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2nd Level Master in Data Science and Statistical Learning (MD2SL)

(in collaboration with the Florence Center for Data Science of the University of Florence)

The Program

By integrating the methodologies of statistics, mathematics, and computer science, Data Science is establishing itself in contemporary societies as a fundamental discipline to extrapolate information from data and provide answers to relevant research questions. Thanks to the powerful tools on which it is based, Data Science plays a central role in all those areas in which big-data are becoming increasingly relevant, including economics, medicine, engineering, education, social sciences, etc.
The 2nd level Master in Data Science and Statistical Learning (MD2SL), promoted by the IMT School for Advanced Studies Lucca and the Florence Center for Data Science of the University of Florence, aims to equip professionals with extensive theoretical knowledge of more advanced statistical, IT and computational tools. The program will allow participants to use and critically evaluate the potential of different methods to extract information from the increasing amount of data available in diverse application areas, with particular reference to applications in the economic-managerial and health sectors, to provide research questions and foster innovation.
The presence of notable partners from the business and research world gives a practical and concrete imprint to the master's program; this feature will be further strengthened by the internship experience at some of the partners and other institutions involved in the program.

Educational Objectives and Career Opportunities

At the end of the program, participants will:
  1. be able to structure, clean, and analyze complex, unstructured, and high-dimensional data;
  2. be able to identify the relevant information, as well as develop innovative methodological and computational solutions for data collection and analysis, to address emerging information needs and support decision-making processes in the medical/health or economic/corporate field;
  3. possess strong communication skills, which are essential for adequate and effective dissemination of results, also to individuals without a technical background in Data Science.
The resulting professional profile can find employment in different fields such as Public Administrations and local authorities, data analysis units of medium and large enterprises, insurance companies, marketing offices of production and distribution companies, research centers, and consulting firms.
Furthermore, thanks to the solid theoretical foundations acquired during the program, students will be ready to access doctoral programs related to the topics covered, in Italy and abroad.
Professor Massimo Riccaboni is the representative of the IMT School for the II level Master in Data Science and Statistical Learning (MD2SL).
For further information, please visit the Master's website:

Educational activities

The 2nd level Master in Data Science and Statistical Learning (MD2SL) is articulated in three distinct teaching blocks and a data analysis laboratory.
It provides a solid knowledge of the disciplines at the base of Data Science (mathematics, statistics, computer programming), to ensure a homogeneous preparation of students with potentially very different backgrounds.They provide students with the theoretical and practical skills of Data Science and Data Analytics.Designed for the acquisition of specific skills in two distinct application areas in which the Data Scientist can play a role of central importance: the medical/health and the economic/business fields.
The specific objectives of each block are achieved through a well-balanced mix of theoretical lectures, case study analysis, workshops, and individual and group practical activities. The latter encourages exchanges and interactions among students for a greater and deeper understanding of the topics covered. At the end of the program, students have the opportunity to apply the knowledge acquired to an internship at one of the public or private companies, research centers and units or at public bodies partners of the master's program.
For further information, please visit the Master's website:

Organizing Committee





For further information on the admission, selection and enrollment processes please visit the Master's website: