Teaching with Advanced Tools in Data Courses - Datasets, APIs, Auto Graders, and Gradescope

March 6, 2024, 3:00pm to 4:00pm
Intended audience: 
Academic Support Staff, Faculty, Graduate Student Instructors, Instructors
Part of series: 

Eric and BalajiAs part of our series of workshops on DataHub, the second part will concentrate on introducing the Berkeley Data Stack–a suite of tools that support Data Science instruction at Berkeley–and exploring how instructors across the campus are integrating such tools as part of their course work. The tools include nbgitpuller, Otter Grader, Gradescope, and Github.  We'll explore the more advanced functionalities of these tools, which are used by diverse instructors. Consider also enrolling in the first part of this workshop series: Teaching with Jupyter Notebooks in Python and R - Intro to Datahub

For the past six years, UC Berkeley has been utilizing DataHub, a campus-wide JupyterHub infrastructure, to enhance learning across various disciplines like Engineering, Data Science, Natural Science, and Social Sciences. DataHub is used in over 100 courses across 30+ departments, offering interactive computing environments via JupyterHub's open-source tools, accessible from any web browser.

This workshop is ideal for those interested in:

  • integrating computational notebooks to improve learning outcomes,
  • utilizing cloud-based DataHub for interactive computing in classrooms and homework
  • integrating auto graders to grade student assignments and store the final scores in Gradescope

This workshop will provide a concise introduction to Berkeley Data Stack, along with case studies from diverse departments and a brief demo to showcase practical applications. This workshop is the second session in a three-part series aimed at introducing both basic and advanced tools that support Data Science pedagogy. 

By the end of the workshop, participants will be able to understand how they can integrate Berkeley Data Stack as part of their coursework and learn from examples of colleagues across the campus interested in using Datahub as part of their pedagogy.

This hybrid event will be held in person in 117 Dwinelle Hall (Academic Innovation Studio) and also on Zoom. Please register to get the Zoom invite.  

➡️Register for this event here!⬅️

***Registration for this session will close one hour before the session***

Unable to join us for this workshop? Check the RTL events calendar for future offerings of this workshop. Engage with our asynchronous offerings on this topic: Berkeley Data Stack or receive customized assistance by emailing balajialwar@berkeley.edu

Balaji Alwar is the DataHub Service Lead and works at the Research, Teaching, and Learning (RTL) and Data Science Undergraduate Studies to design and scale the Berkeley DataHub, a service that provides interactive computing environments to educators and students across campus using open-source tools in the Jupyter ecosystem and beyond. Previously, he was a product lead for a research project focused on upskilling at the Harvard Kennedy School. He is passionate about using technology for public goods that offer immersive and equitable learning experiences.
Eric Van Dusen has been with DSUS and CDSS since 2017, teaching and leading teams focused on interdisciplinary teaching with Jupyter notebooks. He teaches at the nexus of Data Science and Economics and is involved in national efforts to expand data science education through workshops and collaborations with Community Colleges.


Research, Teaching, and Learning (RTL)

Series description

The "Teaching Effectiveness" workshop series is designed to empower educators with diverse strategies and tools across a wide range of topics, including course design, student engagement, active learning, and more. Join us as we explore evidence-based practices and discover innovative approaches to elevate your teaching effectiveness.