With the rapid advancement of Internet of Things (IoT) technologies, there is an urgent need for universities to explore more effective teaching models in IoT engineering programs, particularly to address shortcomings in hands-on training and the disconnect between theoretical instruction and industry demands. Very-Large-Scale Integration (VLSI) technology, as one of the core components of IoT, plays a critical role in determining the performance and market competitiveness of IoT devices. The integration of VLSI design automation tools not only improves design efficiency but also provides intuitive and effective means for practical teaching. This study centers on CMOS semiconductor devices and constructs a radial knowledge framework encompassing “Device–Model–Circuit–System.” By employing LTSPICE, a professional-grade simulation tool, the instructional content is visualized, enabling students to develop a deeper understanding of complex circuit principles and device characteristics. In addition, real industrial-grade SPICE models and fabrication process parameters—such as the 45 nm silicon-on-insulator (SOI) technology—are introduced to strengthen the link between academic instruction and practical engineering applications. Moreover, this research incorporates emerging technologies such as artificial intelligence, deep learning, and autonomous driving into instructional case studies, effectively enhancing student engagement, interest, and innovation capacity in practice-based learning environments.