The course of study in Data Science for the Human and Social Sciences, in line with the specific objectives of the LM91 degree class, aims to train professionals capable of grasping the multidisciplinary aspects of data analysis and interpretation in the various fields of application, with particular attention to the human and social sciences.
The degree course is based on the awareness that the study of social phenomena and, in general, of cultural processes requires transversal skills that involve both the human and social sciences but also the quantitative methods of computer science and mathematical-statistical sciences. In the era of "big data", data not only constitute the fundamental tool to support decision-making processes but are the ultimate effect of a process of profound individual and collective transformation.
The process of data collection and management changes, the technologies supporting the data life cycle evolve and new skills are developed for the valorization and contextualization of data. In this process, the data scientist represents the reference figure.
As also reiterated in the PNR 2021-2017 program and in line with the European objectives of transition towards industry 5.0, "it is essential to promote harmonization between research policies in their implementation at various levels (European, national, regional) and in different sectors because on the one hand the boundary between the different disciplines is increasingly blurred and on the other the solution to the complex problems that the future poses to us increasingly requires a systematic interaction between different knowledge and skills
(interdisciplinarity), different areas of work (intersectorality) and different levels of implementation (interinstitutionality)". The course defines a data scientist figure with specialized skills in computational methods and tools for implementing data analysis.

All students in Data Science for Human and Social Sciences will acquire specific skills in mathematical-statistical and computer science methodologies, but also qualitative analysis tools for social and cognitive processes. The course aims to train professionals able to manage, as a whole, the process of "data analysis", starting from the epistemology of the data, the computational aspects related to "big data", statistical analyses for extracting information and interpreting the results in context analyses. The professional profiles identified are those of Data Scientist, Data Manager, Data Analyst with particular skills in the processing and interpretation of social data. The professional functions performed by graduates in Data Science for the Human and Social Sciences are to analyze, present and predict fundamental trends in data flows, identify the software tools needed to process large amounts of data, coordinate the collection and publication of open data in the public and private sectors and integrate data science methodologies within organizational processes. This profile can find its place both within companies and public and private administrations, including scientific and technological research bodies or institutes as can be seen from the ideas that emerged from the consultation of the parties.

To access the LM-Data course in Data Science in Human and Social Sciences, it is necessary to have obtained a degree in one of the degree classes ex DM 270/04, ex DM 509/99 or in other previous systems, or another qualification obtained abroad recognized as suitable. It is also required to have the following curricular requirement: having obtained at least 16 CFU as follows:

16 CFU in the Mathematical-Statistical field (MAT/*, SECS-S/*, ING-INF/05, INF/01);

or

8 CFU in the Mathematical-Statistical field (MAT/*, SECS-S/*, ING-INF/05, INF/01) and 8 CFU in methodological courses in the sectors (SPS/07, M-PSI/03, SPS/04).

Those who possess the above-mentioned requirements will be able to access the LM-DATA course after
passing an individual interview with a special commission, which will ascertain the adequacy of
their preparation and their study curriculum, as well as their knowledge of the English language equal to
level B2. The methods of evaluation and the composition and functioning of the Commission
are defined in the Course Teaching Regulations.

After passing all the tests of the training activities included in the study plan, the student, regardless of the number of years of enrollment at the University, is admitted to take the final exam,
To obtain the master's degree, the student must present a thesis developed by the student in an original way under the guidance of a supervisor belonging to the scientific disciplinary sector or responsible for a course present in the student's curricular path. The thesis can be a compilation or research and can be accompanied by a digital product
that is an integral part of the final work which consists of the preparation and subsequent presentation, with discussion, of a written paper (degree thesis) on a topic agreed with the supervisor.

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