This is a 2-year graduate programme entirely taught in English, offered to both national and international students. The MSc in Computer and Automation Engineering aims at providing high-level competences for the design, management, development and innovation in the fields of advanced hardware and software architectures, and of control systems and robotics. In particular, the program is focused on human-machine interaction in a wide sense, spanning topics such as artificial intelligence, machine learning, high performance processing of massive data collections, human-robot interfaces, and systems for production automation. The program provides advanced competences in the area of computer and automation engineering, with courses covering topics such as: engineering tools for the design, evaluation and programming of high-performance and parallel computer architectures; artificial intelligence and machine learning techniques needed to implement intelligent systems; design patterns and methodologies for the implementation of complex software systems and distributed applications; advanced interfaces for the interaction with robots, such as vision systems and haptic interfaces; techniques for the analysis and design of discrete event systems and of multivariable and nonlinear control systems, with applications to robot control, path planning and multi-agent systems; mathematical and algorithmic tools for optimization over networks. The students can complete the program by focusing either on information systems design or on robotics and automation. In particular, the students can choose courses covering the design issues for advanced database systems, such as search engine technologies and information retrieval; the theory of formal languages and the technological aspects of language parsers and natural language processing tools; the applications of bioinformatics and information systems for biological databases; the algorithms for image processing; the techniques for the modelling, analysis and simulation of complex dynamic systems; the principles of estimation theory applied to system identification and filtering; the modern paradigms of uncertainty representation and the main techniques for analysis and design of uncertain systems; the competences for the design of advanced sensor systems.