The Master's Degree Programme (LM-23) in "Intelligent Civil Infrastructures Engineering" represents an innovative and unique initiative on both national and international levels. Delivered entirely in English and mainly through distance learning mode, it aims to educate a new interdisciplinary professional figure capable of managing the entire life cycle of civil infrastructures from a digital and sustainable perspective.

Stemming from the collaboration among the Departments of Civil, Environmental and Architectural Engineering (ICEA, the proposing department), Economics and Management "Marco Fanno" (DSEA), and Management and Engineering (DTG), the training programme integrates advanced engineering competences with economic, managerial, and organisational knowledge.

In addition to the core disciplines of Civil Engineering, the Master Programme covers and investigates topics such as structural health monitoring, big data analysis, artificial intelligence, digital twins development, and optimisation strategies, applied to the predictive management and maintenance of "intelligent" civil infrastructures. The curriculum includes courses on structural monitoring, big data analytics, artificial intelligence, BIM and GIS modelling, multi-objective optimisation, and decision support systems, as well as economic, business, financial, organisational, and management courses.

The teaching approach includes project works, interactive simulations, case studies, and online collaborative activities. The Master Programme, delivered mainly through distance learning mode, will implement cutting-edge educational methodologies designed to create a dynamic, interactive, and personalised learning experience. In addition to video lectures, digital resources such as Massive Open Online Courses (MOOCs), e-tivities, and interactive simulations will be widely used.

The e-tivities, specifically designed by lecturers, will enable students to apply the acquired knowledge through practical exercises, problem-solving, and collaborative group projects. Continuous support from tutors and feedback from instructors and lecturers will guide the students' learning process. Self-assessment tools such as multiple-choice or open-ended online tests will be provided at the end of each teaching unit. These tests will enable students to independently verify their level of understanding and identify any potential gap to be filled before the interim and final assessment exams.

The integration of lectures, interactive digital resources, online collaborative activities, self-assessment tools, and live sessions with instructors and lecturers will create a flexible yet structured, engaging and personalized learning path, respecting the specific needs of each student. This innovative approach, combined with practical experience in laboratories, both in-person and online, will ensure an effective acquisition of the multidisciplinary skills envisaged by the Programme.

Further educational opportunities and the development of the Master's thesis can be also planned in collaboration with companies, public and private institutions, engineering firms, and other stakeholders operating in the field of intelligent civil infrastructures. These activities will be organised in close cooperation with the stakeholders consulted during the design phase of the Master Programme.

The Master Programme employs innovative teaching methodologies, such as online collaborative activities, interactive simulations, project work, and real case studies, to ensure a dynamic and profession-oriented learning experience. The Master Program is structured into four semesters, delivered mainly through distance learning mode: 5-10% of the ECTS credits will be taught in person, ordinarily at the end of the second semester of each academic year. This choice is motivated by several factors: fostering direct teacher-student and peer interaction, contributing to the development of soft skills, and facilitating the transformation of theoretical knowledge into practical competencies.

Laboratory experiences constitute another key element of the in-person component. These sessions will take place in the laboratories of the Department of Civil, Environmental and Architectural Engineering, further enhanced by the 2023-2027 Departments of Excellence Project "SEI ICEA" (where SEI stands for Smart Engineering Infrastructures).

Thanks to its predominantly distance learning format, the Master Programme also aims to attract international students and professionals already employed in the sector, offering a flexible and inclusive high-profile educational experience.

Due to the international nature of the Programme and its delivery in English, a B2 level of English proficiency is required. Admission is therefore subject to an evaluation based on curricular requirements, prior competencies, and English language proficiency (B2 level).

Enrolment is limited to 100 students per year. Compared to the maximum limits established by law (specifically, DM 1835/2024) for Master's programmes delivered mainly online, this restriction is necessary due to the sustainability constraints imposed by physical and technological infrastructures (classrooms and laboratories), especially for the in-person activities which, although limited to 5-10% of the mandatory ECTS credits, are essential to the study experience.

These in-person activities are concentrated at the end of the second semester of each academic year to maximize the attendance of both EU and non-EU international students. Exceeding the enrolment limit would adversely affect the quality of laboratory learning experiences, due to the high number of required sessions. Similarly, a number of students exceeding the identified limit would likely reduce the learning quality in the use of advanced equipment acquired through the SEI ICEA Departments of Excellence Project (such as the Heavy Weight Deflectometer, the cDAQ-9185 multi-slot datalogger, and the FibrisTerre FTB 5020 interrogator).

Beyond these objective constraints, the overarching goal is to ensure a high-quality laboratory experience and to maintain interactions with academic and technical staff effective and as much personalised as possible.