Dhavide Aruliah
Dhavide Aruliah has been teaching & mentoring both in academia and in industry for three decades. His career has grown around bringing learners from where they are to where they need to be mathematically & computationally. He was a university professor (Applied Mathematics & Computer Science) at Ontario Tech University before moving to industry where he oversaw training programs supporting the PyData stack at Anaconda Inc. and later at Quansight LLC. He has taught over 40 undergraduate- & graduate-level courses at five Canadian universities as well as numerous Software Carpentry, SciPy, & PyData tutorial workshops. Here are some examples of his past tutorials & talks:
Sessions
The goal of this tutorial is to give you hands-on experience accessing & using NASA Earthdata Cloud — i.e., freely available satellite data — through Pythonic APIs. Ideally, you are a data-curious Pythonista who wants to use NASA data products for geospatial analysis. Modest experience with the PyData stack is expected, but you'll be walked through particular corners of the relevant libraries (e.g., Xarray, Rasterio, Hvplot, etc.) as required. You'll need only a web browser & a network connection to connect to a pre-configured cloud computing environment. The case studies you'll explore — floods & wildfires — highlight strategies for "data-proximate computing," i.e., using cloud-compute resources with distributed data. At the end, you'll be set up to carry out your own explorations of NASA's publicly available earth data in Python.