Quick instruction on how to get instructions and install required packages, get data... Fallback on online hosting for users if can't get to work on laptop.

(We'll continue installation during next section)

- What are the different pieces, how to get help after the tutorial.

- Jupyter

- JupyterHub

- Notebook interfaces.

- Kernels

- Extensions (difference between kernel, front-endand server extension, we'll only explore IPython kernel extension later in the tutorial)

- Binder

- Moving toward Python 3 only, already he case for many pieces

- Difference between notebook and JupyterLab

- Overview what's New in JupyterLab, what's the difference with Classic Notebook.

- Complete compatibility. You can install both at the same time.

- Same file format, same protocol...

- Online hosted platforms

- Azure, Coclac, Colab, ...

- Other frontends

- Nteract Vs Code, Atom,

- Whats new in Python, and how IPython/Jupyter make best use of it (will detail in later sections)

- Beyond Python:

- magic commands, shell access, object introspection.

- integration with top-level async code in Python 3.6+

- superhelp `?` / `??`

- system command `!`

- Tab completion

- Tools for typical development tasks: timing, profiling, debugging.

We will leave 1 to 2 minutes hands-on for simple subjects like object

introspection and variable caching.

- Demo and discussion of the last added features of the command line interpreter.

- `IPython.embed`: a useful 'microscope' into your own scripts.

- Customizing IPython with profiles.

We'll leave 5-10 minutes at the end of this section for user to play

with multiple features of IPython.

- Couple of exercise to get user acclimated to JupyterLab and notebook Interfaces, keyboard shortcut.

- Plan a couple of advance written exercises showing-off advance features for user already familiar with new interface.

- Basic concepts: the server, the dashboard, your notebooks.

- A notebook as a rich document: text, code, results and multimedia.

- Sharing your notebooks: [nbviewer](http://nbviewer.ipython.org), MyBinder.org

- Converting notebooks to other formats for sharing, blogging and publication.

We'll interleave this presentation with few minutes breaks and try to ask user to achieve a specific state before showing them how to achieve it.

In this section we'll have user customize their own code to make full use of the Jupyter and IPython capabilities.

- The IPython display protocol: `__repr__` for more than just text.

- make full use of the display protocol to get a visualisation.

- Discuss and work with widgets.

- How widgets can bring interactivity to visualisation and analysis.

- Create an IPython extension, and register magics.

- This should show the basic of cross-language integration.

- Make use of magic to run a cross language analysis.

Further resource and conclusion (if time permit)