- Degree classification: Data Science (LM-Data).
- Programme structure: 2 alternative graduation paths in (i) data analysis and modelling, (ii) data-driven applications. Check the page graduation paths.
- Course Length: 2 years, since 2022/23.
- Terms of access: restricted, based on the ranking list drawn up according to the rules defined in the yearly invitation to apply (bando).
- Language: English
- Scheme of the annual programme of activities: check the calendar of all the activities.
- Place of Teaching: Catania.
- Director: Prof. Antonio Punzo
With its interdisciplinary vocation, the Course aims to develop in-depth knowledge with regards to:
a) structured and unstructured data collection, processing, compression, filing, security;
b) the most common programming languages for data analysis;
c) statistical learning and statistical analysis of data;
d) machine learning, neural computing and deep learning;
e) database design, also with reference the special features of "Big Data".
Graduates will be able to:
a) actively communicate with experts in various fields by providing focused and competent data analysis for every application, such as in scientific, technological or business fields;
b) design processes of collection, clearing, filing and efficient, safe use of data; also with reference to “Big Data”;
c) correctly and accurately communicate results of data analysis performed by means of advanced tools, such as programming languages, graphic and interactive platforms.
The course is structured into two different paths: have a look.
The graduates of the course will develop a specifically quantitative attitude to the analysis of scientific, economic, managerial, social and health phenomena. They will be able to work in interdisciplinary teams and discuss the results of data analysis with the end-users. They will be fully aware of the ethical principles involved in the collection, storage and use of personal data and information. A specific training function, during the Course, will address opportunities of collaboration and mentoring in companies or, more generally, in institutions and organizations, where data collection and analysis has a crucial role.