The PyData ecosystem is rich with tools for working with and visualizing data. Until recently, it has been difficult to put these tools together into a shareable application to let non-Python users explore and make use of the data. The new tools Panel (https://panel.pyviz.org) and Voila (https://github.com/voila-dashboards/voila) make it much simpler to build, adapt, and explore your data, moving seamlessly between Jupyter notebooks and deployed web applications. Here, we will show you how to get started using Panel to build apps and dashboards in notebooks and make them into deployable web applications.

1. 10 min Setup: Making sure everyone is set up with a working environment and data files
2. 20 min Introduction: Background and demos of running Panel dashboards
3. 20 min The simplest panels: pn.interact
4. Exercise 1: Write a function with arguments and a displayable result, and make it a panel
5. 20 min Connecting and assembling widgets
6. Exercise 2: Instantiate widgets explicitly and link them to your function's arguments
7. 20 min Building more complex panels with multiple interlinked panes
8. Exercise 3: Add multiple, interlinked plots controlled by widgets