Fernando Perez talks about UC Berkeley's transition into an environment where many undergraduates use Jupyter and the open data ecosystem as naturally as they use email.
Tracy Teal explains how to bring people to data and empower them to address their questions.
Ryan Abernathey makes the case for the large-scale migration of scientific data and research to the cloud.
David Schaaf explains how data science and data engineering can work together to deliver results to decision makers.
Michelle Gill discusses how data science methods and tools can link information from different scientific fields and accelerate discovery.
Watch keynotes covering Jupyter's role in business, data science, higher education, open source, journalism, and other domains, from JupyterCon in New York 2018.
All the cool kids are doing it, maybe we should too? Jupyter, gravitational waves, and the LIGO and Virgo Scientific Collaborations
Will Farr offers lessons about the many advantages and few disadvantages of using Jupyter for global scientific collaborations.
Paco Nathan shares a few unexpected things that emerged in Jupyter in 2018.
Carol Willing shows how Jupyter's challenges can be addressed by embracing complexity and trusting others.
Mark Hansen explains how computation has forever changed the practice of journalism.
Julia Meinwald outlines effective ways to support the unseen labor maintaining a healthy open source ecosystem.
Jeremy Freeman describes a growing ecosystem of scientific solutions, many of which involve Jupyter.
Lorena Barba explores how we can build a capacity to support reproducible research into the design of tools like Jupyter.
Andrew Odewahn explains how O’Reilly Media applied the Jupyter architecture to create the next generation of technical content.
Brett Cannon looks at how healthy expectations can maintain a balanced relationship between open source users and project maintainers.
Nadia Eghbal explores how money can support open source development without changing its incentives.
Wes McKinney makes the case for a shared infrastructure for data science.
Labz ‘N Da Wild 2.0: Teaching signal and data processing at scale using Jupyter notebooks in the cloud
Demba Ba explains how he designed and implemented two Harvard courses that use cloud-based Jupyter notebooks.