This series of tutorials is being delivered as part of the data bootcamp ahead of the NASA Space Apps Event 2022 hosted in Exeter by the Joint Centre of Excellence in Environmental Intelligence and TechExeter. The data bootcamp consist of three sessions:
In this session you will learn about useful Python packages for working with environmental datasets and work through some basic examples for loading and exploring different types of data.
In this session, you will be given a brief introduction to machine learning and have the opportunity to work through a simple (cloud computing) example, specifically using some readily available weather data.
In this session, you will be given a brief overview of the types of data we have available within the Met Office. These datasets are open source, you'll have the oppertunity download and explore this data through the example notebooks provided. This will give you the tools to explore weather and climate data yourself.
We will assume you have some experience with programming langauges and ideally have a little bit of knowledge of python. There are a lot of excellent resources on the internet for learning python. This short series of tutorials condenses the most important parts for working specifically with enviromental datasets and provides an overview of tools to make this easier. For a more in depth understanding of python, exploring these exellent tutorials is recommended:
- Software Carpentry: https://swcarpentry.github.io/python-novice-inflammation/index.html
- DataCamp: https://www.datacamp.com/courses/intro-to-python-for-data-science
Some of these tutorials require some python package management, we have done this through Conda. If you don't have Conda, install miniconda here. If you prefer other package management methods please feel free to use them. More information about package management for each session will be contained in the README of that folder.
Development of these tutorials was funded by the Joint Centre for Excellence in Environmental Intelligence.
