This lecture will provide an overview of select core components of the Python software ecosystem for scientific computing and data science, with a particular focus on numpy, scipy, pandas, and matplotlib. The lecture will include both descriptions of the overall design and structure of those packages and their key components, and numerous code examples that demonstrate some of the important functionality. Opportunities for live, hands-on exercises using these packages will be integrated throughout the lecture, all as part of a Jupyter notebook that will include both the lecture content and the hands-on exercises. The Python ecosystem for scientific computing and data science ecosystem enables researchers to use proven and widely-used tools that are easily customized for specific problems using the Python programming language.