Applied Machine Learning in Python
Self-paced
Yes
Python + statistics
Hands-on Michigan course on scikit-learn. Less theory, more ‘here is a dataset, here is what to do.’
What you will learn:
- scikit-learn workflows
- Model evaluation and cross-validation
- Hyperparameter tuning and pipelines
- Algorithms: trees, SVM, ensembles
Who it is for: Analysts moving into ML, engineers building production models.
Honest take: Best after Andrew Ng’s ML Spec or alongside it. The ‘I now know ML — how do I use it?’ course.