The large scale expansion of online courses has led to the crisis of course quality issues. In this study, we first established an evaluation index system for online courses using factor analysis, encompassing three key constructs: course resource construction, course implementation, and teaching effectiveness. Subsequently, we employed factor analysis and entropy weight TOPSIS multi-attribute decision analysis methods to comprehensively evaluate 541 courses. Later on, we conducted correlation and regression analyses between the evaluation results of these two methods and that of experts. The results reveal that the comprehensive evaluation scores derived from both factor analysis and entropy weight TOPSIS models exhibit a significant positive correlation with the experts'. Furthermore, the factor analysis model outperforms the entropy weight TOPSIS model in predicting experts' evaluation scores. The application of this model will help achieve timely and accurate course evaluation, and provide novel idea and approach for real-time monitoring of online courses quality.