Second cycle degree in

Computer engineering (2020/2021)

Class: LM-32 - Computer systems engineering

Class LM-32 - Computer systems engineering
Duration 2 years
Branch Padova
Language English
Tuition fees and scholarships
President of the Course of Study CARLO FERRARI
Access Open access with admission requirements

Next Call for applications (international students):

  • 7th April-7th June: non-EU applicants residing outside Italy
  • 7th April-7th July: EU applicants or equivalent

An interdisciplinary course in English, offering a wide spectrum of knowledge suitable to interpret, describe and solve the problems of computer engineering in an innovative way. You will approach theoretical and application topics such as computation theory, algorithmics, operating and distributed systems, computer systems architectures, computer networks and databases, with a focus on artificial intelligence and robotics, big data and web sciences. The flexibility of the study paths and the great variety of the training opportunities, combined with practical experiences such as internships in companies, will allow you to customise your learning experience. The employment opportunities are wide and varied, from the automation of services in public and private entities to the applications of robotics, industry 4.0 and life sciences.

Curricula
ARTIFICIAL INTELLIGENCE AND ROBOTICS; BIOINFORMATICS; HIGH PERFORMANCE AND BIG DATA COMPUTING; WEB INFORMATION AND DATA ENGINEERING

  Deepening

Characteristics and objectives

The master degree in Computer Engineering forms a professional, second-level engineer, benefiting from the cutting-edge research activities expressed by the Department of Information Engineering of the University of Padua. The professional profile of the graduate student is therefore of high profile and able to use a wide range of knowledge to interpret, describe and solve in an innovative way problems of computer engineering, which require a strong in-depth analysis together with an interdisciplinary approach. The specific training in Computer Engineering concerns all the foundamental theoretical and applicative topics, such as computational theory, algorithmics, operating systems and distributed systems, modern computing system architectures, computer networks, databases. Furthermore, the most recent advances in artificial intelligence and robotics, in big data processing, in the web sciences are presented. The flexibility allowed by the various proposed study paths allows the choice between courses also on other specialized topics of considerable applicative impact, within a varied offer that enhances all the specific areas of competence of the teachers of the Department (bioinformatics, computer music, compilers etc.). Training activities that concern the corporate organization and modern telecommunications are also planned. The course of study concludes with the development of a master thesis (with mentor) on activities related either to departmental research or to company internships.

Occupational opportunities

The pervasive dissemination of information processing tools in every sector of activity makes the set of employment areas of the master computer engineer extremely broad. Among these are of particular relevance: the automation of services in public and private institutions; distributed systems and applications, especially multimedia ones; embedded processing systems, systems for the analysis of large amounts of data and machine learning systems, applications related to robotics and industry 4.0 and those related to life sciences. In general, these areas are characterized by the need to deal with complex information systems in multidisciplinary contexts.

Curricula
ARTIFICIAL INTELLIGENCE AND ROBOTICS; BIOINFORMATICS; HIGH PERFORMANCE AND BIG DATA COMPUTING; WEB INFORMATION AND DATA ENGINEERING

  Teaching list

I Anno STRUCTURAL BIOINFORMATICS [ DAMIANO PIOVESAN ] BIG DATA COMPUTING [ FRANCESCO SILVESTRI ] BIG DATA COMPUTING [ ANDREA ALBERTO PIETRACAPRINA ] COGNITIVE SERVICES AUTOMATA, LANGUAGES AND COMPUTATION [ GIORGIO SATTA ] HUMAN DATA ANALYTICS [ MICHELE ROSSI ] WIRELESS NETWORKS [ MICHELE ROSSI ] DIGITAL FORENSICS [ SIMONE MILANI ] NEUROROBOTICS AND NEUROREHABILITATION [ LUCA TONIN ] IMAGING FOR NEUROSCIENCE [ ALESSANDRA BERTOLDO ] QUALITY ENGINEERING [ MATTEO BERTOCCO ] CRYPTOGRAPHY [ ALESSANDRO LANGUASCO ] CRYPTOGRAPHY [ ALESSANDRO LANGUASCO ] OPERATIONS RESEARCH 1 [ MATTEO FISCHETTI ] INFERENTIAL STATISTICS ITALIAN LANGUAGE [ SIMONE CARMIGNATO ] ENGLISH LANGUAGE B2 (PRODUCTIVE SKILLS) [ SIMONE CARMIGNATO ] ROBOTICS AND CONTROL 1 [ RUGGERO CARLI ] BIOINFORMATICS [ MATTEO COMIN ] WEB APPLICATIONS [ NICOLA FERRO ] DEEP LEARNING PARALLEL COMPUTING [ GIANFRANCO BILARDI ] WEB APPLICATIONS [ NICOLA FERRO ] FOUNDATIONS OF DATABASES [ NICOLA FERRO ] SOFTWARE PLATFORMS COMPUTER NETWORKS [ NICOLA ZINGIRIAN ] SEARCH ENGINES [ NICOLA FERRO ] COMPUTER VISION [ STEFANO GHIDONI ] ARTIFICIAL INTELLIGENCE [ MARIA SILVIA PINI ] DEEP LEARNING MACHINE LEARNING [ FABIO VANDIN ] FINAL PROJECT

Entry requirements

  • A minimum three-year undergraduate degree (or equivalent) in Engineering or related fields (e.g. Mathematics) is required, with proven skills in Information Engineering, Physics and Mathematics
  • English language: B2 level (CEFR)

(The programme is to be approved)