Introductory Computer Vision Teaching Materials for VET Education

Abstract

Rapidly advancing development of artificial intelligence technologies, including deep learning techniques in the field of computer vision, has encouraged the need for early education about artificial intelligence in schools. This paper briefly describes the development of a computer vision curriculum, part of the AIM@VET (Artificial Intelligence Modules for Vocational Education and Training) EU project, targeting VET high-school students. The introductory materials presented in this paper are structured in three main teaching units (TUs), covering object detection and image segmentation. Each TU consists of eight tasks and a final assignment, totaling approximately 10 hours of classroom work. The course material, prepared in both traditional learning materials and in Python notebooks, combines theoretical concepts with practical coding exercises, with separate teacher and student versions. Materials rely on interactive tools and open-source libraries such as OpenCV, facilitating hands-on learning and immediate application of computer vision concepts.