Master of Science in Data Science

he digitisation of information from physical and social systems has considerably increased the production of data in recent years – this process goes under the name of Big Data. New technologies have made the interconnection, the interaction, the exchange and the collection of data easily accessible to public administrations, private companies, non-governmental organisations, and individual citizens. This is driving a series of economic, social and political changes that require strong innovation in all areas of science and business. In the psychological and social sphere, Big Data has enormous potential to change the way of studying human behaviour, lifestyles, and in general the changing ways according to which we interact with the world around us. In economic and managerial terms, the availability of information on individuals' behaviours creates new channels of communication and interaction with consumers. On this basis, companies have come to develop new business models to deal with an increasingly dynamic and complex market. In industry, the so-called Industry 4.0, or Smart Manufacturing, represents in fact Data-Driven Manufacturing. Thanks to the improved performances and the reduced cost of sensor and processing systems, information extracted from large amounts of data has become an essential factor in the development of industrial automation and advanced robotics. The availability of large amounts of data is also an inescapable factor in reducing energy costs and environmental impact, increasing productivity, optimising resources, and ultimately allowing companies to be more competitive in the global economy.

Data are thus no longer just information, but rather a resource with its own economic value that grows along with its usability. As social and economic systems become increasingly complex, governments call for tools that allow sensible real-time decision-making. These transformations are shaping a range of new professional profiles, collectively known as Data Scientists. These profiles share a wide set of skills: they are capable of working in dynamic and multidisciplinary environments; their role is to choose, collect, analyse and select data in a creative and innovative manner, as to allow the decision-maker, be it a manager or a researcher, to make informed choices, anticipating trends and seizing opportunities.

The formation of any Data Scientist, therefore, can only be multidisciplinary. Computing, mathematics, statistics and social and economic sciences will have to be carefully interwoven within a single training path.

For these reasons, the Departments of Mathematics, Sociology and Social Research, Information Engineering and Computer Science, Industrial Engineering, Psychology and Cognitive Sciences, Economics and Management, the Center for Mind/Brain Sciences, and the Fondazione Bruno Kessler (FBK) have decided to set up an interdepartmental Master of Science (Laurea Magistrale) in Data Science at the University of Trento.