Teaching Practice and Innovation in the Professional Master's Degree Program in Electronic Information at Peking University in the Era of Artificial Intelligence

In the era of transformative artificial intelligence (AI), professional Master's programs must navigate both technological breakthroughs and pedagogical shifts. This paper presents an innovative approach adopted by the College of Software and Microelectronics at Peking University to train Electronic Information Master's students through a multi-dimensional framework encompassing academic research, industry applications, and in-service capacity building. By transitioning from code-focused instruction to a higher-level AI toolchain paradigm, the curriculum leverages large-model technologies (e.g., GPT, Chat-GPT) to promote greater efficiency in problem-solving, project-based learning, and critical thinking. The New Engineering Experimental Class exemplifies how enterprises partner with academia to guide real-world project cycles under dual mentor-ship, thereby accelerating technology transfer and strengthening student competencies in both theory and practice. In parallel, a three- tiered engineering practice system-ranging from course-embedded labs to full-scale industrial internships-amplifies hands-on development and integrates rigorous assessments of engineering proficiency. Furthermore, by incorporating cross-disciplinary mentorships, AI-enhanced campus tools, and cutting-edge lectures on new engineering and data-driven domains, the program produces graduates who are well-positioned in algorithm development, system architecture, and technology management. These reforms demonstrate an effective means of aligning educational supply with market demand, empowering students to address the evolving challenges of AI -driven industries while championing ethical and sustainable practices. The paper concludes by discussing the program's adaptability for continued innovation amid AGI-frontier breakthroughs and digital transformation imperatives.