Master in Data Science

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 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, 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 years (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 years (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.

The person with a degree in Data Science:

• Can 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;
• Can 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;
• Can 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;
• Can 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, and 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;
• Can 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; can 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, and legal validity).

The person with a master's degree in Data Science can 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 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, can 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 the in-depth knowledge acquired graduates can:

• 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 visualization of information.

Employment opportunities

In the world, 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 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.