Linear Regression in Python


In this course, you’ll learn how to fit, interpret, and compare linear regression models in Python. This is useful for research questions such as:

  • Can I predict how much a customer will spend at a store based on attributes such as age, income, and location?
  • What is the relationship between a person’s income and other attributes such as education level and years of experience?

This course requires some prior experience with Python, including experience with Pandas and basic data manipulation, summary statistics, and hypothesis testing.

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  1. 1
    Learn how to fit and interpret a simple linear regression model.
  2. 2
    Learn how to build and interpret linear regression models with more than one predictor.
  3. 3
    Learn how to choose the best linear regression model for a particular research question.
  4. 4
    Learn about the differences between scikit-learn and statsmodels with respect to fitting linear regression models.

What you'll create

Portfolio projects that showcase your new skills

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How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory

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I know from first-hand experience that you can go in knowing zero, nothing, and just get a grasp on everything as you go and start building right away.
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