近年来，人工智能技术迅速发展，2024年诺贝尔物理学奖授予在人工神经网络与机器学习领域做出开创性贡献的科学家，进一步凸显了物理学与前沿科技之间的深刻关联.本文探索将神经网络技术引入物理课程的教学设计路径，旨在丰富教学内容，增强课程前沿性与科技关联性，激发学生学习兴趣，从而提升物理课程的教学质量与育人实效.本研究强调神经网络与物理知识体系的可结合性，为物理课程教学内容的创新与拓展提供了借鉴.

In recent years, artificial intelligence technology has developed rapidly. The 2024 Nobel Prize in Physics was awarded to scientists for their groundbreaking contributions in the fields of artificial neural networks and machine learning, further underscoring the deep connection between physics and cutting-edge technologies. This paper explores a teaching design that integrates neural network technology into physics courses, aiming to enrich course content, enhance the cutting-edge nature and technological relevance of the course, stimulate student interest, and ultimately improve the quality and effectiveness of physics courses. This study emphasizes the integration potential of neural networks with the physics knowledge system, providing a reference for the innovation and expansion of physics course content.