CODE 113557 ACADEMIC YEAR 2024/2025 CREDITS 1 cfu anno 1 FORMAZIONE ALLA CITTADINANZA 10790 () - GENOVA TEACHING LOCATION GENOVA SEMESTER Annual TEACHING MATERIALS AULAWEB OVERVIEW The RAISE Citizenship Training Digital Courses are carried out as part of the P4|Basic AI & Robotics Skills at University Level project that is developed in the Training program of RAISE Liguria. The project is aimed at students at all university courses, but is also open to interested citizens, to increase awareness and autonomy in the use of advanced digital skills. At the end of the course an open badge will be issued to everyone and, to Unige students, also 1 CFU. The acquired CFU will result as an additional CFU (free) in the Supplement Diploma. The CFU can also be recognised by the study course as curricular CFU, mainly as other activities, where they are considered important for the achievement of the stated educational goals: in this case, the student must request it to their One-Stop Shop via mail, attaching ID. The study course will decide whether to accept the request and vary the study plan. AIMS AND CONTENT LEARNING OUTCOMES The goal of the training courses on the topics of AI and Robotics is to increase the level of awareness and boost the ability to use advanced digital skills, ensuring, regardless of the sector of specialization, the acquisition of sensitivity, culture and basic skills in Artificial Intelligence (AI) and Robotics. AIMS AND LEARNING OUTCOMES Base level course. Acquiring the basic theoretical knowledge of seismic engineering, the relevant techniques of the damage and images for its rating. PREREQUISITES None TEACHING METHODS Teaching is provided through interactive videos on the platform RAISE Aulaweb that can be followed autonomously and in asynchronous mode. The Course has a total duration of 25 hours, divided into modules of about 30 minutes. The teaching, designed by experienced teachers aided by educational innovation experts, is divided into: Distributed didactic (4 hours) Quizzes, games, and exercises (4 hours) Self-learning: reading and use of in-depth materials such as articles, videos, sites, etc. recommended by the teacher (17 hours). At the end of the course, a questionnaire will be available to determine the degree of satisfaction of the course. The training courses will be accessible without limitation. SYLLABUS/CONTENT Basic principles on seismic risk Seismic emergency phase analysis and damage detection Seismic response of existing buildings in ordinary and monumental masonry and their vulnerability Use of drones and Lidar technologies for seismic damage imaging Automatic interpretation of damage from images: framing of techniques and examples of applications Machine learning tools to support seismic risk reduction: basic principles of ML techniques + applications Use of the theoretical knowledge acquired for the analysis of practical cases and real problems related to seismic risk TEACHERS AND EXAM BOARD SERENA CATTARI BIANCA FEDERICI Ricevimento: By appointment, by calling (+39) 010 335 2421 or sending an e-mail (bianca.federici at unige.it) or a message on Teams Exam Board SERENA CATTARI (President) SIMONE BARANI BIANCA FEDERICI (President Substitute) LESSONS Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION Final skills test on the platform RAISE Aulaweb. Exam schedule Data appello Orario Luogo Degree type Note 04/03/2025 09:00 GENOVA Registrazione 30/09/2025 09:00 GENOVA Registrazione FURTHER INFORMATION All course and teaching details are available on the specif platform RAISE Aulaweb of the course. Upon passing the final verification, once the satisfaction questionnaire is completed, you get an Open Badge, which certifies the acquisition of the Training to citizenship competence. Unige students wanting to obtain the open badge and view the CFU in their career must include the citizenship training course with its code in their study plan, at the page formazione alla cittadinanza. The CFU and the Open Badge will be available only after the registration of the final verification is done by the teacher in charge of the course. That's all for now... Sign up: Machine Learning and Image-based procedures for seisimic risk reduction Contact us: formazione.raise@unige.it Agenda 2030 - Sustainable Development Goals Quality education Decent work and economic growth Industry, innovation and infrastructure Sustainable cities and communities