Research on AI-Enabled Intelligent Innovation of Courses: Taking the Probability Theory Course as an Example

This article focuses on the research of intelligent teaching in the context of artificial intelligence, taking the course of Probability Theory and Mathematical Statistics as the research object. By analyzing the problems existing in the traditional teaching mode, such as complex and abstract theories, fragmented knowledge, single learning paths, and low student participation, an intelligent teaching plan based on AI is proposed. At the same time, by leveraging the Chaoxing platform to structure the course resources, a multi-dimensional knowledge graph system covering core concepts, theorems and formulas, as well as practical application scenarios is established. Moreover, relying on the Learning Pass platform, students' learning situations are analyzed to dynamically grasp their learning status. This research deeply integrates teaching and learning. By integrating online resources and exploring relevant practical cases, it stimulates students' interest in learning and guides them to study independently. The research results show that AI-based intelligent teaching can significantly enhance students' overall effectiveness and autonomous learning ability, and improve teachers' teaching efficiency, providing practical and feasible reference basis and support for the subsequent intelligent teaching reform in science and engineering.