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
4 out of 5 Codecademy learners achieve their goals"Codecademy gave me the tools I needed to land my first job as a developer, completely changing my career from the waste industry." - Jonathan Manner, Sweden
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
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AssessmentsAuto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
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