Study plan

*Elective courses may be selected from any of the courses offered by the Faculty of Mathematical, Physical and Natural Sciences (see the Faculty Guide).

For students interested in the theoretical aspects of the physics of matter, the Faculty recommends choosing from the following courses: PHYS-03/A Advanced solid state physics (6 ECTS), PHYS-03/A Laser technologies and quantum light (6 ECTS), PHYS-03/A Solid state physics (6 ECTS).

For students interested acquiring a computer science basis for managing large amounts of data, the Faculty recommends choosing from the following courses: IINF-05/A Artificial intelligence and machine learning applications, IINF-05/A Coding for artificial intelligence, IINF-05/A Data science, IINF-05/A Machine learning methods for time series forecasting.

*Elective courses may be selected from any of the courses offered by the Faculty of Mathematical, Physical and Natural Sciences (see the Faculty Guide).

For students interested in further exploring environmental issues, the Faculty recommends choosing one of the following courses: BIOS-05/A Ecologia, PHYS-05/B Fisica dell'atmosfera.

*Elective courses may be selected from any of the courses offered by the Faculty of Mathematical, Physical and Natural Sciences (see the Faculty Guide).

For students interested in exploring the aspects of innovation and management in depth, the Faculty recommends choosing from the following courses: ECON-04/A Sustainable finance (6 ECTS), ECON-04/A, Economics of innovation (6 ECTS) - NB: the course will be held at the Milan campus, IEGE-01/A e ECON-06/A Design thinking and start-up launch (8 ECTS) - NB: the course will be held at the Milan campus, ECON-08/A Organizing and leading change (6 ECTS) - NB: the course will be held at the Milan, ECON-09/A Project financing and open innovations (8 ECTS) - NB: the course will be held at the Milan campus, PHYS-03/A Technologies in action lab (4 ECTS) - NB: the course will be held at the Milan campus.

For students interested in deepening their knowledge of data analytics and finance, the Faculty recommends choosing from the following course: : ECON-04/A Data-driven decision making (6 ECTS), ECON-04/A Sustainable finance (6 ECTS), ECON-09/B Laboratory of data analytics for banking and insurance (6 ECTS), ECON-09/B Laboratory of data analytics for investment (6 ECTS), STAT-01/A Foundations of mathematics and statistics for artificial intelligence (6 ECTS), IINF-05/A Machine learning methods for time series forecasting (6 ECTS), INFO-01/A Cloud computing technologies (6 ECTS).