English
ItalianoLearning Outcomes
The Master’s degree programme in Data Science offers an interdisciplinary approach gathering contributions from Engineering, Computer Science, Statistics, Economic and Organizational Sciences, as well as specific knowledge of the main Data Science application domains. In particular, the Master’s degree programme in Data Science offers the necessary professional knowledge for the development of the big data collection, management, processing and analysis technologies, and the resulting translation of these into key information for the knowledge and decision-making process within innovative business and social sectors.
A course of study in Data Science must meet the scientific and technological challenges related to the use of new global platforms for data storage and processing: personal, government and commercial data and their related application leave individually-owned systems for cloud-computing and cloud-storage systems with their related reliability, privacy and security problems.
The Master’s degree programme in Data Science aims at training new professionals who can contribute to increase the efficiency and reliability of public institutions, private companies and local administrations, with particular reference to open data and their use for the development of more efficient services for companies and citizens and for the optimization of resource management in urban contexts. The Master’s degree in Data Science also aims at training professional who can work in public and private agencies with the task of inserting big data in the processes of economic and social analysis.
The interdisciplinary approach of the Master’s degree programme in Data Science and its rigorous methodology make it suitable for students who hold a Bachelor’s degree in all fields of Information Engineering, Computer Science, Statistics, as well as in Economics, Mathematics and Physics.
In addition to specific field knowledge, theoretical and scientific aspects are also key parts of the course catalogue, as they are necessary to describe and interpret the problems found in application contexts where Data Science innovative methodologies are developed. They are related to devising, planning, implementing and managing complex big data management and analysis systems, but also to developing testing skills and acquiring fluency in English.
The final exam, consisting of a written dissertation, is a key element of students’ education/training, as graduands can apply the knowledge and methodologies acquired in industrial, scientific, social and economic analysis fields. The final exam proves the graduand’s expertise in the area, his/her skills in working autonomously and a good communication level.
The course of study is addressed to international students, thanks to the fact that it is taught in English. Moreover, the course of study is designed so as to be closely connected to the job market
The Master’s graduate in Data Science will also be adequately trained for both basic and applied research, both in universities and research centres and in corporate R&D departments, in Italy and abroad.
The course catalogue encompasses all multidisciplinary skills offered by the 4 Departments of the Faculty of Information Engineering, Informatics and Statistics (I3S), the Department of Statistical Sciences, the “Antonio Ruberti” Department of Computer, Automatic and Management Engineering, the Department of Computer Science and the Department of Information Engineering, Electronics and Telecommunications.
The programme regulations of the Master’s degree, according to the related provisions, will define the overall number of hours available to students for personal study and other individual learning activities.
The course of study
The course of study consists of a first set of credits in key academic disciplines which are compulsory for all students. Such disciplines are aimed at providing basic Statistics, Engineering, and IT knowledge needed for the collection, processing and organization of big data and for the development of the mathematical-statistic models useful for their analysis. Key activities also include group and individual laboratory activities, as well as projects.
Key activities will include at least one course in the field of Human, Social, Juridical and Economic Sciences.
The course of study encompasses some optional courses in the fields of computer technologies, organizational-corporate and statistical areas aimed at training a professional profile combining engineering and computer knowledge with statistics, management, economic and juridical skills. These skills need to be developed together with a thorough knowledge of the economic, social and organizational context where Data Science methodologies are applied.
The course of study will be completed by elective courses and courses from related academic disciplines.
Master’s graduates in Data Science are able to analyse and plan Data Science complex solutions, considering their impact in the application context, both from a technical and an organizational perspective. Master’s graduates are also trained to take into account the economic, social and ethical implications of the solutions they provide.
Autonomous judgement is acquired through individual and group study, laboratory and planning activities and the end-of-course project which is carried out in collaboration with companies or at university or industrial laboratories. The student’s skills to autonomously express judgement are assessed through individual written work submitted during single modules and the final exam.
Master’s graduates in Data Science will effectively interact with specialists from diverse application fields, so as to understand their specific needs during the implementation of the solutions required. Master’s graduates will describe solutions and technical aspects of their own field in a clear way. In particular, their skills allow them to train collaborators, coordinate project groups in industries, plan and lead training. Master’s graduates in Data Science are fluent in both spoken and written English, including technical terminology. In particular, the fact that the Master’s degree programme is taught in English aims to prepare students for professional interaction in English. Communication skills are acquired during the two-year programme through exchange of views and discussion taking place in several occasions: during workshops and events organised with representatives from the job market, project exhibitions and work on the final thesis. Group works also allow students to improve communication skills. The overall assessment of acquired skills is carried out during the final exam.
Master’s graduates in Data Science are able to autonomously acquire new, technical and specialised knowledge from the scientific literature of the field, both in relation to methodologies and also in diverse application fields which may differ from their training. Such skills are acquired through traditional didactic tools and individual and group laboratory activities.
Learning ability is assessed through written and oral exams and project activities. The final exam is another occasion to assess the graduand’s learning skills, through his/her autonomous work on the final thesis