Brought to you by NumFOCUS Foundation and O’Reilly Media
The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY

Schedule: Training and education sessions

9:00am–12:30pm Wednesday, August 22, 2018
Deploying a cloud-based JupyterHub for students and researchers
Location: Murray Hill A Level: Beginner
Carol Willing (Cal Poly San Luis Obispo), Min Ragan-Kelley (Simula Research Laboratory), Erik Sundell (IT-Gymnasiet Uppsala)
Average rating: ****.
(4.50, 2 ratings)
Carol Willing, Min Ragan-Kelley, and Erik Sundell demonstrate how to provide easy access to Jupyter notebooks and JupyterLab without requiring users to install anything on their computers. You'll learn how to configure and deploy a cloud-based JupyterHub using Kubernetes and how to customize and extend it for your needs. Read more.
9:00am–12:30pm Wednesday, August 22, 2018
Network and graph analysis with Jupyter notebooks
Location: Gramercy A Level: Intermediate
Noemi Derzsy (AT&T Labs)
Networks, also known as graphs, are one of the most crucial data structures in our increasingly intertwined world. Social friendship networks, the web, financial systems, and infrastructure are all network structures. Noemi Derzsy explains how to generate, manipulate, analyze, and visualize graph structures that will help you gain insight about relationships between elements in your data. Read more.
9:00am–12:30pm Wednesday, August 22, 2018
Preparing your Jupyter notebook for computationally reproducible publication: A hands-on BYONotebook tutorial for researchers
Location: Gramercy B Level: Beginner
April Clyburne-Sherin (Code Ocean)
Average rating: ***..
(3.00, 2 ratings)
April Clyburne-Sherin walks you through preparing Jupyter notebooks for computationally reproducible publication. You'll learn best practices for publishing notebooks and get hands-on experience preparing your own research for reuse, creating documentation, and submitting your notebook to share. Read more.
9:00am–12:30pm Wednesday, August 22, 2018
An introduction to Julia in Jupyter
Location: Murray Hill B Level: Beginner
Jane Herriman (Julia Computing)
Average rating: *****
(5.00, 2 ratings)
Jane Herriman uses Jupyter notebooks to show you why Julia is special, demonstrate how easy it is to learn, and get you writing your first Julia programs. Read more.
1:30pm–5:00pm Wednesday, August 22, 2018
I Do, We Do, You Do: Supporting active learning with notebooks
Location: Gramercy A Level: Intermediate
Rachael Tatman (Kaggle)
Average rating: ***..
(3.33, 3 ratings)
Rachael Tatman offers practical introduction to incorporating Jupyter notebooks into the classroom using active learning techniques. Read more.
1:30pm–5:00pm Wednesday, August 22, 2018
Advanced Data Science
Location: Murray Hill B
Bruno Goncalves (Data For Science), Matt Brems (General Assembly)
This two-part tutorial presents a sequence of advanced topics in Data Science, based on using Jupyter. Read more.
11:05am–11:45am Thursday, August 23, 2018
Flipped learning with Jupyter: Experiences, best practices, and supporting research
Location: Beekman/Sutton North Level: Beginner
Lorena Barba (George Washington University), Robert Talbert (Grand Valley State University)
Average rating: *****
(5.00, 2 ratings)
In flipped learning, students encounter new material before class meetings, which helps them learn how to learn and frees up class time to focus on creative applications of the basic material. Lorena Barba and Robert Talbert discuss the use of Jupyter notebooks as a “tangible interface” for new material in a flipped course and share case studies from their own courses. Read more.
11:55am–12:35pm Thursday, August 23, 2018
JupyterHub for domain-focused integrated learning modules
Location: Beekman/Sutton North Level: Non-technical
Mariah Rogers (UC Berkeley Division of Data Sciences), Julian Kudszus (UC Berkeley Division of Data Sciences)
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. Read more.
1:50pm–2:30pm Thursday, August 23, 2018
Jupyter for every high schooler
Location: Beekman/Sutton North Level: Beginner
Rob Newton (Trinity School)
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. Read more.
2:40pm–3:20pm Thursday, August 23, 2018
Real-time collaboration with Jupyter notebooks using CoCalc
Location: Murray Hill Level: Intermediate
William Stein (SageMath, Inc. | University of Washington)
Average rating: ****.
(4.50, 2 ratings)
William Stein explains how CoCalc relates to Project Jupyter and shares how he implemented real-time collaborative editing of Jupyter notebooks in CoCalc. Read more.
4:10pm–4:50pm Thursday, August 23, 2018
Learn by doing: Using data-driven stories and visualizations in the (high school and college) classroom
Location: Beekman/Sutton North Level: Non-technical
Carol Willing (Cal Poly San Luis Obispo), Jessica Forde (Jupyter), Erik Sundell (IT-Gymnasiet Uppsala)
Average rating: ****.
(4.50, 2 ratings)
Students learn by doing. Carol Willing, Jessica Forde, and Erik Sundell demonstrate the value of interactive content, using Jupyter notebooks, widgets, and visualization libraries, share notable examples of projects within the Jupyter community, and outline ways educators can help students develop data science literacy and use computational skills to build upon their interests. Read more.
11:05am–11:45am Friday, August 24, 2018
Data science in US and Canadian higher education
Location: Beekman/Sutton North Level: Beginner
Laura Noren (Obsidian Security)
Average rating: *****
(5.00, 1 rating)
Laura Noren offers an overview of a research project on the various infrastructure models supporting data science in research settings in terms of funding, educational uses, and research utilization. Laura then shares some of the findings, comparing the national federation model currently established in Canada to the more grassroots efforts in many US universities. Read more.
11:55am–12:35pm Friday, August 24, 2018
I don't like notebooks.
Location: Nassau Level: Beginner
Joel Grus (Allen Institute for Artificial Intelligence)
Average rating: *****
(5.00, 1 rating)
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. Read more.
11:55am–12:35pm Friday, August 24, 2018
The Jupyter Notebook as a transparent way to document machine learning model development: A case study from a US defense agency
Location: Concourse A: Business Summit Level: Beginner
Catherine Ordun (Booz Allen Hamilton)
Average rating: *****
(5.00, 5 ratings)
Many US government agencies are just getting started with machine learning. As a result, data scientists need to de-"black box" models as much as possible. One simple way to do this is to transparently show how the model is coded and its results at each step. Notebooks do just this. Catherine Ordun walks you through a notebook built for RNNs and explains how government agencies can use notebooks. Read more.
1:50pm–2:30pm Friday, August 24, 2018
Jupyter graduates
Location: Beekman/Sutton North Level: Beginner
Douglas Blank (Comet.ML)
For the last four years, Douglas Blank 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. Read more.
2:40pm–3:20pm Friday, August 24, 2018
Reproducible education: What teaching can learn from open science practices
Location: Beekman/Sutton North Level: Non-technical
Elizabeth Wickes (School of Information Sciences, University of Illinois at Urbana-Champaign)
As practitioners of open science begin to migrate their educational material into pubic repositories, many of their common practices and platforms can be used to streamline the instruction material development process. Elizabeth Wickes explains how open science practices can be used in an educational context and why they are best facilitated by tools like the Jupyter Notebook. Read more.
5:00pm–5:40pm Friday, August 24, 2018
Current RISE capabilities and its evolution into the future
Location: Beekman/Sutton North Level: Beginner
Damián Avila (Anaconda, Inc.)
RISE has evolved into the main slideshow machinery for live presentations within the Jupyter notebook. Damián Avila explains how to install and use RISE. You'll also discover how to customize it and see some of its new capabilities. Damián concludes by discussing the migration from RISE into a new JupyterLab-RISE extension providing RISE-based capabilities in the new JupyterLab interface. Read more.