Thanks to its world-class data tools and libraries, like Numpy, Pandas, Jupyter, Matplotlib and xarray, Python is becoming the language of choice in many scientific communities from Physics to Climate Science, from Earth Observation to Economy.
A turn-key but less-know component of the scientific ecosystem is the dask library that enable seamless parallel, distributed and GPU computing in most cases without code changes.
We will use climate science as an typical example of a discipline where simple tasks become easily big data problems and where mastering xarray, dask and dask.distributed is the key to turn them back into simple tasks, possibly on a large cluster of VMs (that you can easily provision from your preferred cloud provider).
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in __on Friday 3 May at 17:15 **See schedule**