This is a course for scientists, engineers, and analysts working with geospatial data sets.
Familiarity with spatial analysis concepts is assumed. No prior experience with programming (in any language) is assumed.
By the end of the course, you will have all the knowledge you need to start programming competently in Python for scientific and engineering applications, with a focus on geospatial applications. You will know what's available with Python and how to use its powerful data types and amazing libraries to write clean, efficient code. You will have had experience with using Python for various scientific data manipulation tasks and solving a range of analytical tasks, including easily creating beautiful plots, performing Monte Carlo simulations, constructing statistical models, regression, optimisation, analysing images, time-series data, geospatial data, and plotting statistical data on maps.
Day 1 covers the basics of using the Python language and standard library, with a focus on scientific and engineering applications, including tips and tricks for making this easy.
Day 2 gives a comprehensive introduction to reading and writing the most important data formats in science and engineering and how to analyse and visualise data easily.
Day 3 teaches the use of Python for numerical and scientific computing. It covers array and matrix manipulation, working with labelled and tabular data, an overview of available scientific routines, and creating simple but beautiful 2D plots, with the packages NumPy, SciPy, and Matplotlib.
Day 4 focuses on techniques for creating larger codebases in teams, interfacing Python with other data sources, scaling from small datasets and small problems to realistic ones that may be too big for memory or too slow for one computer to process.
Maps are a powerful tool for data visualisation. Spatial data is ubiquitous and location analytics are more important than ever. A well drawn map is not only beautiful to look at, but can change how you see the world. In the last 10 years Python has become the go-to language for spatial science. This day will provide a tutorial in working with geospatial data using Python. It will cover spatial data access, spatial analysis, and visualising the results on a map.
We also encourage you to supply your own data sets for us to use in the course if you wish.
We will supply you with printed course notes and a USB stick containing a complete Python environment based on VirtualBox. This saves time in the course and allows us to focus on using Python rather than installing it. The USB stick also contains kitchen-sink Python installers for multiple platforms, solutions to the programming exercises, several written tutorials, and reference documentation on Python and the third-party packages covered in the course.
We also offer custom courses on-site for teams within organisations. These are particularly appropriate if your team uses particular tools or data sources in its workflow. Please contact us to discuss your requirements.