Community College (and smaller institutions) Adoption

Under Cloudbank and with funding from NSF, we offer resources to teach Data Science courses, including the full set of materials used to teach Data 8 at Berkeley.

There are a series of steps needed to acquire the materials and solutions, gain access to compute for your students, and set up our automatic grading system.

You can expect the following:

• The Jupyter Notebooks for labs, homeworks, and projects

• The solutions to all the Jupyter Notebooks

• Lecture slides and videos of each lecture

• Worksheets (and solutions) used in discussion and lab sessions

• A Canvas template customized to use JupyterHub for your institution

• Access to a JupyterHub instance for your institution, configured to your campus single sign-on or other options

• Access to a grading service that grades student notebooks and returns grades in a CSV file

Your institution may need documentation related to privacy (HECVAT) and accessibility (VPAT):

• Here is a HECVAT outlining what student information is needed (just an email address) and how it is protected.

• Accessibility is an ongoing effort at UC Berkeley and within the Jupyter community:

  • This document outlines the current state of Jupyter with regard to accessibility

  • An extension to JupyterHub is being created to assess the accessibility of notebooks

Choose your adoption version¶

We offer two adoption packages. Both use the same adoption workflow below; the main differences are which materials repository and Canvas template you use.

Throughout this guide, look for Version 1 and Version 2 callouts where steps differ.

Step 1. Privacy agreement and general information¶

Estimated time: 15–30 minutes

We ask that anyone using these materials do not distribute solutions. We also need a GitHub username to give you access to the solutions; if you do not have one, please create one here.

Then, complete this form. Indicate which adoption version you plan to use so we can grant access to the correct resources.

We need a few pieces of information about your institution in order to configure the computing environment for your students. Please complete this form as well.

Step 2. Fork the student materials¶

Estimated time: 5–10 minutes

Screen recording: forking the repository

After you have created a GitHub username, log in and Fork the repository for your chosen version:

• Version 1: materials-fds

• Version 2: materials-fds-v2

Step 3. Accept GitHub repository invitations¶

Estimated time: 5 minutes

You will be added to the private solutions repository and to the Otter Service Standalone GitHub organization used to grade student notebooks. Accept the invitations by clicking each of these links:

• Solutions repository: materials-fds-private (solutions for both adoption versions)

• Automatic grading system (Otter Service Standalone): otter-service-stdalone

Step 4. Canvas shell and course website¶

Estimated time: 1–2 hours (depending on customization)

Screen recording: configuring the Canvas shell

We can help you with this process as well.

Download the Canvas template¶

Download the template for your adoption version:

• Version 1: Canvas template (materials-fds)

• Version 2: Use the Fall 2025 Canvas template provided after you complete the adoption form (updated layout, tutoring worksheets, and accessibility improvements). Contact ds-help@berkeley.edu if you need the link again.

Point assignments at your JupyterHub¶

The default template links assignment URLs to datahub.berkeley.edu. If your institution uses a different JupyterHub (for example, your campus hub), use the Canvas JupyterHub rewriter to update the zip or .imscc file before importing:

• Upload your Canvas template (zip or .imscc file) to the rewriter

• Enter your JupyterHub URL (e.g., datahub.berkeley.edu/hub or your institution’s hub URL)

• Enter the materials repository URL for your version:

  • Version 1: https://github.com/data-8/materials-fds

  • Version 2: https://github.com/data-8/materials-fds-v2

• Scan and preview to see how links will change

• Confirm that old links are being rewritten to your hub and that the repo points to the correct repository (data-8/materials-fds or data-8/materials-fds-v2)

• Rewrite and download the updated file

Video: JupyterHub rewriter¶

Import into Canvas¶

We recommend importing the cartridge into a new Canvas course. After the first import, copy that course inside Canvas from term to term instead of re-importing the cartridge into an existing shell (re-importing can duplicate items that do not share the same internal IDs).

• Create a new course — Settings → Start a new course, name it (e.g., “Data 8”)

• Go to Import Course Content from the course menu

• Select Common cartridge 1.x package as the content type

• Upload the .imscc file (the rewritten file from the rewriter step, or the original template if using datahub.berkeley.edu)

• Upload all content for this initial import

• Wait for the import — Status will show “queued” then “running” with a progress bar

• Verify the links — After import, click on an assignment (e.g., Homework 1) and check the link in the bottom-left corner of your browser. It should show your JupyterHub URL. Click through to confirm the notebook loads correctly

Video: Uploading the Canvas template¶

Course calendar overview¶

These week-to-week layouts mirror the Canvas course layout and are useful for getting an overview of the course and exploring alternative platforms to render Jupyter notebooks:

• Version 1: materials-fds demo calendar

• Version 2: Fall 2025 course site

Step 5. Student workflow¶

Review this before your first class

Screen recording: student workflow

Here is how students will interact with assignments:

1. Access: Students log into Canvas and click on an assignment link

2. Open notebook: The notebook opens in JupyterHub (in a new tab)

3. Work: Students complete the notebook, checking answers as they go

4. Export: Students use the “export” cell at the bottom to download their completed notebook

5. Submit: Students upload the downloaded file to Canvas

Step 6. Instructor grading workflow¶

Estimated time: 5–10 minutes per assignment (after initial setup)

Screen recording: grading workflow (5 min)

1. Download student submissions: Export all submissions from Canvas onto your machine

2. Get solutions: Log into materials-fds-private, navigate to the autograder_zips folder, and download the autograder.zip file for the assignment you are grading

3. Grade automatically: Log into grader.datahub.berkeley.edu with your GitHub username and follow the instructions in the screen recording above

4. Import grades: Upload the CSV file with grades back to Canvas

If you would like to test run the grader, you can use these archives:

• Sample HW 08 Submissions (hw-8-submissions.zip)

• HW 08 Solution file (autograder.zip)

For more detail, see the Grading section.

Need more help? Contact us at ds-help@berkeley.edu