Development of a Mobility AI Education Platform and Its Application to First-Year Students

This study presents the design and implementation of an introductory educational platform for first-year university students to enhance their understanding and hands-on experience with artificial intelligence (AI) in the field of mobility.With the increasing demand for AI integration in autonomous vehicles and smart mobility systems, there is a critical need to introduce students to real-world AI applications from the early stages of their academic journey.The proposed platform consists of a stepby-step curriculum that includes Python programming basics, the use of generative AI tools (such as Google Colab and Roboflow), and hands-on model development using YOLO and NVIDIA's PilotNet.Students engage in project-based learning (PBL), selecting topics from an AI project bank closely aligned with industrial demands, such as autonomous driving, delivery robots, and smart surveillance systems.Practical exercises enable students to collect, annotate, and train datasets, culminating in building their own AI models.Evaluation of the program shows significant improvements in AI literacy, self-directed learning, and interest in major-related studies.Furthermore, the use of accessible tools and structured mentoring support lowered the entry barrier for students unfamiliar with AI.This education model demonstrates the feasibility and effectiveness of immersive, application-driven AI learning and provides a foundation for scalable, multi-year curriculum integration for fostering AI talent in the mobility sector.