In the background of the era of digitalization of big data information, the traditional teaching of ideological and political courses faces huge challenges. The innovation of ideological and political courses education is imperative, and the topic of ideological and political education combined with big data technology has attracted the attention and research of ideological educators. This paper focuses on the development of the integration of red genes and curriculum thinking and politics based on the BP neural network mathematical algorithm. Firstly, we briefly understand the concept and principle of the BP neural network mathematical algorithm and algorithm by finding literature, constructing BP neural network model, analyzing the specific strategy of the BP neural network teaching algorithm for the integration of red gene and curriculum Civic and Political development, and data analysis take the ideological and political achievement of a university between 2006 and 2015 as the learning sample and establishes the BP neural network system by conducting the actual achievement and predicted grades data analysis. Then the established model was used to predict the ideological and political grades of the university from 2016 to 2020. The comparison study and discussion were conducted with the actual grades. The results showed that the actual grades of students and the predicted grades both showed a positive linear correlation. The study had a promotional effect on the improvement of students’ grades. The maximum error between the actual and predicted grades was 3, which maximally ensured that the BP neural network-based model predicted the accuracy and stability of the ideological and political grades. This study provides a substantial reference for ideological and political curriculum research and helps students establish correct socialist core values, thus having great historical significance for developing ideological and political education in China