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Research on Optimal Design of Online Education Course Recommendation System Based on Hybrid Recommendation Algorithm

In recent years, online education technology has developed rapidly, and the market scale of online education platform is growing. However, with the widespread application and development of this technology, the requirements of online education users are gradually becoming stricter. Personalized course recommendation system can greatly improve the satisfaction and learning efficiency of student users, making the education platform stand out from many competitors. Based on the analysis of the advantages and disadvantages of the existing learning resource recommendation system on the online education platform, this paper proposes a new learning resource recommendation model based on hybrid recommendation algorithm, which includes course recommendation submodule based on statistics and personalized course recommendation submodule based on professional training requirements. It can not only help users to find high-quality information that they are interested in, save users' time cost, but also effectively solve the problem of cold boot. This paper provides inspiration for the improvement of online education course recommendation system.