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This guide collects provides a basic overview of how to utilize the Datahub infrastructure that powers Data 8, Connectors, Modules, and more. There are useful scripts for doing routine things, some example Jupyter notebooks, tutorials, and teaching pointers.
To go straight to the code, go here (or click on the code tab above).
This guide is for instructors and staff, involved in the data science connector, modules, and other data science courses. The material used will be the same technology infrastructure as the Foundations (Data 8) course.
Specifically, if you want to use Jupyter notebooks and
optionally the datascience package (in python) in your course, this guide is for you.
This guide may also become the home for other info for connector instructors, such as tips on working with your Connector Assistants (CAs).
In addition to the resources in this wiki, there is also a codebase that is meant to be useful for connector instructors. This currently includes three things:
- A collection of general "tutorial" notebooks that cover common computational problems and challenges in python
- A python module called
connectortoolsthat has functions meant to be helpful in your classes - A collection of example notebooks that demonstrate the functionality in the
connectortoolsmodule.
You can find a link to this code here (or click the "code" tab to the top left).
If you're interested in running the tutorials or examples for the connectortools module, click the image below to enter an interactive browsing session.
If you have any questions or suggestions for what to add, you can reach out to your connector associate or contact us on Piazza or the [Datahub Slack Channel].