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  1. Python Pip Installs on the Cluster: Understand where pip installs packages within a user’s home folder with respect to different versions of Python.

  2. Pip Install within a Conda Environment: Understand how Conda’s pip works with a User’s Python pip package Installs.

  3. Create a Shared TensorFlow Conda Environment: General process for creating and sharing a conda environment under a project.

  4. Create a Module File to Load Your Conda Environment: Demonstrate creating a module file to load a Conda environment.

  5. Extend Conda Environment to Jupyter Kernel: Demonstrate extending a Python related conda environment in to Juypter kernel.

  6. Jupyter Python Packages and Issues: When using Jupyter how are python packages managed?

  7. Conda and Pip Environments and Reproducibility: Introduce ideas and practices to assist in managing the reproducibility of environments created using Conda and Pip.

  8. Python, Conda and Pip: Suggested Best Practices: Suggest best practices and summarize workshop.

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