Using simulated data, public datasets, and Jupyter notebooks, this course will take you through: Simple linear regressions and multiple linear regression concepts, the mathematics behind linear regression models, how to manually implement a linear regression model, how to use statsmodels and scikit-learn Python packages to implement a linear regression model, how to validate a model and measure it's efficacy, and how to handle common issues. Then, you will be given the opportunity to build a linear regression model from start to finish in a self-guided project.


  • Python (including pandas,numpy, and matplotlib libraries)
  • Basic maths and statistics (introductory calculus helpful but not necessary)

Provided By

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Course Components

Virtual Labs to gain hands on experience and apply what you learned
Assessments to gauge understanding and comprehension

Certificate of Completion

Certificate Of Completion

Complete this entire course to earn a Linear Regression with Python Certificate of Completion