Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. This course will prepare you to design and implement realistic predictive models based on data. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake.

Learning data analysis with excel