January 8, 2020

213 words 1 min read

Jupyter graduates

Jupyter graduates

For the last four years, Douglas Blank has used nothing but Jupyter in the classroomfrom a first-year writing course to a course on assembly language, from biology to computer science, from lectures to homework. Join in to learn how Douglas has leveraged Jupyter and discover the successes and failures he experienced along the way. Nicole Petrozzo then offers a student's perspective.
Talk Title Jupyter graduates
Speakers Douglas Blank (Comet.ML)
Conference JupyterCon in New York 2018
Conf Tag The Official Jupyter Conference
Location New York, New York
Date August 22-24, 2018
URL Talk Page
Slides Talk Slides
Video

When Douglas Blank first encountered IPython in the browser, he saw its immediate usefulness for the classroom and began reengineering tools he had been developing with colleagues to work with these new technologies. The expansion of they Jupyter ecosystem—its kernels, languages, metakernels, libraries, and magics—helped him transition to a flipped-classroom design, engaging students at multiple levels. For the last four years, Douglas has used nothing but Jupyter in the classroom—from a first-year writing course to a course on assembly language, from biology to computer science, from lectures to homework. Join in to learn how Douglas has leveraged Jupyter and discover the successes and failures he experienced along the way. Nicole Petrozzo then offers a student’s perspective.

computer science ecosystem biology jupyter python course lecture
comments powered by Disqus
Jupyter for every high schooler

Jupyter for every high schooler

January 8, 2020

In an effort to broaden graduates' mathematical toolkit and address gender equity in STEM education, Rob Newton has led the implementation of Python projects across his school's entire ninth-grade math courses. Now every student in the ninth grade completes three python projects that introduce programming and integrate them with the ideas developed in class.
JupyterHub for domain-focused integrated learning modules

JupyterHub for domain-focused integrated learning modules

January 7, 2020

The Data Science Modules program at UC Berkeley creates short explorations into data science using notebooks to allow students to work hands-on with a dataset relevant to their course. Mariah Rogers, Ronald Walker, and Julian Kudszus explain the logistics behind such a program and the indispensable features of JupyterHub that enable such a unique learning experience.
nbinteract: Shareable interactive web pages from notebooks

nbinteract: Shareable interactive web pages from notebooks

January 7, 2020

The nbinteract package converts Jupyter notebooks with widgets into interactive, standalone HTML pages. Its built-in support for function-driven plotting makes authoring interactive pages simpler by allowing users to focus on data, not callbacks. Sam Lau and Caleb Siu offer an overview of nbinteract and walk you through the steps to publish an interactive web page from a Jupyter notebook.
Sea change: What happens when Jupyter becomes pervasive at a university?

Sea change: What happens when Jupyter becomes pervasive at a university?

January 6, 2020

In 2018, UC Berkeley launched a new major in data science, anchored by two core courses that are the fastest-growing in the history of the university. Fernando Prez discusses the program and explains how the core courses, which now reach roughly 40% of the campus population, are extending data science into specific domains that cover virtually all disciplinary areas of the campus.
The future of data-driven discovery in the cloud

The future of data-driven discovery in the cloud

January 5, 2020

Drawing on his experience with the Pangeo project, Ryan Abernathey makes the case for the large-scale migration of scientific data and research to the cloud. The cloud offers a way to make the largest datasets instantly accessible to the most sophisticated computational techniques. A global scientific data commons could usher in a golden age of data-driven discovery.
I don't like notebooks.

I don't like notebooks.

January 8, 2020

I have been using and teaching Python for many years. I wrote a best-selling book about learning data science. And here's my confession: I don't like notebooks. (There are dozens of us!) I'll explain why I find notebooks difficult, show how they frustrate my preferred pedagogy, demonstrate how I prefer to work, and discuss what Jupyter could do to win me over.