IPython Notebook/Project Jupyter hands-on

Who: Titus Brown (lead instructor).

When: November 19 and 20, 2015

Times: 9am-3pm on both days

Where: Data Science Initiative, Shields Library, UC Davis campus.

Cost: there is no fee.

Host: C. Titus Brown and Jessica Mizzi; contact Jessica Mizzi with any questions.

This workshop is open to everyone, including graduate students, postdocs, staff, faculty, and community members. We have extra space for UC Davis VetMed affiliates; contact the Jessica Mizzi if you are an SVM affiliate.

Description

This two-day hands-on workshop will introduce biologists to Project Jupyter (formerly IPython Notebook). We will assume some minimal experience with Python, but people new to IPython Notebook/Project Jupyter are welcome to attend!

Project Jupyter is a literate data analysis environment (similar to knitr and Shiny) that supports over 40 different programming languages, including R and Python both. It can be used to build reproducible analyses for publication, collaborate over distances on data analysis, and build interactive tutorials and homeworks around data analysis.

Topics overview

On the first day, we will start with a hands-on tour of Project Jupyter in Python.

The remaining day and a half will be devoted to hands-on experimentation with Project Jupyter features and plugins, including:

  • d3.js / JavaScript widgets inside of notebooks;
  • building plugins;
  • writing slideshows;
  • JupyterHub
  • independent challenge exercises.

Schedule

  • Thurs, 9am-noon: Introduction to Project Jupyter.
  • Thurs, noon-1pm: lunch
  • Thurs, 1-3pm: open working time
  • Fri, 9am-noon: open working time
  • Fri, noon-1pm: lunch
  • Fri, 1pm-3pm: open working time

Computer requirements

Attendees will need to bring a computer with a Web browser, an Internet connection, and an ssh client; Windows users should install MobaXterm before the workshop.

Installation/Preparation Instructions

  1. Following the instructions here, install Python. The instructions for Windows, Mac, and Linux are at the bottom of the page.
  2. Sign up for an account at GitHub if you do not already have one.
  3. Sign up for an account at Amazon Web Services (this will be used if there is a problem with Python or Anaconda installation).
LICENSE: This documentation and all textual/graphic site content is licensed under the Creative Commons - 0 License (CC0) -- fork @ github. Presentations (PPT/PDF) and PDFs are the property of their respective owners and are under the terms indicated within the presentation.