【摘要】 该文基于研究生神经网络及其应用课程教学实践，提出科研反哺教学模式，以应对人工智能技术快速发展下传统教学滞后的问题。该模式从科研内容融入课程、项目驱动教学设计、双导师协同指导、多元化评价机制4个方面展开，注重将真实科研项目与产业案例引入课堂，提升课程的应用导向与实践深度。该文结合具体教学案例，系统阐述课程设计路径、教学方法创新与学生发展支持，旨在为人工智能类课程改革提供参考。更多还原

【Abstract】 This article is based on the teaching practice of graduate courses on neural networks and their applications, and proposes a research feedback teaching model to address the problem of traditional teaching lagging behind under the rapid development of artificial intelligence technology. This model is developed from four aspects: integrating scientific research content into the curriculum, project driven teaching design, dual mentor collaborative guidance, and diversified evaluation mechanism. It focuses on introducing real scientific research projects and industry cases into the classroom to enhance the application orientation and practical depth of the curriculum. This article combines specific teaching cases to systematically explain the curriculum design path, innovative teaching methods, and student development support, aiming to provide references for the reform of artificial intelligence courses.更多还原