Interactive exploration and analysis of large amounts of data from scientific simulations, in-situ visualization and application control are convincing scenarios for explorative sciences. Based on the open source software JupyterLab, a way has been a
## General Information
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Interactive exploration and analysis of large amounts of data from scientific simulations, in-situ visualization and application control are convincing scenarios for explorative sciences. Based on the open source software JupyterLab, a way has been available for some time now that combines interactive with reproducible computing while at the same time meeting the challenges of support for the wide range of different workflows. The approach enables the creation of documents that combine live code with narrative text, mathematical equations, visualizations, interactive controls, and other extensive output.
However, a number of challenges must be mastered in order to make existing workflows ready for interactive high-performance computing. With so many possibilities, it's easy to lose sight of the big picture. The course offers an introduction to the world of possibilities of JupyterLab.
