Master's in Data Science

The University of Milano-Bicocca offers a diverse range of undergraduate and postgraduate programs across various fields, including natural sciences, social sciences, economics, and humanities. By emphasizing a multidisciplinary approach and collaboration between different areas of study, the University of Milano-Bicocca prepares students to tackle complex real-world challenges and contribute meaningfully to their respective fields. At the heart of the university's mission is a dedication to promoting academic and scientific research. With state-of-the-art facilities and a supportive environment for scholars and researchers, the University of Milano-Bicocca continues to make significant contributions to a wide array of fields, including biotechnology, economics, environmental science, and sociology. The institution's strong international connections and partnerships enable students and faculty to engage with global perspectives and participate in cross-cultural exchanges, enriching their academic experience and nurturing a broader understanding of the world.

The Master’s Degree in Data Science is part of the Class of Master Degrees in Information Society; it lasts two years and is awarded with 120 ECTS. Twelve exams are enivisaged, corresponding to 90 ECTS. Seven exams are held in the first year, and five exams in the second year. Remaining credits will be acquired in terms of a stage and the final thesis. The master is freely accessible to graduate students, subject to having been previously earned 30 ETCS in Statistics, Computer Science, Mathematics, Physics. The language of the master degree is English. At the end of the period, a Master’s Degree in Data Science is earned. The goal of the degree is to provide graduate students, who are coming from different scientific backgrounds, with advanced competences and skills required for the value-driven analysis of large amount of data (so called big data) using cutting-edge statistical techniques and computational models. The degree is targeted to graduate students who have a background in different scientific domains, ranging from Natural Sciences to Social Sciences and Economics. It is designed to have a solid basis in Statistics and Computer science but also a strong multidisciplinary characterization in juridical, social and economic issues.