Guideline Limitations

The majority of scheduled live training sessions will utilize notebooks (Python, SQL, R), but it is highly encouraged to adapt these style guidelines if you are teaching a technology/topic that doesn’t rely on notebooks (or for which these guidelines don’t work) and document any style changes you think should become the standard for these technologies.

Make sure to check out the Getting Started in Tableau, Data Viz with ggplot 2 sessions here for how such sessions could be made.

Live Training with Notebooks

Using Python, R, and SQL Notebooks

For Live Trainings involving Python, R, and SQL, a Google Colab template will be provided for you to use. The template will come with guidelines for the introductory cells and the code to import your dataset.

Note for SQL

DataCamp SQL Live Trainings will use PostgreSQL. This is achieved by running Postgres inside a Python Google Colabs notebook. The code to import and run Postgres will be included in your notebook, but you will need to revise the cell to create the table.

As the script takes a few minutes to import Postgres, it is important to remind your learners to run the cell immediately upon opening the notebook, and every time they open the notebook again for their own use.

Any live training utilizing notebooks (Google colabs, Jupyter and Binder) should adopt the following guidelines:

Structure

  • Notebook should begin with a Markdown cell containing the DataCamp logo - as well as a description of your session with the learning objectives, and a description of the dataset being used. Here's an example of such a cell in the introduction of this notebook.
  • Add 2 code cells containing relevant imports (if any), and reading the dataset used (if any) respectively.

Aim to have a narrative and purpose to the flow of the notebook, for more on designing your outline, here's a post on designing live training specs.

Ways to use Markdown, images and graphics

In order to:

  • Enable notebook re-usability (i.e. students can open your notebook in the future without watching the session and understand what’s going on)
  • Minimize questions during Q&A
  • Remain consistent with the DataCamp design language in courses and projects
  • Enable high quality pedagogy, and empower you to remember what matters

We highly encourage the use of creative markdown cells with images and gifs to get your point across. A ballpark of a 30%-70% split between markdown and code cells is what you're aiming for throughout the notebook.

Here's a list of recommended uses for Markdown:

  1. Explaining a concept. See here for the anatomy of a matplotlib figure.
  2. Brief explanation of the relevant syntax you're using in a session. See here for introduction of plots and relevant syntax used before each code cell.
  3. Brief explanation of things you're anticipating learners to struggle with. See here for an explanation of .flatten() and zip().
  4. Narrative hooks to help you guide your session. See here for the data cleaning to-do list created to help learners not feel overwhelmed and give them direction.
  5. Use of Latex and colors to introduce formulas + Q&A section here.

If you want to create your own custom images, an easy way to do so is creating your graphics on google slides and screen-shotting them. For gifs, you can use this tool to record transitions between slides.

Other Coding Environments

Live Training Sessions may feature other technologies, such as Tableau or Microsoft Excel. These environments may not feature the same markdown capabilities as Google Colab notebooks, but keep the following in mind:

  • Make instructions within the workbook clear and easy to follow
  • Use color coding if possible to distinguish tabs
  • Unless the activity calls for a new sheet to be created, have all necessary sheets created beforehand (For example, in an Excel session, include worksheets for pivot tables, analysis, visualizations in addition to the raw data)
  • Consider including an introduction sheet, or a Table of Contents sheet to stay organized
  • As with Google Colab notebooks, remember that you can include images if necessary or helpful
  • Include recaps and explanation of code syntax where applicable

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