COUniversity of Washington · on Coursera
Machine Learning: Classification
Beginner English Professional CertificateFREE
What you'll learn
Build classifiers with logistic regression
Use decision trees and ensemble methods like boosting
Handle missing data and class imbalance
Evaluate classifiers with the right metrics
Apply classification to real case studies
Implement the methods in Python
This course includes
Yes
Certificate
Yes
Mobile access
English
Language
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Instructor
EF
Emily Fox
Coursera instructor
— learners— courses — instructor rating
Emily Fox and Carlos Guestrin of the University of Washington bring research depth and unusually clear teaching to the specialization. Guestrin in particular is often praised by learners for making complex ideas approachable.
Requirements
- Some Python programming
- Basic maths (linear algebra and statistics help)
Who this course is for
- Learners building practical ML skills
- Data scientists strengthening classification
- Anyone in the UW ML Specialization
About this provider
CO
Coursera
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4.6 trust score
Frequently asked questions
Classification methods — logistic regression, decision trees, boosting — plus practical issues like missing data and class imbalance, applied through case studies such as sentiment analysis.
Some Python and basic maths. It's hands-on, with programming assignments using the methods on real datasets.
You can audit the full course free on Coursera. A certificate requires a subscription.
Yes — it's well-regarded and project-oriented, with excellent lectures. Be aware a few topics across the series get only light coverage (e.g. SVMs).
It helps to follow the specialization order, but if you already know the basics of ML and Python you can take the classification course fairly independently.