Master's Degree in Data Science and Statistical Learning (MD2SL)
In collaboration with the Florence Centre for Data Science of the University of Florence
Originating from the integration of methodologies belonging to statistics, mathematics and computer science, Data Science is imposing itself in contemporary societies characterised by the continuous production of big data as a fundamental discipline to be able to extract information from data and provide answers to relevant research questions. Thanks to the power of the tools on which it is based, Data Science plays a central role in all those fields in which big data is becoming increasingly relevant, including economics, medicine, engineering, education and social sciences.
The 2nd level Master's Degree in Data Science and Statistical Learning (MD2SL), promoted by the IMT School for Advanced Studies Lucca and the Florence Centre for Data Science of the University of Florence, is aimed at training professional figures characterised by a deep theoretical knowledge of the most advanced statistical, computing and computational tools, capable of using and critically evaluating the potential of the various methods for extrapolating information from the growing mass of data available in various application fields, with particular reference to applications in the economic-managerial and health fields, providing answers to research questions and fostering innovation.
The presence of prominent partners in the world of business and research gives a practical and concrete imprint to the Master's programme. This will be further strengthened thanks to the internship course to be carried out at one of the partners’ or organisations’ premises, which will bring their own testimony to the Master's programme.
Professors Massimo Riccaboni and Tiziano Squartini are the representatives of the IMT School for Advanced Studies Lucca for the Master's Degree programme in Data Science and Statistical Learning (MD2SL).
The Master’s programme is aimed at developing all-round professional figures, Data Scientists, able to provide answers to emerging research questions arising from the pervasive presence of complex, unstructured and high-dimensional data (the so-called big data), in a variety of application fields.
This target is achieved through the students’ acquisition of solid theoretical and practical skills in the fields of statistics, mathematics and computer science, which can be used in business processes, in Public Administrations, as well as to support the decision-making processes of public and private organisations. Specifically, the training proposal aims to bring graduates in quantitative disciplines to a higher level thanks to the multidisciplinary nature of Data Science tools.
In today's societies characterised by the continuous production of big data, Data Science is imposing itself as a fundamental discipline to be able to extract information from data and provide answers to relevant research questions.
Data Science stems from the integration of methodologies belonging to statistics, mathematics and computer science and, thanks to the power of the tools on which it is based, it plays a central role in all those fields in which big data is becoming increasingly relevant. These include economics, medicine, engineering, education and social sciences.
The MD2SL Master's programme aims to train all-round professionals – the Data Scientists – capable of answering the emerging research questions arising from the pervasive presence of complex, unstructured and high-dimensional data (the so-called big-data), in the most diverse fields of application.
Exit skills
Upon completing the programme, students will be able to structure, clean and analyse complex, unstructured and high-dimensional data, will be able to identify relevant information coming from such data, as well as to develop innovative methodological and computational solutions for their collection and analysis, in order to cope with emerging information needs and support decision-making processes in the medical-health and/or economic-business fields. The outgoing profile will also possess solid communication skills that are indispensable for an adequate and effective dissemination of results, also towards subjects without a technical background on Data Science methods.
Job Profiles
Outgoing professionals can find employment in a variety of fields including Public Administrations and local authorities, data analysis units of medium-sized and large companies, insurance companies, marketing departments of production and distribution companies, research centres and consultancy firms.
In addition, thanks to the solid theoretical foundations acquired during the course, upon successful completion of the programme, students will be ready to access Doctoral programmes related to the topics covered, both in Italy and abroad.
The MD2SL Master's Course comprises 16 hours of teaching per week, Wednesday to Friday from 3:30 PM to 7:30 PM and Saturdays from 9 AM to 1 PM.
Teaching takes place synchronously and is offered in a mixed mode (both online and face-to-face). A 75% attendance requirement for lectures is required. However, the final exam must be taken in presence in Florence, Italy.
The MD2SL Master's programme is divided into three distinct teaching blocks and a data analysis lab.
- The first block, “Data Science Bootcamp”, allows students to acquire a solid knowledge of the disciplines underlying Data Science (mathematics, statistics, computer programming), thanks to a series of courses designed to ensure a homogeneous preparation of students with potentially very different backgrounds.
- The second block is made up of the “Core Courses” and enables students to acquire the theoretical and practical skills typical of Data Science and Data Analytics.
- The third block consists of the “Elective Courses” and is designed for the acquisition of specific skills in two distinct application areas in which the Data Scientist can play a central role: the medical-health field and the economic-business field.
The specific objectives of each block will be achieved through a well-balanced mix of frontal theoretical lectures, analysis of case studies, workshops and individual and group practical activities. The latter will aim to foster exchanges and interactions between students useful for a greater and deeper understanding of the topics covered. There will be in itinere examinations on each individual module.
The degree will be awarded upon verification of attendance and after a final examination, which will consist of the presentation of a project relating to the application of one of the methodologies introduced during the Master's course to real case studies, hopefully resulting from the training placement.
Coordinator: Chiara Bocci, University of Florence
Organising Committee:
- Andrew David Bagdanov, University of Florence
- Chiara Bocci, University of Florence (Coordinator)
- Giorgio Stefano Gnecco, IMT School for Advanced Studies Lucca
- Anna Gottard, University of Florence
- Maria Francesca Marino, University of Florence
- Massimo Riccaboni, IMT School for Advanced Studies Lucca
- Tiziano Squartini, IMT School for Advanced Studies Lucca
- Silvia Bacci, University of Florence
- Michela Baccini, University of Florence
- Andrew David Bagdanov, University of Florence
- Gianmarco Bet, University of Florence
- Ennio Bilancini, IMT School for Advanced Studies Lucca
- Chiara Bocci, University of Florence
- Leonardo Boncinelli, University of Florence
- Cesare Bracco, University of Florence
- Carlotta Giannelli, University of Florence
- Giorgio Stefano Gnecco, IMT School for Advanced Studies Lucca
- Anna Gottard, University of Florence
- Gianluca Iannucci, University of Florence
- Matteo Lapucci, University of Florence
- Stefano Lepri, CNR-ISC
- Giampaolo Liuzzi, "Sapienza" University of Rome
- Erik Longo, University of Florence
- Alessandro Magrini, University of Florence
- Giovanni Maria Marchetti, University of Florence
- Simone Marinai, University of Florence
- Andrea Marino,University of Florence
- Maria Francesca Marino, University of Florence
- Alessandra Mattei, University of Florence
- Anna Carla Nazzaro, Università degli Studi Internazionali di Roma
- Fabio Pinelli, IMT School for Advanced Studies Lucca
- Massimo Riccaboni, IMT School for Advanced Studies Lucca
- Armando Rungi, IMT School for Advanced Studies Lucca
- Giacomo Scandolo, University of Florence
- Lorenzo Seidenari, University of Florence
- Francesco Sera, University of Florence
- Francesco Serti, IMT School for Advanced Studies Lucca
- Tiziano Squartini, IMT School for Advanced Studies Lucca
- Giacomo Toscano, University of Florence
- Cecilia Viscardi, University of Florence
At the end of the programme, students will have the opportunity to field test the knowledge acquired through a 225-hour internship to be carried out in one of the programme's partner companies and public and private organisations, research centres or university departments. The work placement will enable students to follow first-hand the design, implementation and development phases of software and the realisation of complex data analyses.
- The internship activities are aimed at enabling students to acquire specific skills such as:
the ability to apply the acquired technical skills to real cases problem solving scenarios in the design, execution and monitoring phases of specific projects; - skills for communicating the results of activities related to projects developed in corporate or institutional contexts;
- management skills useful in all phases of the development of Data Science and big data analytics projects.
The course is recognised by MIUR as a Level II Academic Master's Degree and allows the acquisition of 64 CFUs.
The MD2SL Master's Course has a minimum of 10 and a maximum of 25 participants.
Application for admission
The application for admission must be submitted exclusively online.
The call for applications and the admission procedure for the next edition of the Master's programme are now open.
The application for admission must be submitted by 15 November 2024 at 12:30 PM (Italian time), using the procedure defined on the https://ammissioni.unifi.it/INFO/ portal.
Applicants will be asked to provide the following:
- personal data;
- Curriculum Vitae in pdf format.
After filling out the application form, the system will request the payment of €50.00, as a contribution for administrative charges related to the selection.
Selection procedures for admission to the Master's programme
The selection of candidates consists of an examination of the applications and an interview in English, remotely, in order to verify the candidate's preparation, aimed at a fruitful participation in the Master's courses, on statistics, mathematics and programming/informatics, as well as knowledge of the English language at the level B2.
The interview will be held on 3 December 2024 at 9:30 AM (remotely).
Publication of the ranking list
The ranking list of those admitted will be published on 10 December 2024.
Registration of those admitted to the Master's Programme
Those admitted to the Master's programme must apply exclusively online by 13 January 2025 at 12:30 PM (Italian time).
They will be asked to provide:
- a passport size photo;
- an admissible identity document.
Classes will start on 29 January 2025.
Enrolment in Individual Modules
The Master's Programme offers the possibility of enrolling in individual modules.
The Master's modules in which selected students can enrol individually are provided below.
There are 2 places for enrolment in single modules. The cost is €100 per CFU.
The timetable with deadlines for enrolling in the individual modules is as follows:
- 9 January 2025: Application deadline;
- 15 January 2025 at 9:30 AM (remote): Admission test (if more than the number of places available);
- 22 January 2025: Publication of the admission ranking list;
- 28 January 2025: Application deadline.
Admission requirements: In order to be admitted to individual modules, candidates must possess one of the qualifications listed among those required for admission to the Master's programme.
Admission test: The selection of candidates for enrolment in individual modules will take place if the number exceeds the places available and will consist of an interview.
Costs
The enrolment fee of €4,500 can be paid in two equal instalments: the first instalment must be paid at the time of enrolment; the second instalment in the subsequent months (specifically, for the next edition, by 17 June 2025).
It is also possible to enrol in individual modules. The list of courses available as single modules can be consulted on the Master's degree announcement. In this case the registration fee is €100/CFU. To be admitted to individual modules, you must hold one of the qualifications listed among those required for admission to the Master's programme.
Each year, a variable number of scholarships of an amount equal to the enrolment fee are available for Italian or foreign students enrolling in the 2nd Level Master's Course in Data Science and Statistical Learning (MD2SL).
Scholarships
As regards the scholarships granted by the University of Florence, at the end of the academic year, 10% of enrolled students who have applied and have an ISEE 2025 within the first contribution bracket established by the 2024/2025 Study Manifesto, may benefit from scholarships to reimburse the tuition fee. These grants, subject to applicable taxation, are awarded according to a ranking based on final Master's degree grade and, in the event of a tie, on age. More information is available at https://www.unifi.it/master and in the Notice of Selection for Admission to the Masters Courses - Annex B.
2024/2025 Edition
The call for applications for 2 scholarships for enrolment in the Master's Degree Course in Data Science and Statistical Learning (MD2SL) has been published.
The deadline for applications is 28 November 2024 at 1 PM.
Announcement D.D. no. 11478/2023 prot. no. 251078 of 20/10/2023
published on the Official Register repertory no. 12384 from 20/10/2023 to 23/11/2023
Application to fill out (Annex A)
Curriculum Vitae (Annex B)
Scientific and Administrative Secretariat
University of Florence
Department of Statistics, Informatics, Applications “Giuseppe Parenti” (DISIA)
Viale Morgagni, 59, 50134 - Florence
md2sl@disia.unifi.it
Scientific Secretariat:
School IMT Alti Studi Lucca
PhD and Higher Education Office
Piazza San Ponziano, 6, 55100 - Lucca
highered@imtlucca.it