This paper introduces the course titled “Foundations and Applications of Large AI Models,” which is offered to all students across the university by the School of Computer Science and Technology. The course aims to provide a comprehensive understanding of the basic concepts, development history, core technological principles, and application cases of artificial intelligence (AI) and large models, while also addressing their ethical, legal, and societal impacts. The course content encompasses various aspects, including the underlying technologies of large models, language large models, text processing techniques, multimodal large models, image analysis technologies, stable diffusion large models, image generation techniques, applications in copywriting and cultural creativity, code generation, video generation, stock and housing price prediction, robotics, autonomous driving, and AI ethics. The teaching methods employed in this course include lecture-based instruction, case analysis, group discussions, interactive question-and-answer sessions, hands-on demonstrations, and project report-based learning. The assessment methods for the course consist of regular assignments and a final report, focusing on knowledge mastery, skill application, thinking cultivation, knowledge integration, analysis and application, and innovative thinking. Through this course, students will develop critical thinking skills, interdisciplinary integration abilities, and habits of continuous learning, preparing them well for future career development.