Scaling Data Science Education with JupyterHub (feat. Min Ragan-Kelley)
Failed to add items
Add to basket failed.
Add to Wish List failed.
Remove from Wish List failed.
Follow podcast failed
Unfollow podcast failed
Scaling Data Science Education with JupyterHub (feat. Min Ragan-Kelley)
-
Narrated by:
-
By:
About this listen
Access the full transcript for this episode
“The goal of the students is not to learn how JupyterHub works. The goal is to learn what’s the topic of the course. So we want to make it as easy as possible to get into an environment where they can learn what they’re actually there to learn, and not get in their way with the tools that they’re supposed to be using.”
Welcome to season 11 of the podcast! To kick off the new season, we interviewed Min Ragan-Kelley, Senior Open Infrastructure Architect at Berkeley Institute for Data Science (BIDS) and a founding member of JupyterHub. Min discusses the origin story of JupyterHub and how it evolved into the scalable platform that students and researchers alike utilize daily, reflecting on key design decisions that have shaped the platform into what it is today. He describes the importance of the platform to “get out of the way” of students in order to best aid in learning how to operate within a computing environment. Finally, Min touches on his passion for open source projects and what he hopes to come of it in relation to data science education.
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit datascienceeducation.substack.com