Back to Predictive Modeling and Analytics
University of Colorado Boulder

Predictive Modeling and Analytics

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.

Status: Microsoft Excel
Status: Data Cleansing
IntermediateCourse11 hours

Featured reviews

AA

5.0Reviewed Aug 11, 2019

Got to many techniques like boosting, bagging, Neural networks, regression tress etc.. Useful and informative course

TN

5.0Reviewed Apr 14, 2020

Good course to give a basic understanding of predictive modelling and analytics. Good assignments and opportunity to review peer submissions help reinforce the learnings.

SK

5.0Reviewed Feb 15, 2017

Its an excellent course and thanks to Professor for making this course so practice oriented.

JJ

4.0Reviewed May 17, 2019

The tutor organised the course with clear points and highlights questions during videos. The only confusion is about web version xlminer tool.

SG

5.0Reviewed May 14, 2020

Very nice course, everything is up to the point very clean and clear explanation of concepts with examples and practical illustrations.

AA

5.0Reviewed Jul 6, 2020

It has been very exciting and an eye-opening for me. I am getting into the world of data analytics gradually. Thanks for this great opportunity.

RM

4.0Reviewed Sep 10, 2019

Professor is a little tough to understand, so I had to read the transcript during some of the videos. However, once I got the XLMiner issues resolved, it continued to be a great class and experience.

PC

4.0Reviewed Nov 9, 2020

some items were unclear, the definitions, the explanation, the examples were necessary. however, I could google to get those.

OD

5.0Reviewed May 29, 2019

Even though a basic math background is needed, this course is extremely simplified for understanding and being really useful introduction to Predictive modeling.

MS

5.0Reviewed Aug 10, 2020

One of the best course I for business analytics that I came across. The whole specialization is worth the time

H

5.0Reviewed Aug 30, 2020

I really enjoyed every aspect of the class it was well designed and the excises were both enjoyable and informative.

AA

5.0Reviewed May 16, 2020

Great course for starting learning the basics of predictive modeling and its application in MS Excel!

All reviews

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William Carnes
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Reviewed Jul 3, 2018
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Abhishek Upadhayaya
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Rachel Shifflett
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Alexandros Ntzoufas
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Yihan Wang
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Mark Shocklee
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Roshni Rajput
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Tracy Cacho
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Antonio JesĂşs Adsuar GĂłmez
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John Tillett
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Reviewed Jan 2, 2018