Jupyter Notebooks have been a widely popular tool for data science in recent years due to their ability to combine code, text, and visualizations in a single document.

Despite its popularity, the core functionality and user experience of the Classic Jupyter Notebook interface has remained largely unchanged over the past years.

Lately the Jupyter Notebook project decided to base its next major version 7 on JupyterLab components and extensions, which means many JupyterLab features are also available to Jupyter Notebook users.

In this presentation, we will demo the new features coming in Jupyter Notebook version 7 and how they are relevant to existing users of the Classic Notebook.

Jupyter notebooks are a popular tool for data science and scientific computing, allowing users to mix code, text, and multimedia in a single document. However, sharing Jupyter notebooks can be challenging, as they require installing a specific software environment to be viewed and executed.

JupyterLite is a Jupyter distribution that runs entirely in the web browser without any server components. A significant benefit of this approach is the ease of deployment. With JupyterLite, the only requirement to provide a live computing environment is a collection of static assets. In this talk, we will show how you can create such static website and deploy it to your users.