Master programs for data scientists

In addition to the master’s degrees in Statistics and Data Science, Computer Science, Design of sustainable tourism systems, and Software: Science and Technology, we have recently activated the master’s degree in Data Science, Scientific Computing & Artificial Intelligence.

Data Science, Scientific Computing & Artificial Intelligence

Scientific Coordinator: Prof.ssa Donatella Merlini

Other DiSIA members: Michele Boreale, Daniele Castellana, Anna Gottard, Monia Lupparelli, Andrea Marino, Alessandra Mattei, Maria Cecilia Verri

Network: Dipartimento di riferimento: Statistica, Informatica, Applicazioni “G. Parenti” (DISIA). Dipartimenti associati: Chimica “Ugo Schiff” (DICUS), Biologia (BIO), Fisica e Astronomia, Matematica e Informatica “Ulisse Dini” (DIMAI)  e Scienze della Terra (DST) dell’Università di Firenze.

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.

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 of mathematical-statistical training;
• 27 CFU of computer science training;
• 6 CFU of  legal-linguistic training;
• 18 CFU of training in various scientific disciplines;
• 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 courses which will be in English. The activities planned over the 2 years, with the related teaching load, are described on the web page of the Master (available at: https://www.datascience-cs-ia.unifi.it/ )

Career opportunities

Graduates in Data Science, Scientific Calculation & 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 scientific computing;
• 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.

More info: https://www.datascience-cs-ia.unifi.it/