Introduction to Linear & Logistic Regression

About this course

A comprehensive introduction to linear & logistic regression for newcomers.

• 3 lessons
• 15 min
• beginner

What you'll learn

• Explain the historical origins of linear regression and the concept of regression to the mean
• Identify the key figures in developing logistic regression as a statistical model
• Recognize how both regression techniques fit into the broader landscape of supervised machine learning
• Describe the purpose and output type of linear regression for continuous prediction
• Explain how logistic regression uses the S-shaped curve to model probability for categorical outcomes
• Compare least squares estimation (linear regression) with maximum likelihood estimation (logistic regression)

Finishing the course

• 12 knowledge-check questions along the way, so you know the ideas stuck before you move on.
• Watching is free and needs no account. Sign in to save your progress. Pass each lesson's quiz (60%+) to earn the certificate. Each certificate has its own public verification link to share, marked quiz-verified.
• Part of the Machine Learning Fundamentals and Applications learning path. Enrol in the path and finish its required courses to earn one certificate for all of them.

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