INTRODUCTION

The Master's Degree Course in Data Science, Scientific Computing & Artificial Intelligence of the LM-DATA Data Science class  borns in the academic year 2023/24 as a transformation of the Data Science Curriculum of the Master's Degree Course in Computer Science of the LM-18 class.

The Ministerial Decree 146 of 02/09/2021 established the new LM-DATA  degree class with the aim of training specialists capable of using mathematical-statistical-computer science techniques within companies and public and private administrations, including scientific and technological research bodies or institutes, in particular as regards the production, management, treatment, analysis and use of large amounts of data in specific application sectors including the biological, chemical, physical and geological fields.

When the new LM-DATA Data Science degree class was established, the educational offer was evaluated with respect to both the current needs of the territory and the labor market and the possibility of taking advantage of collaborations among colleagues from the Scuola di Scienze Matematiche, Fisiche e Naturali who have been carrying out teaching and research activities for years in the context of data production and analysis and scientific and high-performance computing.

It therefore seemed natural to transform the pre-existing Data Science Curriculum into a new course of study in the new LM-DATA Data Science degree class, involving all the Departments of the scientific area of the University and promoting a multidisciplinary course consistent with the excellence profiles of the search for the departments involved.

LEARNING OBJECTIVES

The Master's Degree Course in Data Science, Scientific Computing & Artificial Intelligence intends to provide a degree course in a certainly emerging sector such as that of data science and scientific computing. In fact, the profession of Data Scientist is naturally emerging as one of the most sought professions on the market and the demand significantly exceeds the actual availability of these figures. The course of study therefore has the objective of training professional figures capable of answering research questions arising from the pervasive presence of complex data, both structured and unstructured, and of high dimensionality (so-called big data) in the most varied fields of application; in particular, in scientific fields of an interdisciplinary nature involving biology, chemistry, physics, and geology.

This objective is achieved through the acquisition of solid theoretical and practical skills in various fields of computer science, mathematics and statistics and their application through various paths declined in the various scientific fields, including those of in-depth study of computer science and mathematics for data science, scientific computing and artificial intelligence.

REQUIREMENTS TO ENROLL

See Enrolment.

STRUCTURE OF THE COURSE OF STUDY

The Degree Course is divided into 2 years for a total of 120 credits (ECTS) and normally the student's activity corresponds to the achievement of 60 CFU per year. The following types of training activities are foreseen:

• 27 CFU caratterizzanti of mathematical-statistical training;
• 27CFU caratterizzanti of computer science training;
• 6 CFU  caratterizzanti of  legal-linguistic training;
• 18 CFU affini of training;
• 18 CFU  self-chosen by the student;
• 24 CFU for the final exam and further training activities.

In order to enhance the heterogeneity of incoming students, the study program offers diversified  activities of typology caratterizzante and a wide range of activities of typology affine on emerging Data Science topics. This makes it possible to offer students, also according to their own interests, a wide choice and deepening of knowledge and skills on emerging scientific topics. In particular, some courses in computer science, mathematics and statistics of typology caratterizzante, foreseen in the first year, must be chosen by the student on the basis of their knowledge and skills. Also in the first year, some courses are compulsory for all students. The same consideration applies to a set of courses of typology affine chosen by the student, which can always be selected according to the knowledge and skills required.

The training activities of typology affine combine mathematics, statistics and information technology skills with disciplinary fields such as those of biology, chemistry, physics and geology (for example, biology and computational chemistry; the predictive methods of structural biology,  statistical phisics, physics of complex systems and modern geology; methods for the analysis of biological, geological with spatial characterization and for environmental chemistry data, and of images in the various fields of physics). Furthermore, the activities of typology affine broaden the mathematical, statistical and computer science skills in specific methodological and applicative fields of support to Data Science.

Furthermore, in various courses there will be projects and laboratory activities that will allow students to deal directly with the most advanced Data Science tools and with the resolution of concrete problems. As regards the educational activities chosen individually by the student, courses of typology caratterizzante and affine not previously chosen or other courses activated in the University may be selected. The choice of these activities is free as long as it is consistent with the training project.

The courses will be held in Italian, except for some optional optional courses which will be in English. The activities planned over the 2 years, with the related teaching load, are described on the page Organization of teaching activities.

THESIS

 Under the supervision of a member of the Degree Course Council, second half of the second year will be almost exclusively dedicated to in-depth activities and to the realization of a theoretical or practical project which will lead to the drafting of an original personal paper (final exam) .

CAREER OPPORTUNITIES

Graduates in Data Science, Scientific Computing & Artificial Intelligence will possess the skills to directly address public administrations,  companies and laboratories that are active in sectors such as the management of large databases and the collection, processing and analysis of large amounts of data, especially in the fields of biology, chemistry, physics and geology, as well as the production of data through numerical simulations.

In particular, two main occupational and professional outlets can be identified:

• the first, an expert in systems and methodologies for data management, security, modeling and analysis, corresponding to courses that include more advanced level courses and in-depth study of information technology and mathematics for data science and calculation scientific;
•  second, an expert in the production and processing of scientific data, corresponding to courses that especially study scientific applications in biology, chemistry, physics and geology.

Given the enormous interest in scientific research in the sector, obviously both from university and from the most advanced industries, the degree course will try to favor the brightest minds by encouraging them to continue with third-level studies.