Master in Computing for Data Science

We live in a digital society. Human and automated activities continuously generate data, storing them in digital format. These data come from everywhere: enterprise information systems, social media, wearable equipment, and many more.

Data are like crude oil: unrefined, they are useless.

In our English-taught programme in Computing for Data Science, we teach you how to become a computational data scientist, i.e. a computer scientist specialised in the development of next-generation information systems.

Data science sits at the interface between computer science, mathematics, and application domains. Our study programme covers all these areas: computer science and IT methods for managing and engineering big and complex data, mathematical tools for data interpretation and analysis, artificial intelligence techniques to extract insights from data and support decision makers, and aspects of human-computer interaction. You will participate in cutting-edge research, and apply your skills to real data from actual application domains, such as business information systems, travel and tourism, bioinformatics, healthcare, internet of things, industry 4.0, agriculture, and many more.

For your final thesis you will collaborate on research projects with major industries - such as IBM, Oracle, Siemens, and with leading research institutions, such as TU Wien, TU München and Politecnico di Milano.

Career opportunities

Graduates enter the labour market as Machine Learning Engineers and Data Architects, key roles in the development of IT solutions for data science.

Machine Learning Engineers are sought after in all those business and organisational contexts, by no means limited to IT, where it is crucial to analyse, interpret and extract knowledge from big data and complex, heterogeneous datasets.

Data Architects hold technical and coordinating roles for data management within companies and organisations operating in the IT sector, or with a complex network of IT systems dependent on heterogeneous data sources.

Possible fields of employment include the sectors of finance, retail, e-commerce, marketing, Industry 4.0, public administration, but also applied sciences such as physics, biology, medicine, life sciences and environmental sciences. This also extends to scientific institutes, laboratories and universities.

Structure of the course

Students can choose between two curricula:

• Machine Learning is oriented toward data-driven Artificial Intelligence methods and, in particular, Machine Learning methods for data analysis, including the principles and methods for data exploration, for interpretation and visualization of the results of such analysis, and more generally, for the extraction of knowledge from data to inform and guide decision-making processes. Students can customise their study plan by choosing five optional courses in addition to the compulsory ones.
• Artificial Intelligence for Data Management is focused primarily on data management and on the techniques and methodologies specific to computer science and artificial intelligence for building IT architectures, infrastructures, on systems for maintaining, integrating, and curating complex and heterogeneous data, as well as for supporting the subsequent analysis for decision-making processes. Students can customise their study plan by choosing five optional courses in addition to the compulsory ones.

• Aula internazionale
• Docenti internazionali
• Lezioni in lingua straniera 100%
• Tirocinio formativo all’estero
• Tirocinio formativo presso aziende internazionali

Frequentare questo corso ha un costo di € 1200 Esente IVA.

L’Ufficio per il Diritto allo Studio universitario della Provincia Autonoma di Bolzano è l’ufficio competente per posti alloggio negli studentati e borse di studio. Per informazioni puoi rivolgerti all’Ufficio provinciale o ai collaboratori dell'Associazione studenti universitari sudtirolesi.