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.
Codecademy courses have been taken by employees at
Linear Regression at Codecademy
Help us understand quiz performance on Codecademy using linear regression.
Algerian Forest Fires
In this project, you will explore data on Algerian forests and run multiple linear regression models using variables including temperature, humidity, and fire risk.
Compare linear regression models to predict housing prices on Craigslist.
— Madelyn, Pinterest“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.”
Learn how to fit, interpret, and compare linear regression models in Python.
Earn a certificate of completion
7 hours to complete in total
Learn how to fit and interpret a simple linear regression model.
2 lessons, 2 articles, 1 quiz, 1 project
1 lesson, 1 quiz, 1 project