DataCamp's most-reviewed machine-learning course, walking through classification and regression with real datasets — predicting customer churn, diabetes risk and song genre — rather than toy examples. Hands-on in Python with scikit-learn, it is a practical, popular first real ML course for people who already know some Python.
Good for: A hands-on, practical first machine-learning course in Python.
Less suitable if: You cannot code Python or want deep ML theory.
Requirements: Basic Python; some statistics helps.
Realistic time: Around 4 hours.
About this course
Supervised Learning with scikit-learn is DataCamp's most reviewed machine learning course, walking through classification and regression with real datasets — predicting customer churn, diabetes risk, and even song genre — rather than toy examples. It covers the full practical workflow: train/test splits, k-fold cross-validation, hyperparameter tuning with GridSearchCV, and building preprocessing pipelines.
What you'll learn
Assess model generalization with train-test splits and cross-validation
Build classification and regression models on real datasets
This course includes
4h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
DataCamp runs on a subscription — roughly $14/month billed annually (more month-to-month), with the first chapter of each course free to try. A certificate of completion is included with the subscription.
Comparison · LBS
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DADataCamp4.8(8,419)
Supervised Learning with scikit-learn
Price
Paid
DataCamp subscription · from $25/mo (free trial)
Duration
4 hrs
Level
Beginner
Certificate
Course Certificate
EDedX
Machine Learning with Python: A Practical Introduction