IPython and Jupyter in Depth: High productivity, interactive Python | Tutorials
IPython and Jupyter provide tools for interactive computing that are widely used in scientific computing, education, and data science, but can benefit any Python developer. You will learn how to use IPython in different ways, as: an interactive shell, a graphical console, a network-aware VM (Virtual machine) in GUIs, a web-based notebook combining code, graphics and rich HTML. We will demonstrate how to deploy a custom environment with Docker that not only contains multiple Python kernels but also a couple of other languages.
Matthias Bussonnier
Matthias is PostDoc at UC Berkeley Institute for Data science, and have been a core Developer of IPython and Jupyter for a couple of years. With a background in Physics Matthias spend most of his time developing tools for the scientific community and for education as well as promoting Python 3.
Mike Bright
Solution Architect at Hewlett-Packard Enterprise working in the EMEA OpenNFV lab (Cloud Computing for Telecom), based in Grenoble France.Passionate about Containers, Orchestration and Programming Languages.Runs the Grenoble Python User Group.Like to travel, danse (Argentinian Tango, Salsa, Rock)
Min Ragan-Kelley
Min has been a core developer of IPython (and now Jupyter) since 2006. He holds a PhD from UC Berkeley in Applied Science & Technology, with an emphasis in computational plasma physics. He now works as a postdoctoral researcher at Simula Research Laboratory in Oslo, Norway, on the Jupyter and OpenDreamKit projects, focusing on JupyterHub and the Jupyter protocols for interactive computing.
Room 7
Thursday, 18th May, 09:00 - 12:20
