The learning outcomes are achieved by couplinga solid theoretical, methodological and technological background, on the oneside, with strong and effective operating skills, on the other. Such skillsderive both from practical experiences in courses and from targeted projectactivities, which constitute an essential part of the study programme. Theprogramme aims to train professionals able to take part in all activitiesconcerning the development of complex computer systems, processes and servicesin the specific field of computer engineering and more generally in any othercontext in which information technologies play an important role. For thispurpose, the degree programme provides knowledge and competencies in a wide numberof subjects within an integrated framework – from programming languages andcomputational paradigms, to software design, computer systems architecture,advanced operating systems, information systems and big data, distributed andautonomous systems, computer networks and cloud computing, IT security,artificial intelligence, real-time processing and control systems – completedwith topics about the organisation, management and optimisation oftechnological innovation processes. The degree programme intentionallyleaves broad space for customisation: apart from the few mandatory courses inthe fields of operational and management research and optimisation oftechnological innovation processes, students have a wide choice of IT subjectsand application areas.
In each particular subject area, students can acquire both foundationaland methodological knowledge, as well as analytical and design competencies –yet maintaining all the flexibility needed to design their own path, in compliancewith the learning outcomes, both vertically or in a multidisciplinary, broader-spectrumapproach.
The main subject areas can be devised asfollows:
1) 'Industrial computing' area
Students focus primarily on subjects relating to computer and digitalsystems architecture, operating systems and real-time systems, as well as ITsecurity; they may also study topics relating to computer vision andoptimisation algorithms
2) 'Software systems engineering' area
Students focus primarily on subjects relating to software engineeringand languages, operating systems and IT security, as well as computer anddigital systems architecture
3) 'Artificial Intelligence' area
Students focus primarily on subjects relating to Artificial Intelligenceand the many forms of intelligent systems, languages and computational models,as well as data mining techniques and optimisation algorithms
4) 'Distributed systems' area
Students focus primarily on subjects relating to operating systems anddistributed systems, including infrastructure for cloud computing and big data,as well as the key topics of artificial intelligence and optimisationalgorithms; they may also investigate topics relating to computer architecture.
5) 'Information systems' area
Students focus primarily on subjects relating to the principles,technologies and systems for databases, big data and data mining, as well as ITsecurity; they may also investigate issues relating to optimisation algorithms
6) 'Mobile systems' area
Students focus primarily on subjects relatingto infrastructures for cloud computing and big data, distributed systems andparticularly on mobile systems, integrated with competences in IT security
7) 'Multimedia systems' area
Students focus primarily on subjects relating to database systems andtechnologies, big data and data mining, as well as the management of multimediadata, integrated with competencies in the field of cloud computinginfrastructures, computer vision and computer graphics.
The specific learning outcomes are achievedthrough a systematic approach, involving:
a) for each area, a set of course unitsfocusing on the specific topics
b) for each course unit, a project work (possiblychosen by the student) aiming to specifically develop a concrete case study whereto apply the acquired knowledge and skills
c) course units designed to be harmoniouslycombined according to the many possible choices, also through amultidisciplinary approach: this is why they are intentionally designed asself-contained entities, which require little or no prior knowledge.
