career

This international track aims to train "data scientists", "data analysts", "project managers", "engineers” and/or “consultants" in statistics with backgrounds in economics and econometrics. The graduates benefit from direct professional integration not only in the tertiary sector (e.g. quantitative marketing, banking, insurance), but also in industry and academic research.