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<\/h2>\n<\/h2>\nArtificial Intelligence (AI) is rapidly transforming our society through applications such as self-driving cars, personal assistants, surveillance systems, robotic manufacturing, machine translation, financial services, cybersecurity, web search, video games, image and signal analysis, machine vision, code analysis, and product recommendation systems. These systems employ AI techniques to interpret diverse types of data, enabling intelligent, adaptive, goal-oriented behavior.<\/span><\/p>\n This track covers modern AI methodologies, including self-learning systems trained on massive datasets and interacting intelligent agents that perform distributed reasoning and computation. Students explore the integration of sensors, algorithms, and human-computer interfaces, extending into large networks of smart devices.<\/span><\/p>\n The track offers a blend of theoretical instruction and practical labs, ensuring that each student masters the theoretical foundations and acquires hands-on experience. Core courses cover areas such as artificial intelligence fundamentals, machine learning, human language technologies, and intelligent systems for pattern recognition. Elective options have been expanded to allow personalized exploration of advanced AI areas, including continual learning, quantum computing, scalable systems, and algorithmic design.<\/span><\/p>\n By engaging with both foundational and cutting-edge topics, students are prepared to contribute to the evolving landscape of AI, addressing complex challenges and driving innovation across various domains.<\/span><\/p>\n 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.<\/span><\/p>\n The track has been recently updated to reflect the evolution of the field. It now includes:<\/span><\/p>\n The course <\/span>Smart Applications<\/span><\/i> has been transformed into an elective to offer greater flexibility.<\/span><\/p>\n Algorithm engineering (Sem. 1 ) 3D Geometric Modeling & Processing (Sem. 1) (*) Courses offered only to new enrolled students.<\/p>\n Students enrolled before the academic year 2025\/2026 may refer to the previous\u00a0 rules.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Objectives\/Vision Artificial Intelligence (AI) is rapidly transforming our society through applications such as self-driving cars, personal assistants, surveillance systems, robotic…<\/p>\nCareer opportunities<\/h2>\n
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First year<\/h3>\n
\n\n
\n \n Semester 1<\/h3>\n<\/td>\n
\n CFU<\/h3>\n<\/td>\n
\n Semester 2<\/h3>\n<\/td>\n
\n CFU<\/h3>\n<\/td>\n<\/tr>\n
\n Artificial intelligence fundamentals<\/td>\n 6<\/td>\n Generative and deep learning<\/td>\n 9<\/td>\n<\/tr>\n \n Computational mathematics for learning and data analysis<\/td>\n 9<\/td>\n Parallel and distributed systems: paradigms and models<\/td>\n 9<\/td>\n<\/tr>\n \n Machine learning<\/td>\n 9<\/td>\n Group: AI elective 9 CFU<\/a><\/td>\n 9<\/td>\n<\/tr>\n \n <\/td>\n <\/td>\n Group: AI elective 6 CFU<\/a><\/td>\n 6<\/td>\n<\/tr>\n \n <\/td>\n 24<\/b><\/td>\n <\/td>\n 33<\/b><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Second year<\/h3>\n
\n\n
\n \n Semester 3<\/h3>\n<\/td>\n
\n CFU<\/h3>\n<\/td>\n
\n Semester 4<\/h3>\n<\/td>\n
\n CFU<\/h3>\n<\/td>\n<\/tr>\n
\n Human language technologies (not offered in the a.y. 25\/26)<\/em><\/td>\n 9<\/td>\n Group: AI elective 6 CFU<\/a><\/td>\n 6<\/td>\n<\/tr>\n \n Computer vision <\/em>(not offered in the a.y. 25\/26)<\/em><\/td>\n 9<\/td>\n <\/td>\n <\/td>\n<\/tr>\n \n Group: AI elective 6 CFU<\/a><\/td>\n 6<\/td>\n <\/td>\n <\/td>\n<\/tr>\n \n Group: free choice<\/td>\n 9<\/td>\n Thesis<\/td>\n 24<\/td>\n<\/tr>\n \n <\/td>\n 33<\/b><\/td>\n <\/td>\n 30<\/b><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Group: AI electives (9 CFU)<\/h3>\n
\nAlgorithm design (Sem. 2) (*)
\nData mining (Sem. 1)
\nDigital Health lab (Sem. 2) (*)
\nMobile and cyber-physical systems (Sem. 2)<\/p>\nGroup: AI electives (6 CFU)<\/h3>\n
\nAccelerated Computing (Sem. 1)
\nAlgorithmic Game Theory (Sem. 2)
\nCompetitive programming and contest (Sem. 1) (*)
\nComputational models for complex systems (Sem. 2)
\nComputational neuroscience (Sem. 2)
\nContinual learning (Sem. 2)
\nInformation retrieval (Sem. 1)
\nIntroduction to Quantum Computing (Sem. 2)
\nLaboratory on ICT Startup Building (Sem. 1)
\nLearning on Graphs (Sem. 1) (not offered in the a.y. 25\/26<\/em>) (*)
\nRobotics (Sem. 2)
\nScalable Distributed Computing (Sem. 1) (*)
\nScientific and large data visualization (Sem. 2)
\nSemantic web (Sem. 1)
\nSmart applications (Sem. 1) (not offered in a.y. 25\/26 – Smart Applications, 9 cfu, is offered instead<\/em>)
\nSocial and ethical issues in computer technology (Sem. 2)<\/p>\n