To provide guidance for students in choosing among the great variety of the available courses for the composition of the Study Plan T2A, the Council of the Study Programme has defined three reference Methodological Areas and nine specialized Tracks. Students are strongly advised to choose a precise methodological area, and a single track.

Specialized tracks, which can be built by adding further credits from Computer Science and Engineering courses, or from complementary subjects according to the student’s preference. Some courses are provided by the Doctor of Philosophy School, supplied by Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB); students can check the full list of such courses on the web site of the Doctorate at the DEIB.

 

 

 

 

Methodological Areas and Specialized Tracks

 

The Methodological Areas are the following: 

  • IT Management and Applications:  the area studies how information technology is used in the enterprises, and how it is applied in different areas.
  • Software Methodologies:  the area is oriented to topics concerning software analysis, design, and verification.
  • Hardware Architectures:  the area focuses on basic and advanced methodologies for the design and realization of computer architectures and applications, as well as techniques for analyzing and comparing different computer organizations. 

 

Specialized tracks, which can be built by adding further credits from Computer Science and Engineering courses, or from complementary subjects according to the student’s preference

Each track generally includes 10-15 cfu of courses from the TABB group and a Laboratory/Project of 5 cfu that is specialized for that given track (generally identified in the programme as Multidisciplinary Project).

Follow the links on the right to show the description of each track and the table of the related courses.

 

 

 

 

Interactive Applications

Bioinformatics and e-Health

Cybersecurity

Networked enterprises and services

Artificial Intelligence

Internet Engineering

Robotics and vision

Pervasive Systems

Big Data