{"id":47496,"date":"2025-03-13T14:48:20","date_gmt":"2025-03-13T13:48:20","guid":{"rendered":"https:\/\/eunice-university.eu\/?post_type=courses&p=47496"},"modified":"2025-06-05T15:04:26","modified_gmt":"2025-06-05T13:04:26","slug":"applications-of-artificial-intelligence-summer-school","status":"publish","type":"courses","link":"https:\/\/eunice-university.eu\/pl\/course\/applications-of-artificial-intelligence-summer-school\/","title":{"rendered":"Applications of Artificial Intelligence – Summer School"},"featured_media":47592,"parent":0,"template":"","course_studylvl":[1830,1831],"course_category":[778],"teaching":[447],"course_tag":[1110,1062,1515,474,3796,2552],"branch":[552,550],"class_list":["post-47496","courses","type-courses","status-publish","has-post-thumbnail","course_studylvl-master","course_studylvl-phd","course_category-1-to-3-ects-credits","teaching-onsite","course_tag-ai","course_tag-artificial-intelligence","course_tag-blended-intensive-programme","course_tag-engineering","course_tag-metaheuristics","course_tag-summer-school","branch-engineering-energy-transport-mobility-environment","branch-sustainable-development"],"acf":{"description":"The \"Applications of Artificial Intelligence\" course is a summer school where students will discover, understand, and use the different AI techniques: logic, agents, machine learning, deep learning, and generative AI. This programme enables students to explore these AI techniques through both theoretical presentations and practical applications. An added value of this course is its multiculturalism and multidisciplinarity: it will be taught by researchers from 5 different EUNICE universities and attended by students from across Europe.","programme":"\"Course<\/a>\r\n\r\nThe online part of the \"Applications of Artificial Intelligence\" course will take place in early June 2025 via EUNICE Moodle platform. The onsite part will be held in Santander, Spain, from 23 to 27 June.\r\n

Course units:<\/h3>\r\n1. Overview of Artificial Intelligence: from past to present\u00a0 |\u00a0 Prof. Emmanuel Adam - Universit\u00e9 Polytechnique Hauts-de-France (France)\r\n2. Overview of distributed Artificial Intelligence: agents\u00a0 |\u00a0 Prof. Emmanuel Adam - Universit\u00e9 Polytechnique Hauts-de-France (France)\r\n3. Agent-based model for crowd simulation\u00a0<\/em> |\u00a0 Prof. Mario F. Pavone - University of Catania (Italy)\r\n4. Deep learning for meteorological and climate applications\u00a0 |\u00a0 Prof. Jos\u00e9 Gonz\u00e1lez-Abad - University of Cantabria (Spain)\r\n5. From exact solvers to metaheuristics\u00a0 |\u00a0 Prof. Sara P\u00e9rez Carabaza\u00a0- University of Cantabria (Spain)\r\n6. Generative Artificial Intelligence: this is just the beginning!\u00a0 |\u00a0 Prof. Diego Garc\u00eda Saiz\u00a0- University of Cantabria (Spain)\r\n7. Evolutionary design of 3D agents: applications\u00a0 |\u00a0 Prof. Konrad Miazga<\/span> - Poznan University of Technology (Poland)\r\n8. Evolutionary design of 3D agents: experiments\u00a0<\/em> |\u00a0 Prof. Konrad Miazga<\/span> - Poznan University of Technology (Poland)\r\n9. Learning through physiological signals: from sensors for data acquisition to data processing for knowledge discovery\u00a0 |\u00a0 Prof. Raquel Sebastia\u00f5 - Polytechnic Institute of Viseu (Portugal)\r\n10. Learning and unlearning with foundation and generative models in AI-driven health applications\u00a0 | Prof. Concetto Spampinato - University of Catania (Italy)","prerequisites":"