Time to completeApprox. 7 hours
Certificate of completionIncluded with paid plans
About this course
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.
Syllabus4 lessons • 3 projects • 3 quizzes
Hands-on learningDon’t just watch or read about someone else coding — write your own code live in our online, interactive platform. You’ll even get AI-driven recommendations on what you need to review to help keep you on track.
Projects in this course
Linear Regression at CodecademyHelp us understand quiz performance on Codecademy using linear regression.
Algerian Forest FiresIn this project, you will explore data on Algerian forests and run multiple linear regression models using variables including temperature, humidity, and fire risk.
Craigslist AnalysisCompare linear regression models to predict housing prices on Craigslist.
Reviews from learners
- The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.ChrisCodecademy Learner @ USA
- I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.RodrigoCodecademy Learner @ UK
- Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.John-AndrewCodecademy Learner @ USA
Our learners work at
Looking for something else?
Introduction to Regression AnalysisThis article is a brief introduction to the formal theory (otherwise known as Math) behind regression analysis.
What is Scikit-Learn?Open-source ML library for Python. Built on NumPy, SciPy, and Matplotlib.
Log Transformations (And More)Learn when to use a log transformation of the dependent variable of your linear regression and how to interpret the resulting regression equation.
Related courses and paths
Learn Linear Regression with RLearn about the difference between simple linear regression and multiple linear regression in RWith CertificateIntermediate3 hours
- Free course
Multiple Linear RegressionLearn how to build and interpret linear regression models with more than one predictor variable.Beginner Friendly3 hours
- Free course
How to Choose a Linear Regression ModelLearn about the differences between different regression models and how to decide which one to use.Intermediate1 hour
Browse more topics
- Python4,368,657 learners enrolled
- Data Science5,574,259 learners enrolled
- Math83,280 learners enrolled
- Code Foundations12,504,472 learners enrolled
- For Business9,518,168 learners enrolled
- Computer Science7,145,442 learners enrolled
- Web Development6,629,762 learners enrolled
- Cloud Computing3,950,424 learners enrolled
- Data Analytics3,731,593 learners enrolled
Unlock additional features with a paid plan
Practice ProjectsGuided projects that help you solidify the skills and concepts you're learning.
AssessmentsAuto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
Certificate of CompletionEarn a document to prove you've completed a course or path that you can share with your network.