Abstract: To address the challenges in professional talent cultivation caused by the rapid iteration of autonomous driving technology and its high learning barriers, an online learning platform is developed for autonomous driving—the OnSite Learning Center. It aims to provide learners at different levels with a “zero-threshold” algorithm development environment, datasets, models, communication communities, resource-sharing platforms, and AI-assisted learning tools for autonomous driving, thereby facilitating rapid learning and algorithmic practice. Leveraging this platform, experimental teaching in autonomous driving combines theory with practice, integrates online and offline methods, bridges undergraduate and graduate education, and shifts from single-discipline instruction to interdisciplinary collaboration. The platform has already supported teaching in over 10 undergraduate and graduate courses across three colleges at Tongji University, serving more than 500 students and faculty members. Its online users span 30 provinces across China, with monthly active users exceeding 1,000 and page views surpassing 10,000. Currently, the platform is being promoted to universities nationwide through the China Society of Automotive Engineers. Teaching practices demonstrate that with this platform, students can engage in theoretical learning and algorithmic practice in autonomous driving, enhancing their independent learning, interdisciplinary knowledge integration, and practical innovation capabilities. This approach offers new insights for accelerating the cultivation of interdisciplinary talent in autonomous driving, particularly for training outstanding engineers.