This lecture focuses on the estimation of optimism for predictors learned via statistical models using the maximum likelihood principle. It covers the derivation of Takeuchi's Information Criterion, which leads to Akaike's information criterion as a special case. The application of AIC to linear regression is demonstrated, along with the presentation of AICc for cases with large p.