Evaluating and Fine-Tuning Regression Models in Python with Scikit-learn

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Description

Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics.Read more.

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The techniques and tools covered in Customer Analytics are most similar to the requirements found in Data Analyst job advertisements.

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Learning Sequence

Customer Analytics is a part of one structured learning path.

Coursera
University of Pennsylvania

5 Courses 6 Months

Business Analytics