About this course: This course introduces some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. Two common examples are used throughout the course so that you will see how different predictive models work on the same dataset and get a sense of their relative strengths and weaknesses. You will also learn how to build these predictive models using the software tool XLMiner, which is a plug-in for Excel. Even though we do not cover every predictive models, the fundamental ideas you will learn from this course apply to models not covered in the course as well.