Interactive Data Analysis with Jupyter Data Science Notebooks

Most programming workflows in research combine data analysis with visualizations and explanations on the scientific purpose of a given method or piece of data. Jupyter notebooks allow us to combine all of these elements in a single document which makes them a very useful tool for computational research. In this unit, we will explore the basics of Jupyter and learn how to write text in Markdown (a simple Markup language), run code and display images.