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  • Welcome to the UC Berkeley Data Science Curriculum Guide!

Getting started with DataHub tools

  • Jupyter Notebooks and JupyterHub
  • R Hub
  • Shiny
  • Quarto
  • VSCode
  • RetroLab
  • Real Time Collaboration (RTC)
  • Use Realtime file sharing using SyncThing
  • Options to Launch R

Workflow Basics

  • Create Assignments
  • Notebook Zero
  • Creating Accessible Notebook Experience
  • Upload Files to Github
  • Distribute Assignments
  • Collect and Grade Assignments
  • Download Jupyter Notebook as PDF
  • Download Datahub home directory contents as archive
  • Best Practices to Avoid Performance Issues
  • Launch Cloud Cost Calculator Widget
  • Securely Push Changes to Github
  • Generative AI Usecase in DataHub
  • Work with Large Datasets
  • Instructional Design Best Practices for Creating Jupyter Notebooks
  • Sharing information about the Hub

Datahub Frequently Asked Questions (FAQ)

  • Onboard new users
  • Package Installations
  • Elevated privileges
  • Change existing requirements in the Hub
  • Troubleshoot issues in DataHub
  • Troubleshoot issues in Link Generator
  • Troubleshoot issues in the Python Code
  • Request new features in the Hub

Resources for Students

  • Resources for Students
  • Troubleshooting Tips for Students

Getting Started with Modules and Connectors

  • What is a Connector course?
    • Previous Connectors
  • What is a Data Science Module?
  • What is a Data-Enabled Course?

Creating a Connector

  • Logistics, Rooms, and Technology
  • Designing Your Syllabus
  • Requesting Student Help
  • Joining Communication Channels
  • Pre-Semester Checklist

Creating a Module

  • Pre-Planning
  • Developing the Module
  • Requesting Deployment Help

Workshop Resources

  • Instructor Activity

Reference

  • People
  • Terms and Abbreviations
  • Contact
  • .md

Instructor activity: Generate nbgitpuller link from scratch

Contents

  • Option 1 - via nbgitpuller
  • Option 2 - via Jupyter notebook

Instructor activity: Generate nbgitpuller link from scratch#

Option 1 - via nbgitpuller#

  • Click this link to launch a Jupyter notebook. This will clone a repository containing a Jupyter notebook to the home directory of your Berkeley Jupyterhub account.

  • Execute all the cells in the “iris.ipynb” notebook which is located inside “datahub_workshop_feb24” directory

  • (This is an optional step) Add text as markdown in the notebook. For instance, you could add a header cell that says “Welcome to my first notebook!”

  • (This is an optional step) Clear all the cells (this is relevant in teaching scenario).

  • Download the notebook by selecting “File -> Download” option

  • Login to your Github account. Incase you don’t have an account, try creating a new Github account for the sake of this activity (or collaborate with someone who has a Github account)

  • Create a new Github repository (If you are new to Github, check this documentation for detailed steps to create a repository)

  • Upload the notebook to Github repository (Refer to this documentation if needed)

  • Install the “Datahub Link Generator” browser extension using this link. Please follow the steps in the documentation to make the extension visible in your browser

  • Generate a new nbgitpuller link by entering the following details in the input fields and clicking the button “Copy nbgitpuller link” “JupyterHub URL”: “https://datahub.berkeley.edu/”, “Open In”: “Classic Notebook”

  • Share the nbgitpuller link with another collaborator who is attending the workshop

Option 2 - via Jupyter notebook#

  • Click this link to download a PDF containing python code

  • Login to https://datahub.berkeley.edu/

  • Launch a new notebook by selecting “Python 3 (ipykernel)” option from launcher (If required, refer to this documentation)

  • Copy paste the code from the PDF to the new notebook

  • Save the notebook

  • Download the notebook by selecting “File -> Download” option

  • Login to your Github account. Incase you don’t have an account, try creating a new Github account for the sake of this activity (or collaborate with someone who has a Github account)

  • Create a new Github repository (If you are new to Github, check this documentation for detailed steps). Upload the downloaded notebook to this Github repository.

  • Install the “Datahub Link Generator” browser extension using this link. Please follow the steps in the documentation to make the extension visible in your browser

  • Generate a new nbgitpuller link by entering the following details in the input fields and clicking the button “Copy nbgitpuller link” “JupyterHub URL”: “https://datahub.berkeley.edu/”, “Open In”: “Classic Notebook”

  • Share the nbgitpuller link with another collaborator who is attending the workshop

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Requesting Deployment Help

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Who are we?

Contents
  • Option 1 - via nbgitpuller
  • Option 2 - via Jupyter notebook

By Christopher Pyles and Balaji Alwar

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