An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Exciting new topics such as random forests and general linear models are included. The book emphasizes datadriven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. It exercises at the end of every chapter, totaling over 500 exercises in the book.