The regression-focused course of the University of Washington's ML Specialization on Coursera, taught by Emily Fox and Carlos Guestrin through practical case studies like predicting house prices. The teaching of the concepts — linear regression, ridge, lasso and model assessment — is strong. Just be aware the course is from 2016 and uses older proprietary tooling.
Good for: Building solid conceptual understanding of regression, via case studies.
Less suitable if: You want current, job-ready tooling (scikit-learn/PyTorch) from the start.
Skills you'll gain
RegressionLinear regressionRidge and lassoModel assessmentMachine learningFeature selection
Is this course right for you?
A good fit if you…
You want to understand regression deeply
You like case-study learning
You are comfortable the tooling is dated
Consider something else if you…
You want current industry tools from day one
You want the latest deep-learning focus
You want a quick, code-only tutorial
Requirements: Basic Python and some maths comfort.
Realistic time: Around 15–20 hours over a few weeks.
About this course
Machine Learning: Regression is the regression-focused course in the University of Washington's well-regarded ML Specialization. Through practical case studies (like predicting house prices), Emily Fox and Carlos Guestrin build up from simple linear regression to regularisation with ridge and lasso, feature selection, and the bias-variance trade-off — coding the ideas, not just describing them.
What you'll learn
Build and interpret linear regression models
Apply ridge and lasso regularisation
Perform feature selection
Understand the bias-variance trade-off
Evaluate regression models properly
Implement the methods through case studies in Python
This course includes
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
You can audit the course free on Coursera. A certificate needs a Coursera subscription (about $49/month) or Coursera Plus, with financial aid available. It is part of the University of Washington Machine Learning Specialisation.
Comparison · LBS
Compare alternatives for Machine Learning: Regression
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A University of Washington certificate on Coursera is a credible learning record. It is a course certificate rather than a professional qualification or degree.
Last updated
Created in 2016, this course teaches through the proprietary GraphLab/Turi Create library rather than today's standard tools like scikit-learn or PyTorch. The concepts remain sound, but the tooling is dated — factor that in if you want directly job-ready code.
Instructor
EF
Emily Fox
Coursera instructor
Emily Fox and Carlos Guestrin are machine-learning researchers at the University of Washington whose lectures are often singled out as some of the clearest in any online ML course. The specialization takes a practical, case-study-driven approach.
The concepts are sound, but it is from 2016 and uses the proprietary GraphLab/Turi Create library rather than scikit-learn or PyTorch. Factor that in for job-ready code.
Yes, you can audit it free; the certificate needs a Coursera subscription or Coursera Plus.
Yes — basic Python and some comfort with maths are expected.
Yes, it is part of the University of Washington Machine Learning Specialisation.
Both teach fundamentals well. Ng's courses use more current tooling; this one is strong on regression concepts but dated in its tools.