This paper aims to study the design and implementation points of the English learning user behavior data mining and analysis system based on artificial intelligence technology. By collecting and analyzing user behavior data, a set of efficient personalized learning solutions is launched to improve the effect and efficiency of English learning. The method uses machine learning algorithms to process a large amount of user data, and by generating user behavior data models, it reveals user learning habits, preferences and difficulties, and provides personalized learning guidance and resource recommendations based on the analysis results. The experimental results show that the system can accurately analyze the characteristics of user behavior and strengthen the fit of personalized recommendation of learning paths. Finally, relying on the actual application review of the system, the user learning effect is obvious, and the learning time and cost have been reduced. This study has found a feasible way for intelligent English learning and has considerable practical application value.