Hands-on practice with text featurization and advanced predictive modeling techniques, including Ridge, Lasso, ensemble methods, and Naive Bayes.

Hands-on practice with data cleaning, feature engineering, and predictive modeling algorithms beyond the basics, including classification trees, kNNs, and regularized logistic regression. Practice creating and interpreting ROC and lift curves.

Predict the target variable “IsBadBuy”, which labels whether a car purchased at auction was a “bad buy” or not.