This course introduces the mean-field asymptotic results for high dimensional linear models, and discusses two applications in statistics and machine learning. One application is deriving the double-descent curve for the generalization error of over-parameterized models. The other application is analyzing the power of false discovery rate (FDR) controlling procedures.