Studyportals
M.Sc. On Campus

Data Science

University of Trento

24 months
Duration
4500 EUR/year
3400 EUR/year
Unknown
Tuition fee
Passed
Unknown
Apply date
Unknown
Start date

About

The Data Science programme from University of Trento 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. 

Overview

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, 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-organisational, being able to govern complex organizations 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 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.

Program Overview

The Master's Degree program in  Data Science is a two-year full-time program taught in English, which aims at training trains professional figures with strong transversal competences that can work in multidisciplinary environments. The person with a master's degree in Data Science will be able to manage and analyze large amounts of data produced by natural and social systems to support decision-making processes in the economic-productive, political-social, and scientific research activities in the fields of public administration, industry, public and private services, and the third sector.

The person with a Master's degree in Data Science will be able to hold high-profile technical and/or managerial roles in contexts that require a good combination of skills in computer science, mathematics, statistics, and social, psychological, and economic sciences.

At the end of the course, the person with a master degree in Data Science will be able to analyze the elements that contribute to the formation of the data being analyzed and to identify possible sources of noise, bias, and uncertainty; she/he will be able to use the IT platforms for the storage, management, and transformation of data, being aware of the performance limits and/or the advantages offered by the various platforms; she/he will be able to identify the strategic objectives that can be better-pursued thanks to data analysis, also by effectively combining the methodologies of social and psychological sciences.

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 subsequent to the master's level (second level Masters and PhDs).

Program Outcome

The person 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 analyze 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 organizational innovation in companies and administrations;

Is able to analyze and interpret data according to their nature and variety, applying the most appropriate analytical approach to respond to the activities or objectives of the organization 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).

Curriculum

The Master in Data Science is organized into two curricula. Students enroll in one of the two curricula, according to their previous studies.

Curriculum A is meant for students who have taken a bachelor's degree (Laurea) in  Computer Science, Mathematics, Physics, Statistics, or Engineering.

Curriculum B is meant for students who have taken 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 - II 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 - II 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 personalized 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.

Career Opportunities

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 visualization of quantitative or quantifiable data of the organization 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 organization in order to extract information (of synthesis or derived from analysis), also through the development of predictive models to generate advanced organized knowledge systems. The data scientist is, therefore, an analyst of large amounts of highly complex technical data (Big Data and Open Data) which, however, is 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 function thanks to in-depth knowledge to: 

Identify and access data sources; Support and develop business processes; 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 visualization of information.

Employment opportunitiesIn the world: 

There is a growing interest in Big Data, Open Data, and the Data Scientist profession due mainly to the growing demand of 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 this context, the professional figure of the Data Scientist, coherently with the flexibility in the educational path offered by the LM 91 class, will be characterized to a greater extent, according to the individual student's options, by the capacity of substantive reading of socio-economic-psychological data or by the ability to develop analytical tools useful for their elaboration and presentation. 

In concrete terms, the skills acquired by people graduating from this Master's Degree will give them professional and career opportunities in: public or private market research and analysis institutes; organizations oriented, at the national or international level, to the formulation and implementation of social and economic policies; organizations, 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, process, and product innovation, and company management.

Programme Structure

Courses include:

  • Data mining
  • Social and psychological science:
  • ICT and social science theory and models
  • ICT cognitive psychology theory and models
  • Information, knowledge and service management
  • Mathematics for data science
  • Programming
  • Algorithms and data structures

Key information

Duration

  • Full-time
    • 24 months

Start dates & application deadlines

More details

Application Period

12/15/2021-04/03/2022: NON-EU citizens permanently living abroad. 

05/03/2022-30/06/2022: EU students and NON EU students living in Italy.

Language

English

Credits

120 ECTS

Delivered

On Campus

Academic requirements

We are not aware of any academic requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • Bachelor’s degree (or equivalent)
  • Courses taken in following areas: Computer Science/Information Engineering- Sociology/Economics/Psychology/Law- Mathematics/Statistics
  • English at B2 level of the Common European Framework of Reference for Languages
  • Please check the Call for Applications for more details.

Tuition Fee

To alway see correct tuition fees
  • International

    4500 EUR/year
    Tuition Fee
    Based on the tuition of 4500 EUR per year during 24 months.
  • EU/EEA

    3400 EUR/year
    Tuition Fee
    Based on the tuition of 3400 EUR per year during 24 months.
  • 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) 

Living costs for Trento

700 - 1000 EUR /month
Living costs

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

Funding

Scholarships for non-EU Citizens living abroad

Top-scored candidates will be entitled to receive a UniTrento scholarship. Students that benefit from a UniTrento scholarship will also have the tuition fees waived. 

Scholarships for EU Citizens and Non-EU citizens regularly living in Italy

Scholarships are based on income/merit. Information on the tuition fees and ISEE index (economic index of your family financial situation) are available on the Infostudenti UniTrento web page. Please note that if you do not want to calculate the ISEE index, you will have to pay the maximum tuition amount. Once the ISEE has been calculated, eligible students can apply for the Opera Universitaria scholarship starting from June/July.

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Our partners

Data Science
-
University of Trento

Wishlist

Go to your profile page to get personalised recommendations!