Traditional teaching of computer network courses faces problems such as the disconnection between theory and practice, insufficient cultivation of students’ higher-order thinking abilities, and the lag of teaching resource updates behind technological development. These issues result in students having shortcomings in mastering core skills such as network protocol analysis and troubleshooting, making it difficult for them to meet the demand for compound technical talents in the digital transformation of industries. Based on this, this paper deeply explores the significance and strategies of researching the teaching mode of computer network courses based on the concept of deep learning. It aims to improve students’ ability to analyze complex network scenarios through strategies including constructing a “three-dimensional integrated” teaching objective system, implementing problem chain-driven hybrid teaching, creating an intelligent learning environment integrating virtual and real elements, establishing a “dual-tutor system” project-based teaching mechanism, building a diversified dynamic evaluation system, and promoting the iteration of curriculum resources through “integration of production and education.” This study provides valuable references for the teaching reform of similar courses.