Architecture
Architecture
1
Data Science has become essential in several areas, from the financial sector to computer and communications security, due to its importance in the analysis and interpretation of huge volumes of data. The interest of companies and organizations in various topics of Data Science and Engineering has been growing exponentially. Business recognizes the enormous economic and commercial value of information and its use as a differentiating element between competitors. Data Science thus supports strategic decisions and can even assist credit rating and algorithm-based stock exchange transactions.
• To train specialists with solid competences in a subset of the disciplines that integrate Data Science and
Engineering, qualified to address and solve a vast class of problems in data acquisition, management, and
processing and in extraction, analysis, and visualization of information.
• To enable students to integrate work teams, which are typically large and with some heterogeneity and
multidisciplinarity, including experts with different profiles of expertise.
• To engage students in research in Data Science and Engineering, giving them the ability to grasp the latest
advances and techniques and to update their knowledge throughout their professional lives.
• To familiarize students with problems and practical applications, in which techniques and methods of Data Science and Engineering are employed, whether in a business environment, services and industry, or scientific applications.
National Admission 2024/25
Grade of the last student admitted – 1st phase153.50Grade of the last student admitted – 2nd phase159.50
.