The Master's Degree course in Data Science offers the student the multidisciplinary knowledge and skills necessary for the effective declination of mathematical / IT skills in the analysis of data sets that are not necessarily heterogeneous and/or structured, achieving skills related to disciplines such as computer science, engineering, mathematics, statistics, management, law, humanities, and physics.
Graduates will be able to develop methods and tools to manage and analyze Big Data, develop forecasting and decision-making models, and use the knowledge extracted to support strategic decision-making processes in various application areas.
Quality Assurance
The quality of a degree program is the extent to which it achieves its educational objectives and meets the quality requirements of the educational activities offered, which are determined in line with the needs and expectations of students and representatives of the world of work.
This program has adopted a teaching Quality Assurance system in line with the University’s quality assurance guidelines and based on the e ANVUR national quality assurance guidelines, by carrying out the following activities:
- periodic consultations with representatives of the world of work to assess the adequacy of the cultural and professional profiles offered in their courses;
- design of educational contents and planning of resources;
- organization of educational activities and teaching services;
- monitoring the effectiveness of teaching and planning measures to improve teaching and services;
- provision of complete and up-to-date information on its website, relating to the program (professional roles, expected learning outcomes, learning activities).
The above activities are scheduled and interrelated, based on the PDCA principles (Plan, Do, Check, Act).
In a Quality Assurance system, students play a fundamental role: each student can play their part by participating in the Quality Assurance groups of their degree program and in the Faculty-Student Joint Committees or, more simply, by taking part in the Student Survey on teaching, or questionnaires. It’s in this context that specific workshops for student representatives (‘Laboratori di rappresentanza attiva’) are periodically made available to students by the University and the University’s Quality Assurance Board.