Master in Data Science
Trento, Italy
Master degree
DURATION
2 years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
Sep 2026
TUITION FEES
EUR 4,500 / per year **
STUDY FORMAT
On-Campus
* for non-EU citizens living abroad: 4 March 2026 | only for EU citizens and non-EU citizens regularly residing in Italy: 1 April to 29 May 2026
** 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).
Key Summary
The Master's is a multidisciplinary degree offered jointly by the following organisations 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 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 take 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 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 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 Master's degree, 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 organisation, 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 organisational processes in the private, public and third sector. 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.
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 Information Science, 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 subsequent to the Master level (second-level master's and PhDs).
The Master's in Data Science is organised into two curricula. Students enrol in one of the two curricula according to their previous studies.
- Curriculum A is meant for students who have a Bachelor's degree (Laurea) in Computer Science, Mathematics, Physics, Statistics or Engineering.
- Curriculum B is meant for students who have a Bachelor's degree (Laurea) in Sociology, Economics or Psychology.
Each curriculum represents a 120 CFU workload which includes mandatory courses, elective courses, and labs, open-choice courses, a stage and a thesis, as detailed below.
Students in both Curricula should additionally complete the following activities:
- Elective course - 2nd year (6 CFU): Students are required to choose 6 CFU from a list of elective courses that will be advertised in due time (see Regulations for further information).
- Elective laboratories - 2nd year (12 CFU): Students are required to choose 12 CFU from a list of elective laboratories, which will be advertised in due time (see Regulations for further information).
- Open-choice courses (12 CFU): Students are required to choose 12 open-choice credits among the courses offered by the University of Trento. The courses listed in the tables above are automatically approved. In all other cases, a personalised study plan must be completed and submitted to the commission for study plan examination.
- Stage (9 CFU).
- Thesis (18 CFU): The course of studies is concluded with the discussion of an original thesis, under the guidance of a supervisor, providing 18 CFU.
The graduate with a degree in Data Science:
- Is able to understand the origin and characteristics of the processed data; knows the ICT technologies connected to the life phases of the data, and their performance limits; can analyse and manage the flow of generation, acquisition, transmission, and access to data; can manage and integrate heterogeneous archives of statistical and administrative data;
- Is able to combine the methods and techniques of social sciences and psychological sciences, business management and public and private administration with the technologies and methodologies of information technology and data analysis of mathematics and statistics, possessing skills in each of the areas and managing to effectively interpret change and technological and organisational innovation in companies and administrations;
- Is able to analyse and interpret data according to their nature and variety, applying the most appropriate analytical approach to respond to the activities or objectives of the organisation or public or private body.
- Is able to identify and access data sources and choose the most suitable and effective methods and models to support and guide the decision-making processes and strategic choices of the company and management, can develop lines of evolution, operational plans and generate indications and programs for the development of action also through the application of techniques to reduce dimensional complexity and the development of predictive models to generate organized systems of advanced knowledge.
- Is able to work in interdisciplinary working groups and can use the most appropriate methods of communication and storytelling to present empirical evidence in the most suitable form to support tactical and strategic management decisions, paying particular attention to issues related to the synthesis and effective representation and visualization of information; is able to use fluently English as well as Italian, in written and oral form, with reference also to disciplinary lexicons.
- has basic legal knowledge in the areas and regulatory issues related to the use of information technology and data processing (with reference, among others, to security issues, protection of confidentiality, legal validity).
Scholarships and tuition fees for Non-EU Citizens living abroad
Top-scored candidates will be entitled to receive a UniTrento scholarship assigned by the Evaluation Committee based on the application score. Tuition fees are waived for students who receive a UniTrento scholarship.
The amount of tuition fees for Non-EU applicants living abroad is related to the application score obtained during the selection. For more information, check the UniTrento scholarships web page.
Scholarships and tuition fees for EU Citizens and non-EU citizens regularly living in Italy
DSU (Diritto allo Studio Universitario) Scholarships are available for EU citizens and non-EU citizens living in Italy who meet the ISEE requirements based on the family income. Further information is available on Scholarships starting from June/July.
Details about tuition fees and ISEE are available on the Opera Universitaria web page.
The person with a Master's degree in Data Science is able to take part in or hold technical and/or managerial roles in contexts that require a good knowledge of the disciplines of Computer Science, Mathematics, Statistics and Social Sciences and a thorough knowledge of data processing for problem-solving purposes. The Data Scientist is a professional figure responsible for the collection, analysis, elaboration, interpretation, dissemination and visualisation of quantitative or quantifiable data of the organisation for analytical, predictive, or strategic purposes. In her/his work, she/he identifies, collects, compiles, prepares, validates, analyses and interprets data concerning different activities of the organisation in order to extract information (of synthesis or derived from analysis), also through the development of predictive models to generate advanced, organised knowledge systems. The data scientist is, therefore, an analyst of large amounts of highly complex technical data (Big Data and Open Data). Furthermore, they are able to combine methods and techniques of business management and public, private and third sector administration with technologies and methodologies of computer science and social sciences, possessing skills in each of the areas.
Competencies associated with the degree
Thanks to the in-depth knowledge acquired, graduates are able to:
- Identify and access data sources;
- Support and develop business processes;
- To choose suitable and effective methods and models to support strategic business decisions;
- Develop lines of evolution and operational plans;
- Abstract the information obtained and, through it, generate indications to support the active development programs;
- Finally, the Data Scientist presents this information in the most suitable form to support management's tactical and strategic decisions, paying particular attention to the issues related to the synthesis and effective representation and visualisation of information.
Employment Opportunities
Worldwide there is a growing interest in Big Data, Open Data, and the Data Scientist profession due mainly to the growing demand for this professional figure in the Analytics market by the more traditional sectors of the economy, including banking, manufacturing, telecommunications and media; Public Administration and health; other business services; large-scale distribution; utilities; and insurance.
In concrete terms, the skills acquired by people graduating with the Master's Degree in Data Science will give them professional and career opportunities in:
- Public or private market research and analysis institutes;
- Organisations oriented, at the national or international level, to the formulation and implementation of social and economic policies;
- Organisations, public or private, oriented towards innovation and the promotion of services and products for consumers, the design of new services in the public sector, or the definition of new communication strategies;
- Private companies, including small and medium-sized companies, consider it strategic to make effective use of the information available in planning market strategies, processes, and product innovation, and company management.