Free
CourseLinear Regression in Python
Learn how to fit, interpret, and compare linear regression models in Python.
This course includes
This course includes
Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary6 hoursProjects
3Prerequisites
None
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.
Syllabus
4 lessons • 3 projects • 3 quizzesCertificate of completion available with Plus or Pro
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Projects in this course
- practice Project
Linear Regression at Codecademy
Help us understand quiz performance on Codecademy using linear regression. - practice Project
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. - practice Project
Craigslist Analysis
Compare linear regression models to predict housing prices on Craigslist.
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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
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Looking for something else?
Related resources
- Article
Introduction to Regression Analysis
This article is a brief introduction to the formal theory (otherwise known as Math) behind regression analysis. - Article
What is Scikit-Learn?
Open-source ML library for Python. Built on NumPy, SciPy, and Matplotlib. - Article
Regression vs. Classification
Learn about the two types of Supervised Learning algorithms.
Related courses and paths
- Free course
Simple Linear Regression
Learn how to fit and interpret linear regression with a single predictor variableBeginner Friendly2 hours - Free course
Multiple Linear Regression
Learn 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 Model
Learn about the differences between different regression models and how to decide which one to use.Intermediate1 hour
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.