This notebook contains steps and code to work with the watson-machine-learning-client library available in PyPI repository. It introduces commands for getting data and for basic data exploration, pipeline creation, model training and evaluation, model persistance to the Watson Machine Learning (WML) repository, model deployment, and scoring. This notebook uses the latest version of Python, scikit-learn and the watson-machine-learning client package.