
This Master’s Degree provides a strong and modern education in probabilistic and statistical methods. The program focuses on advanced techniques essential for mathematical modeling under uncertainty (Stochastics) and for analyzing complex, high-dimensional data (Data Science). It balances theoretical knowledge with computational skills and practical applications, aiming to equip students with the ability to discern, combine, and apply modern methods in Probability and Statistics. The curriculum is designed to enable graduates to model and analyze data from various fields by leveraging a deep mathematical understanding of underlying structures. Graduates will possess solid knowledge in Applied Mathematics, Probability, and Statistics, combined with essential computational skills for interdisciplinary applications. This preparation allows for the formulation of complex probabilistic models, development of analytical tools, estimation, forecasting, and uncertainty quantification, as well as the design of computational strategies. The program draws inspiration from leading Data Science graduate programs in the USA and Europe and is unique in Italy. It prepares students for professional roles in both private and public sectors, as well as for PhD studies in fields such as Statistics, Mathematics, Applied Mathematics, Operations Research, Computer Science, Economics, and Mathematical Finance.
Graduates will be highly sought after in various professional environments within the private and public sectors, equipped with skills for data analysis, modeling, and uncertainty quantification. The strong academic foundation also prepares students for advanced research and PhD studies.
A motivation letter is required. The program has 50 places available for non-European applicants residing abroad.
An application fee of €60 is required one-time. Tuition fees can vary based on the student's financial situation. Refer to the university portal for the most current fee information for the 2026-27 academic year, including potential fee reductions or exemptions.