This guide is designed to help students find business cases to practice data mining techniques. Each case consists of a problem statement, a data set and a data dictionary, and some metadata information. In each problem statement section students can find a hypothetical business case or scenario that needs to be analyzed and solved. The name of the target variable, number of columns, number of data records, and links to the data set and data dictionary are provided. Problems are categorized into Classification and Regression cases, based on the type of the target variable. To solve each case, at least one predictive model needs be built to predict the target variable, but visual exploration of data or statistical tests can help understand and address the problem better. Data sets are cleaned to be ready for model building, however, additional feature engineering may improve the predictive outcome. For each case, a list of data mining techniques/tasks that can be used to solve the case is suggested. Finally, links to the sources of data sets or additional resources to study are provided. 

If you have a question about the cases, please contact Dr. Mahdi Ahmadi.