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This tutorial is available for download as a PDF here.

Course Goals:

  • Introduce what Jupyter is and why it’s useful

  • Identify the difference between Jupyter Lab and Jupyter Notebooks and when to use one tool over another

  • Demonstrate the Jupyter service within OnDemand across a variety of available languages and kernels

  • Provide the steps to convert an existing Conda environment into a kernel that can be used within a Jupyter session

Note

Notes:

  • The workshop modules work best in a sequential manner as a story introducing concepts and providing examples, but sections can be used separately to focus on a particular concept.

  • You will need to modify usernames, project names, and folder locations, to apply to yourself.

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  1. Intro to Jupyter

  2. Jupyter: Things to Keep in Mind

  3. Starting Jupyter in OnDemand

  4. Dive into Jupyter Notebooks

  5. Dive into Jupyter Labs

  6. Exporting Conda Environments as a Kernels

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