MUR LM-18 class "Class of master's degrees in computer science"
The students' initial preparation is verified through the analysis of qualifications and/or the administration of an assessment test of the skills acquired.
- Course information (Course in brief, Requirements, Perspectives, Objectives, Expected results, Contacts)
- Study course regulations
The Master's Degree in Computer Science is designed for those who wish to acquire advanced skills in the most strategic areas of modern computing: High-Performance Systems, Cyber Security, Data Science, and Artificial Intelligence.
The program combines a solid theoretical foundation with applied and design activities, enabling students to develop skills that are immediately applicable to the world of work and research.
The program is divided into two tracks:
● High-Performance and Cyber Security Systems, for those who wish to specialize in advanced architectures, high-performance computing, and system and data protection;
● Applied Computer Science and Artificial Intelligence, for those who wish to delve deeper into data analysis, machine learning, and the development of intelligent solutions to complex problems.
Thanks to a wide range of courses and a high degree of flexibility in designing their curriculum, students can customize their study plan based on their interests and professional goals, updating it at the end of each semester.
The educational experience can be enriched through Erasmus+ programs, allowing students to study abroad and engage with international academic institutions. Finally, the internship and thesis offer a concrete opportunity to test themselves on innovative projects, develop autonomy and critical thinking, and build their professional profile, also in collaboration with companies and research centers.
Curricula
High-performance and Cyber Security Systems
The curriculum focuses on the design, development, and management of high-performance and secure computing systems, with particular attention to advanced architectures, distributed systems, and infrastructure and data protection.
The high-performance area is developed through courses dedicated to parallel and distributed computing, cloud and edge infrastructures, programming on heterogeneous architectures (such as GPUs), embedded and real-time systems, and interaction with the innermost layers of operating systems. The goal is to train professionals capable of designing and optimizing applications and infrastructures in computationally intensive contexts and with stringent efficiency and reliability constraints.
The Cyber Security component is a cornerstone of the program and comprehensively addresses topics such as network and system security, application protection, encryption and data protection, industrial and automotive security, as well as regulatory and risk management aspects. Security is addressed from both a theoretical perspective (models, protocols, algorithms) and a practical perspective (vulnerability analysis, secure development, critical infrastructure protection).
Graduates will be able to design, analyze, and manage complex IT systems, develop secure and high-performance software, and operate in industrial, scientific, and institutional contexts where reliability, scalability, and security are essential requirements.
Applied Computer Science and Artificial Intelligence
The curriculum focuses on the applications of computer science in algorithmic and artificial intelligence. The program is organized into groups of elective courses that allow students to develop a professional profile consistent with their interests, deepening their advanced skills in the leading fields of Artificial Intelligence, Data Science, Algorithmic Thinking, and Computer Graphics.
A key feature of this program is the dual skills required for data analysis and synthesis. Students will acquire solid skills in analyzing complex data, both textual and non-textual, using mathematical, algorithmic, and artificial intelligence methods. Students will also study methods for synthesizing text, images, and three-dimensional models, also based on both computational and generative AI methods. In support of these topics, attention will be paid to the regulatory, ethical, and social aspects of the technologies used.
Graduates will be able to develop models and software in industrial, scientific, and institutional contexts where data analysis and management are essential.
