Predictive Modeling and Analytics

Published learning objectives:

Apply exploratory data analysis to gain insights and prepare data for predictive modeling

Summarize and visualize datasets using appropriate tools

Identify modeling techniques for prediction of continuous and discrete outcomes

Identify appropriate graphs to explore and display datasets

Published course description:

Welcome to the second course in the Data Analytics for Business specialization!

This course will introduce you to 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.

You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business.

You’ll also learn how to summarize and visualize datasets using plots so that you can present your results in a compelling and meaningful way.We will use a practical predictive modeling software, XLMiner, which is a popular Excel plug-in.

This course is designed for anyone who is interested in using data to gain insights and make better business decisions.

The techniques discussed are applied in all functional areas within business organizations including accounting, finance, human resource management, marketing, operations, and strategic planning.

The expected prerequisites for this course include a prior working knowledge of Excel, introductory level algebra, and basic statistics.