With the rapid development of computer network technology, all aspects of human life have begun to show a trend of networking and intelligence, and the education industry is no exception. This study wants to improve the quality of classroom teaching and student performance. Through demand analysis, this paper understands the teaching characteristics of software engineering and the shortcomings of the original teaching methods and develops a comprehensive network teaching system (TS). This article introduces the framework design of the system around screenshots, electronic whiteboards, and image compression schemes; starting from three aspects of teaching courseware, exercise library, and teaching practice, it illustrates the advantages of intelligent and personalized teaching. From the experimental data, it can be seen that the excellent performance rate (score>80) of students who study software engineering courses through the network TS after one semester is 75.56%, which is compared with the 46% excellent rate in the class using traditional methods. It can be seen that an intelligent and personalized network TS can play an excellent role in stimulating students’ enthusiasm for learning and improving students’ academic performance in practice.