Considering the swift evolution of technology driven by advances in computer science, a pivotal inquiry facing the pedagogy of the discipline is: “Which core principles enable one to effectively navigate the constantly shifting landscape of the field?”

In this context, the undergraduate curriculum at Krea University aims to provide a comprehensive introduction to the foundations of the discipline and its connection with technological advancements. Throughout the curriculum, we expect students to learn how to tackle computational challenges and develop insights into the conceptual principles underlying programming and computing paradigms, such as machine learning. Students will gain a solid grounding in key mathematical principles and techniques that underlie modern computing and domains like artificial intelligence. This will be complemented by a systems-level perspective through courses covering key concepts in computer organisation, operating systems and networks. The curriculum also intends to enhance students’ understanding of how computing plays out in real life through a range of interdisciplinary courses, helping them see how computing is embedded in various domains.

The required courses in Krea are designed to provide a rigorous introduction to the conceptual core and skills that every computer science major should possess in the contemporary era. These include the ability to write correct and efficient code, reason about code, grasp various layers of computer systems, and gain hands-on experience with systems programming. Students will also study the mathematical foundations of computer science, theoretical foundations, and contemporary computational paradigms such as machine learning and artificial intelligence. They will learn to deploy their understanding to deliver real-world projects.

In their final years, students have access to a range of electives to enable further exploration, either in depth or breadth, of computer science and interdisciplinary domains. Electives may include conventional computer science areas such as deep learning, complexity theory, and computer vision, as well as interdisciplinary fields such as computational music and quantum information. Some electives can be substituted with independent study courses, where students can undertake guided study in a domain of interest with a faculty member. Additionally, students have the option to engage in a capstone project to gain hands-on experience in research, develop ancillary skills including writing research reports, and communicate their findings effectively.