
The Master's degree program in Data Science for Economics and Health (DSEH) is taught entirely in English and aims to equip students with advanced knowledge of methodologies and tools in computer science, statistics, and mathematics. This program focuses on interpreting and analyzing complex phenomena within economics and health sectors. Students will gain expertise in emerging information technologies for data management and analysis in cloud environments, advanced statistical and mathematical techniques, and machine learning for information extraction and classification. The curriculum also covers economic theory, decision theory under uncertainty, econometrics, time-series analysis, biostatistics, and epidemiology. The DSEH program offers students the flexibility to customize their studies through elective courses across three specialization paths: "Data Science," "Economic Data Analysis," and "Health." The "Data Science" path focuses on methodological and technological innovation, advanced statistics, social media analysis, and textual analysis for data-driven business. The "Economic Data Analysis" path provides tools for economic applications in policy assessment, investment analysis, production processes, and environmental issues. The "Health" path concentrates on analyzing medical data, understanding exposure-health relationships, and evaluating epidemiological literature. This program is designed to provide a solid methodological foundation, integrating lectures, laboratory classes, project work, and practical activities with real-world case studies. Graduates will be well-prepared for PhD programs and research in Data Science, Computer Science, Economics, and Epidemiology and Public Health.
The program consists of compulsory courses and elective courses allowing for specialization. Students can choose electives up to 18 ECTS from three distinct educational paths: "Data Science," "Economic Data Analysis," and "Health."
Graduates of the DSEH program are prepared for various professional roles requiring advanced data analysis skills in economics and health. The program aims to train professionals who can interpret complex data, develop predictive models, and contribute to decision-making in both private and public sectors.
Access is open with an examination of entry requirements. Proficiency in English at level B2 or higher is required.
The University of Milan typically does not charge separate tuition fees for international students from outside the EU; instead, fees are determined by income. However, specific details for international students and exact amounts for 2026/2027 are not available in the provided text. The provided figures (€200 min, ~€2,600 max for home/EU) refer to general fee structures. The general minimum fee for all students is €200. For non-EU students residing abroad, the fee is generally the maximum amount. The regional tax is an additional mandatory amount. An annual stamp duty of €16 is also required.
You need a Bachelor's degree with a minimum of 30 ECTS in specific fields like computer science, mathematics, economic sciences, statistics, or certain medical sciences. English proficiency at B2 level or higher is also required.
The Master's degree program in Data Science for Economics and Health is taught entirely in English.
The program is designed to be completed over two years and awards 120 ECTS credits.
Tuition fees vary based on income. Non-EU students residing abroad are generally subject to the maximum fee, which is €200, plus a mandatory regional tax and an annual stamp duty of €16. Exact amounts for 2026/2027 are not specified.
Graduates are prepared for roles such as Data Scientist, Data Analyst, Data Driven Economist, and Analyst in economic policy or health sectors.
You must check that you meet the academic and English language requirements, prepare your documentation including transcripts and proof of English proficiency, and submit your application by the deadline.