The Master programme (Laurea Magistrale) in Data Science will provide graduates with a deep theoretical, methodological and practical understanding of mathematics and statistics, computer science, while at the same time providing them with domain-specific knowledge in fields like Social and Political Sciences, Psychology, Law and Business. Graduates will be able to put their expertise to work in the private, public and third sector, being knowledgeable about the treatment of data and their analysis. Great emphasis will be given to the acquisition of practical abilities and soft skills - for example many of the labs and courses will provide teamwork oriented activities as part of interdisciplinary workshops often with the participation of non-academic stakeholders. These abilities and skills will be further strengthened through training placements within public administrations, private companies, research institutes and laboratories, as well as stays at other Italian and European universities. The overarching objective of the programme is to foster the acquisition of interdisciplinary knowledge applied to concrete cases and of relational, communicative, negotiating and organisational skills.
The Master is a multidisciplinary degree offered jointly by the following organizations at the University of Trento:
- Department of Mathematics
- Department of Information Engineering and Computer Science
- Department of Economics and Management
- Department of Psycology and Cognitive Science
- Department of Industrial Engineering
- Department of Sociology and Social Research
- CIMEC - Centre for Mind/Brain Sciences
- and by FBK - Fondazione Bruno Kessler
The Interdepartmental Master's Degree Course in Data Science trains students to become data analysis professionals with strong transversal skills and the ability to work in dynamic and multidisciplinary environments with theoretical, methodological and practical knowledge in computer science, mathematics and statistics and in one or more of the domains of competence that are at the base of Data Science, such as Social, Cognitive, Economic, Industrial Sciences and Law.
During training, special attention will be paid to the acquisition of know-how and the development of soft skills. As early as the first year the student will be asked to follow a large group of classes that involve laboratory activities, interdisciplinary working groups and case studies with the direct involvement of experts in the field. These skills are then further developed through internships and traineeships in public institutions, research institutes, laboratories, public and private companies.
The aim is to create a new professional figure capable of combining interdisciplinary knowledge and interpersonal, communicative and organisational skills, who will be able to hold high-profile technical and/or managerial roles in highly interdisciplinary contexts in the following fields:
- technology, being able to manage projects and apply innovative solutions in the field of information and IT systems and network technologies, taking into account commercial, socio-organisational and regulatory issues;
- corporate-organisational, being able to govern complex organisations using modern technologies, such as in the field of e-commerce and web-based services;
- socio-psycho-economic, being in possession of a the basic skills required to design technologically innovative solutions in public and private institutions, such as in the field of eGovernment and market research.
At the end of the course, graduates will be able to work transversally across several departments of a company or administration according to their domains of competence transforming data into actionable information. By filling the role of Data Scientist in an organization, graduates will be supporting managerial functions with the information required to make informed decisions, sometimes anticipating trends and seizing opportunities of great economic, social, political or ethical importance as well as in the definition and planning of production, logistical and organizational processes in the private, public and third sector sectors. Depending on their interests, they will also be able to deepen their knowledge of advanced topics in the field of Data Science with applications in specific domains of competence, and/or to explore advanced technical concepts in the fields of mathematics, statistics and information technology.