With the development of the modern sports concept, physical education mode in colleges and universities needs to adapt to the requirements of the new era. In this paper, we studied the feasibility and comparative advantages of exercise prescription physical education, collected physical fitness test data of college students, completed the cluster analysis of student physical test data based on the k-medoids algorithm, used semi-supervised RBF neural network to learn each cluster, and generated an exercise prescription for each class of students. In the comparative teaching, the performance of students in the experimental class improved in standing long jump and 50 m, and the changes were statistically significant with p-values less than 0.05. While the indicators in the control class improved slightly before and after the experiment, the p-values were greater than 0.05, and there was no significant difference.