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  • Understand the concept, importance, and components of reproducible research
    • Define reproducible research
    • Name four ways that reproducible research practices can help you in your own work.
    • Name & describe the four facets of reproducible research
    • Explain advantages of using Jupyter Notebooks/Python for implementing reproducible practices
  • Be able to describe the architecture/components of a Jupyter notebook service/application/environment
    • Describe components of the wider Jupyter ecosystem (draw a diagram?)
      • Other Languages that interface with Jupyter
      • Extending notebooks
        • IPyWidgets: Interactive components within the notebook
        • Outputs: Slides, PDFs, html format
      • Alternative User Interfaces: (API Manager, Dashboard Server → https://github.com/jupyter-incubator )
    • Identify and describe the components of a Jupyter notebook service: web interface, ipynb/JSON notebook format, programming language kernel, Jupyter server
  • Be able to use a single Jupyter notebook effectively
    • Access a Jupyter notebook environment Either: install a Jupyter environment from scratch Or: access an online Jupyter notebook environment
    • Manage a running Jupyter notebook server application (/tree page): notebook listing, running kernels, terminal
    • Use the browser interface interface to an individual Jupyter notebook effectively:
      • Understand the functions notebook tabs (File, Edit, View, Insert, Cell, Kernel, Help)
      • Execute and modify cells:
        • Insert & delete cells
        • Change cell type (& know different cell types)
        • Run a single cell from taskbar & keyboard shortcut (shift + Enter)
        • Run multiples cells, all cells
        • Re-order cells
        • Split & merge cells
        • Stop a running cell
      • Use Jupyter notebook keyboard shortcuts effectively: Shift + Enter → run a cell
      • Kernel management Clear and restart a kernel Know which kernel you are running on
    • Use a Jupyter notebook to create a document that combines text, code and executed code output:
      • Use Markdown cells to: generate rich text, demonstrating: headings, lists, embedded images, code formatting embed media objects: images, video, audio
      • Use code cells to:
        • execute code fragments
        • create rich outputs: tables, images
        • perform command line operations: use the ! operator
        • display documentation and help files: use the ? operator
        • list variables, functions, and modules in your notebook (%whos)
  • Be able to access the wider Jupyter community
    • Identify 2+ resources (online or a local group) you can use/ask questions as you learn & develop your Python research project.
      • Jupyter Google Group
      • GitHub repo, gitter etc?