Master in Computer Engineering

The University of Pavia stands as one of the world's oldest academic institutions, known for its strong emphasis on research and academic excellence. The university offers a wide range of undergraduate, graduate, and doctoral programs across various disciplines, including humanities, social sciences, natural sciences, engineering, and medicine. With a strong commitment to providing students with a comprehensive and intellectually stimulating learning environment, the University of Pavia continues to uphold its reputation as a leading institution for higher education. The University of Pavia's academic community is characterized by its distinguished faculty, innovative research initiatives, and state-of-the-art facilities. Students benefit from a dynamic educational experience that combines rigorous academic training with practical skills development, preparing them for successful careers in their chosen fields. The university's vibrant campus life, historical heritage, and strong ties to the local community contribute to a well-rounded and enriching academic journey for students from all walks of life.

Students can build a strong background with advanced competences in Information Technology and Automation through the Master’s Degree Course in Computer Engineering and they can focus their studying on the economical and management issues typical of firms and markets. At the end of the degree course, the graduate will be able to identify, analyse, formalize and solve main problems, even more complex ones, typical of computer and automation engineering with an innovative point of view when needed. They also will be able to build a professional and flexible career updated with the evolution of technology. The Computer Science and Multimedia curriculum includes Multiprocessor Architectures, Computer Networks, Performance Evaluation, Multimedia Systems and Technologies, Computer Vision and Human Computer Interaction. The Embedded and Control Systems curriculum ncludes Automation and Advanced Control Systems, Process Control and Control of Robotic Systems, Embedded and Real-time systems. The Data Science curriculum includes machine learning and deep learning techniques, data modelling and analysis (statistical learning and data analytics), Big Data in the geospatial, biomedical and financial fields.