在人工智能+高等教育背景下，探讨了大学物理智慧课程的建设与实施．研究以知识图谱为基础，采用线上线下相结合的混合式教学模式，旨在解决数字化和AI时代学生自主化与个性化学习需求，以及新工科建设对大学物理通识课程高阶能力培养的要求．通过构建智慧课程教学体系，实施问题导向、项目式、研讨式等教学策略，结合课程专属智能体优化学生学习体验，并利用大数据分析学生学习轨迹，推荐个性化学习路径．教学实践表明，智慧课程建设显著提升了学生的学习效果，近5个教学学期的期中和期末成绩总体提升显著．研究结论表明，基于知识图谱与AI技术的智慧课程建设与实施，能够有效提高教学效率和效果，为新时代高等教育改革提供了有益的实践参考．

 In the context of artificial intelligence and higher education, this study explores the construction and implementation of intelligent courses in university physics. The research is based on knowledge graphs and adopts a hybrid teaching mode that combines online and offline methods, aiming to address the autonomous and personalized learning needs of students in the digital and AI era, as well as the requirements of the new engineering construction for the cultivation of advanced abilities in university physics general courses. By constructing a intelligent course teaching system and implementing teaching strategies such as problem oriented, project-based, and seminar based, combined with course specific intelligent agents to optimize students learning experience, and using big data to analyze students learning trajectories, personalized learning paths are recommended. Teaching practice has shown that the construction of smart courses has significantly improved students learning effectiveness, the overall improvement in mid-term and final grades in the past five teaching semesters is significant. The research conclusion shows that the construction and implementation of intelligent courses based on knowledge map and AI technology can effectively improve teaching efficiency and effectiveness, providing useful practical references for higher education reform in the new era.