Mainly includes the basics of data mining, probability theory and mathematical statistics, data mining effect evaluation, data preprocessing, data warehouse, data classification analysis, data clustering analysis, association rule discovery, statistical prediction methods. In the discussion of algorithms at the same time the introduction of application examples, emphasizing the application of methods including algorithm characteristics, parameter selection, evaluation of results and other aspects of the analysis, the theory is linked to practice, conducive to the rapid mastery of the algorithm and effective use.