Features and Purpose
The Master of Science in Data Science degree program provides the student with the multidisciplinary knowledge and skills necessary for the effective declination of mathematical/informatics skills in the analysis of datasets that are not
necessarily heterogeneous and/or structured, achieving skills pertaining to disciplines such as: computer science, engineering, mathematics, statistics, management, law, humanities and physics.
The master's graduate will be able to develop methods and tools to manage and analyze Big Data, develop predictive and decision-making models, and use the extracted knowledge to support strategic-decision-making processes in various application areas and with particular reference.
These skills are attained through the study of analytical methods and tools pertaining to Probability theory, statistical-inferential analysis, statistical learning, and data optimization and selection techniques; methods proper to Computer Science, with emphasis on data cleaning/data analysis/data visualization and exploratory analysis techniques; Management tools for knowledge in the area of business management and organizational culture from the perspective of business intelligence; knowledge from the area of Law, with specific reference to knowledge of the principles and sources of Private Law and Public Law; methods of Philosophical-Social afference for the correct acquisition of the ethical-philosophical basis of the value of data.
In addition to traditional didactics, the course includes application-based training activities, for example by exploiting specific software in the field of machine learning, so as to enrich the student's skills in relation to the profiles of data analyst and data scientist.
Areas of Work
The Master's Degree Course in Data Science trains professionals with specific skills in the field of Data Science, with particular reference to the skills characterizing the profiles of the data analysts and data scientist. The data analyst holds roles of responsibility in the analysis of large masses of data within heterogeneous companies and organizations, e.g.: manufacturing industries, banking/insurance institutions, pharmaceutical companies, etc., with the objective of extracting and inferring new knowledge from the data/historical series held by the company in order to optimize its maintenance, programming, production and strategic-decision-making processes.
Data analysts are sought after in all business and organizational contexts where there is a need to analyze and extract value from complex masses of data. For these reasons, the data analyst position is also sought after by scientific institutes, laboratories and universities.
The Data Scientist engaged on projects related to the application and development of probabilistic/analytical models to extract properties from data, relationships between them, carry out their related study and design models in the predictive domain, including in relation to the production of new statistical/probabilistic algorithms to optimize business processes.
The peculiarities of the professional figure of the data scientist make him or her a particularly sought-after resource within study offices of companies/public/private institutions; research centers; companies/public/private institutions and in particular financial institutions, pharmaceutical companies, public utilities management, as well as in academia.
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