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
- 1Learn how to fit and interpret a simple linear regression model.
- 2Learn how to build and interpret linear regression models with more than one predictor.
- 3Learn how to choose the best linear regression model for a particular research question.
- 4Learn 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
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.
Craigslist Analysis
Compare linear regression models to predict housing prices on Craigslist.
How you'll master it
Stress-test your knowledge with quizzes that help commit syntax to memory
— 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.
Course Description
Learn how to fit, interpret, and compare linear regression models in Python.
Details
Earn a certificate of completion
7 hours to complete in total
Intermediate
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
1 article