This chapter primarily introduces the regular process of structured data competitions, including exploratory data analysis (EDA), data preprocessing (including Missing Values, Outliers and Memory Optimization), feature engineering (including feature construction and feature selection), modeling (including model selection and model hyperparameter optimization), and ensemble learning (including Voting Method, Average Method, Weighted Average Method, Stacking and Blending).