Teaching Units for a Computer Vision CourseKIRN, VASJA LEV (Avtor) Peer, Peter (Mentor) Emeršič, Žiga (Komentor) Computer visionPython notebookobject detectionsegmentationRapidly advancing development of artificial intelligence (AI) technologies, including deep learning techniques in the field of computer vision, has encouraged the need for early education about artificial intelligence in schools. This thesis details the development of a computer vision (CV) curriculum, part of the AIM@VET (Artificial Intelligence Modules for Vocational Education and Training) project, targeting VET high-school students. The thesis is structured into three main teaching units (TUs): fundamentals of object detection, deep learning models for object detection, and fundamentals of image segmentation. Each TU consists of eight tasks and a final assignment, totaling 30 hours of classroom work. The course material, designed in Python notebooks, combines theoretical concepts with practical coding exercises. Unique versions for teachers and students facilitate effective learning and teaching, even for those unfamiliar with the topics. This approach to digital education in CV leverages interactive tools and open-source libraries like OpenCV, facilitating hands-on learning and immediate application of CV concepts. Also discussed are instructional design, content selection, and the initial evaluation of feedback, emphasizing the evolving need for digital education in the field of AI and CV.20242024-01-09 11:05:00Diplomsko delo/naloga153473sl