Applied Machine Learning in Python

Applied Machine Learning in Python is a self-paced online course offered by the University of Michigan on Coursera that focuses on practical machine learning techniques using the scikit-learn toolkit. The course covers key topics including supervised and unsupervised learning (classification, clustering), feature engineering, model evaluation and selection, regularization, ensembles (random forests, gradient boosted trees), and an introduction to neural networks and issues such as data leakage.

The course is structured into four modules with videos, readings, programming assignments, ungraded labs and quizzes. It is described as intermediate level and is intended for learners who have some prior experience with Python (Pandas) and basic data science concepts.

It is part of the Applied Data Science with Python Specialization and is recommended to be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python. Learners can earn a shareable Coursera Certificate by purchasing the Certificate experience; auditing is possible without a certificate.

Financial aid is available for eligible learners. The course is taught in English and is accessible globally via Coursera (remote delivery).