Master in Stochastics and Data Science at University of Turin

About the programme

Stochastics and Data Science is a two-year master's degree in class LM-40-R, mathematics, worth 120 ECTS. It is taught in English and in person in Turin by the Giuseppe Peano Department of Mathematics. Access is open, but enrolment follows a check of your preparation.

The degree develops advanced skills in stochastic and inferential methods together with modern computational tools, so that graduates can analyse uncertainty and manage complex data at scale. It suits graduates in mathematics, statistics, physics, computer science or quantitative economics who want a rigorous route into data science.

What you will study

The first year is fully compulsory and builds the mathematical and computational core. In the second year a course on partial and stochastic differential equations is required, and you shape the rest through 18 ECTS of electives, 12 ECTS of free choice and the thesis, with options leaning to theoretical, statistical or computational work. Units in the 2026/27 study plan include:

• Probability Theory (9 ECTS)
• Statistical Inference (9 ECTS)
• Analysis (9 ECTS)
• Stochastic Processes (6 ECTS) and Statistics for Stochastic Processes (6 ECTS)
• Multivariate Statistical Analysis (6 ECTS)
• Databases and Algorithms (12 ECTS)
• Python or R for Data Science (3 ECTS)
• Electives such as Bayesian Statistics, Statistical Machine Learning, Deep Learning, Applied Stochastic Calculus and Complex Networks

How the programme is taught

The degree ends with a 24 ECTS thesis, a fifth of the programme, which can include work done during an internship; internships can be recognised in the study plan. A visiting professors scheme brings international experts to Turin, and courses from the UNITA European university alliance can count towards the degree. Short Italian courses are available for international students.

Career paths

According to the official course page, graduates either continue to a PhD or enter the job market as experts in data science and modelling. The professional profiles it lists are statistician and mathematician.

The mix of probability, inference and stochastic processes with databases, algorithms and machine learning is aimed at work where uncertainty and large data sets meet. Electives in econometrics, game theory and decisions under uncertainty add options for quantitative roles close to economics and finance.

Fees and scholarships

The degree is not on UniTo's list of additional contributions. For 2026/27, students residing abroad pay a fixed yearly amount linked to the GDP per capita of their country of residence, from €500 to €1,500 within the standard length of the degree, plus €156 in regional tax and stamp duty. Students from the particularly poor countries on the ministry's list pay the €156 only. EDISU Piemonte scholarship winners are refunded, which means zero euro tuition for eligible students.

How to apply from outside the EU

Revise analysis, probability and statistics before applying, since the preparation check covers them, in an individual interview or an online test with a 60% pass mark. Non-EU applicants residing abroad apply on Apply@UniTo, where €60 covers up to two programmes; for 2026/27 the master's call ran from 25 November 2025 to 29 January 2026. You upload your degree and transcript with proof of authenticity, a CV and a motivation letter.

After admission, you complete the Universitaly pre-enrolment (by 15 July 2026 for 2026/27) and apply for a study visa, which the consulate decides.

How ApplyAZ helps

If this programme fits your goals, ApplyAZ can include it in a shortlist of 20 to 30 English-taught programmes at Italian public universities. We write your CV and a tailored statement of purpose, submit your applications and Universitaly pre-enrolment, file your DSU scholarship application and prepare your visa file, with a named person on each stage. The university decides admission, the region decides the scholarship and the consulate decides the visa. See how ApplyAZ works or check your eligibility.