Predictive modeling and analytics

Welcome to the second course of the Data Analytics for Business specialization! This course will introduce you to some of the most widely used predictive modeling techniques and their underlying principles. By the end of this course, you will have a solid foundation in predictive analytics, which refers to the tools and techniques for building statistical or machine learning models that make predictions from data. You will learn how to conduct exploratory data analysis to gain insights and prepare data for predictive modeling, an important skill valued in business. You will also learn how to summarize and visualize data sets using graphs to present results in a compelling and meaningful way. We will use practical predictive modeling software, XLMiner, which is a popular Excel plugin. This course is designed for anyone interested in using data to gain insights and make better business decisions. The techniques discussed apply across all functional areas of business organizations, including accounting, finance, human resources, marketing, operations, and strategic planning. Suggested prerequisites for this course include a prior working knowledge of Excel, introductory algebra, and basic statistics.