About this Course

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Start instantly and learn at your own schedule.

Flexible deadlines

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Beginner Level

Basic familiarity with programming in Python. An understanding of linear regression.

Approx. 5 hours to complete

Suggested: 2 hours...

English

Subtitles: English

What you will learn

  • Check

    Build univariate and multivariate linear regression models in Python using scikit-learn

  • Check

    Perform Exploratory Data Analysis (EDA) and data visualization with seaborn

  • Check

    Evaluate model fit and accuracy using numerical measures such as R² and RMSE

  • Check

    Model interaction effects in regression using basic feature engineering techniques

Skills you will gain

Machine LearningPython ProgrammingData Visualization (DataViz)Linear RegressionScikit-Learn

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Basic familiarity with programming in Python. An understanding of linear regression.

Approx. 5 hours to complete

Suggested: 2 hours...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Machine Learning with scikit-learn: Predict Sales Revenue with Multiple Linear Regression

1 reading, 3 quizzes
1 reading
Course Overview10m
2 practice exercises
Ungraded Practice Assessment2m
Multiple Linear Regression — Graded15m

Instructor

Avatar

Snehan Kekre

Machine Learning Instructor

About Rhyme

Rhyme is Coursera's hands-on project-based learning platform. On Rhyme, learners get instant access to pre-configured cloud desktops containing all the software and data they need. Rhyme helps learners apply the knowledge they learned in other Coursera courses into specific tools and use-cases. So they become fully prepared to solve problems in the real-world! ...

Frequently Asked Questions

  • Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

  • If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

  • Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

  • If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

  • This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

  • A project-based course enables you to practice applying a skill by providing you all the guidance, tools, and data you need to complete a project.

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