Foundations of Predictive Analytics: Regression and Classification

The course provides practical guidance on implementing predictive analytics to achieve business goals. You will explore the different stages of a data analytics pipeline, including data collection, data cleaning, and data analysis. You will discover how regression analysis can be used to identify relationships between variables for business decision-making and find out how sales data is used to probe customer behavior ahead of further analysis. You will also learn how to estimate relationships between variables with regression analysis and review whether a regression model meets specified business success criteria. Lastly, you will delve into the value and practical considerations of using classification models to customize business strategies.

• Identify areas where predictive analytics can be applied to achieve business objectives.
• Evaluate data requirements and sources needed for predictive analytics projects.
• Choose appropriate regression analysis techniques based on business objectives.
• Analyze model outputs and determine if further iterations are necessary to improve model accuracy.
• Evaluate classification approaches and limitations to determine the best approach for achieving business goals.