Acquire basic knowledge on the fundamentals of AI and machine learning, and know how the theory has been developed. Understand the motivations for designing intelligent machines. Have a first experience of the possible fields of applications of AI systems and their broader implications. Understand and explain the concepts, principles, strengths and limitations of the main kinds of knowledge representation: the logic (symbolic) approach, Bayesian networks and the connectionist approach. Understand and apply some main algorithms for uninformed and heuristic search Understand and explain the main differences between the major kinds of machine learning problems Understand and explain some possible ethical and societal impacts of AI and machine learning Understand and apply some fundamental principles to design AI systems to be aligned with sustainable goals
Professore associato in epistemologia, logica e etica dell'intelligenza artificiale / Co-Responsabile corso di laurea in Data Science and Artificial Intelligence - Dipartimento tecnologie innovative