The Master's degree in Computer Engineering for Robotics and Smart Industry provides students with knowledge and skills typical of information engineering enabling them to identify, formulate, analyze and solve problems related to the design, integration, and management of industrial production systems. The course aims to train graduates with advanced skills in strategic and innovative sectors, such as industrial robotics, cyber-physical systems, information processing of large amounts of data, digital manufacturing. The application domain includes the use of information technology in the industrial environment to automate manufacturing processes.
The Master's program includes basic training, which deepens and extends the knowledge obtained in computer science and engineering Bachelor courses, providing the student with a set of tools suitable for tackling non-trivial problems in the industrial context, and a series of courses related to different professional paths. These teachings will provide state-of-the-art knowledge in dynamic systems, robotics, computational vision, machine learning and artificial intelligence, industrial plants, and advanced simulation and interaction techniques. Students will have the possibility of having practical training in specialized laboratories as well as internships in local companies.
Quality Assurance
The quality of a degree program is the extent to which it achieves its educational objectives and meets the quality requirements of the educational activities offered, which are determined in line with the needs and expectations of students and representatives of the world of work.
This program has adopted a teaching Quality Assurance system in line with the University’s quality assurance guidelines and based on the e ANVUR national quality assurance guidelines, by carrying out the following activities:
- periodic consultations with representatives of the world of work to assess the adequacy of the cultural and professional profiles offered in their courses;
- design of educational contents and planning of resources;
- organization of educational activities and teaching services;
- monitoring the effectiveness of teaching and planning measures to improve teaching and services;
- provision of complete and up-to-date information on its website, relating to the program (professional roles, expected learning outcomes, learning activities).
The above activities are scheduled and interrelated, based on the PDCA principles (Plan, Do, Check, Act).
In a Quality Assurance system, students play a fundamental role: each student can play their part by participating in the Quality Assurance groups of their degree program and in the Faculty-Student Joint Committees or, more simply, by taking part in the Student Survey on teaching, or questionnaires. It’s in this context that specific workshops for student representatives (‘Laboratori di rappresentanza attiva’) are periodically made available to students by the University and the University’s Quality Assurance Board.