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University of Trento Master in Data Science
University of Trento

Master in Data Science

Trento, Italy

2 Years

English

Full time

Request application deadline

Sep 2024

EUR 4,500 / per year *

On-Campus

* EU 340€-3400€ (fee range based on personal income and merit); Non-EU: 1000€-4500€ (fee range based on merit only, i.e. score in the application evaluation).

Introduction

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 Psychology 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

Objectives

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, and public and private companies.

The aim is to create a new professional figure capable of combining interdisciplinary knowledge and interpersonal, communicative, and organizational 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-organizational, and regulatory issues;
  • Corporate-organizational, being able to govern complex organizations using modern technologies, such as in the field of e-commerce and web-based services;
  • Socio-psycho-economic, having 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 transversely 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 explore advanced technical concepts in the fields of mathematics, statistics, and information technology.

The interdepartmental nature of the study course makes it possible to accept students from different backgrounds and to provide them with a highly interdisciplinary curriculum. The first year will include courses aimed at integrating the different competencies and will cover the fundamental disciplines of Informatics, Mathematics, Statistics, and Social, Psychological, and Economic Sciences. These introductory courses will be followed by courses and workshops on relevant applications of Data Science, in particular for Social, Psychological, and Economic Sciences. An adequate offer of optional courses and workshops will allow the design of courses aimed at specific areas. As a result, students earning a master's degree in Data Science will be provided with a cultural, scientific, and methodological background that will allow her/him to access university programs after the master's level (second-level Master's and Ph.D.).

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