Challenges in operating system courses, such as inefficient evaluation of practical skills, delays in debugging, and a lack of personalized instruction, were addressed by an AI-driven platform developed in this study. The platform enables precise teaching and efficient debugging through real-time compliance verification, intelligent error diagnosis, and dynamic generation of personalized tasks. By utilizing full-process behavioral data for multidimensional competency assessment, the platform was deployed in over 20 classes. It effectively reduced instructors’ workload while enhancing students’ theoretical knowledge and practical understanding, promoting efficient, personalized, and intelligent transformation in operating system training.