Objectives/Vision
The ICT Solutions Architect track is designed to train professionals capable of designing, implementing, and assessing complex ICT systems that integrate heterogeneous software services and infrastructures. These systems must not only work functionally but also meet rigorous requirements in terms of performance, scalability, security, and privacy. As modern ICT architectures span cloud platforms, mobile environments, distributed systems, and virtualized infrastructures, this track emphasizes the ability to master complexity across the entire technology stack.
The track combines a solid grounding in computer science—covering algorithms, programming, and software engineering—with advanced topics focused on system integration and infrastructure-aware design. Students learn to design complex systems, evaluate service- and cloud-based solutions, and apply DevOps principles. They also gain the skills to assess IT infrastructures—both physical and virtual—and verify non-functional requirements such as performance, dependability, and data security. The program highlights the importance of risk assessment, secure data management, and coordination in distributed environments, including peer-to-peer and blockchain-based systems.
Throughout the track, students benefit from a balanced approach that combines theoretical knowledge with applied skills. Courses such as Advanced Software Engineering, Distributed Algorithms, ICT Infrastructures, and Risk Assessment are complemented by elective options that allow for personalized specialization. The training culminates in a thesis project that typically engages students in solving real-world ICT design problems, often in collaboration with external companies or research partners.
Career opportunities
Career opportunities are extensive, as ICT Solutions Architect is one of the most in-demand profiles in both the public and private sectors. From traditional software vendors to cloud providers, telecom companies, and IoT-driven startups, the need for professionals who can integrate, validate, and innovate complex systems is growing rapidly. The Department of Computer Science maintains strong ties with leading global companies and national players, offering students opportunities for internships and project collaborations. The program also provides excellent preparation for those wishing to pursue a Ph.D. in Computer Science or related fields.
Graduates are well prepared for careers in top-tier tech companies (both national and international) or to pursue Ph.D. programs in Computer Science or related fields.
Study plan
The plan of studies is composed by two courses on the infrastructure layers (“ICT infrastructures” and “Mobile and cyber-physical systems”), two courses on the software layers (“Advanced software engineering” and “Advanced programming”), and two courses on security aspects (“ICT risk assessment” and “Peer to peer systems and blockchains”).
First year
Semester 1 |
CFU |
Semester 2 |
CFU |
| Advanced programming | 9 | Peer to peer systems and blockchains | 9 |
| Algorithm engineering | 9 | Mobile and cyber-physical systems | 9 |
| ICT risk assessment | 9 | ICT infrastructures | 6 |
| Group: ICT electives 9 cfu | 9 | ||
| 27 | 33 |
Second year
Semester 3 |
CFU |
Semester 4 |
CFU |
| Advanced software engineering | 9 | Group: ICT elective 6 CFU | 6 |
| Group: ICT elective 6 CFU | 6 | ||
| Group: ICT elective 6 CFU | 6 | ||
| Group: free choice | 9 | Thesis | 24 |
| 30 | 30 |
Group: ICT electives (9 CFU)
Data mining (Sem. 1)
Generative and deep learning (Sem. 2) (*)
Language-based tecnology for security (Sem. 2)
Machine learning (Sem. 1)
Parallel and distributed systems: paradigms and models (Sem. 2)
Software Verification: Principles and Techniques (not offered in the a.y. 25/26 – ex-Software validation and verification, offered instead in the a.y. 25/26) (Sem. 1) (*)
Group: ICT electives (6 CFU)
Accelerated Computing (Sem. 1) (*)
Algorithmic Game Theory (Sem. 2)
Business Process Modeling (Sem. 1)
Competitive programming and contests (Sem. 1) (*)
Distributed Algorithms (Sem. 1) (*)
Information retrieval (Sem. 1)
Introduction to Quantum Computing (Sem. 2)
Laboratory on ICT Startup Building (Sem. 2)
Scalable Distributed Computing (Sem. 1)
Scientific and large data visualization (Sem. 2)
(*) Courses offered only to new enrolled students.
Students enrolled before the academic year 2025/2026 can refer to the previous study plan (see the following linked document)