Machine Learning with Python

Machine Learning with Python, course code ML0101EN, introduces the main families of machine learning algorithms using Python and Jupyter notebooks. The Cognitive Class page states an estimated effort of 20 hours at beginner level, in English. Five modules run in order: supervised versus unsupervised learning and how machine learning relates to statistical modelling; supervised learning with K-nearest neighbours, decision trees and random forests; regression algorithms and model evaluation, including overfitting and underfitting; unsupervised learning with K-means, hierarchical and density-based clustering; and dimensionality reduction with collaborative filtering. The page lists Python for Data Science as a prerequisite and warns that the hands-on labs require working knowledge of Python for data analysis, suggesting the platform's Data Analysis with Python and Data Science Hands-on with Open Source Tools courses for anyone not yet comfortable in Jupyter.

Course staff include IBM data scientists and curriculum developers. The course is free of charge and the page says a certificate is offered on completion, provided at no cost. IBM also lists a Machine Learning with Python digital badge on its badges page, issued through Credly.