In order to improve the limitations of traditional teaching models, this paper analyzes the demand for building a personalized teaching platform for high school computers based on big data. It elaborates in detail on the core functions of supporting large-scale user access, intelligent recommendation of learning content, and providing personalized teaching suggestions for teachers. The system design and technical implementation are discussed from four aspects: platform architecture design, data collection and processing, personalized recommendation algorithms, and intelligent evaluation feedback mechanisms. Through experiments, it can be verified that the platform constructed in the article has significant advantages in improving student learning outcomes, enhancing teaching flexibility, and supporting teacher decision-making.