SENS 01D - Building Skills in Environmental Data Analysis with Python
Description
Level up your data analysis skills!
For anyone working with environmental data, scripting languages are a superpower. They not only expand what you can do, but they also vastly improve how quickly and effectively you can do it. There is a natural progression from doing calculations by hand, to using a calculator, to working in spreadsheets, and finally to using a scripting language. At each stage, however, the barrier to entry can seem higher, and many people find programming intimidating. The key to success is to first get over the initial hurdle of starting, and secondly to integrate this into your workflow so that you use the tools routinely. Once you do, tasks that once took hours can be completed in minutes.
In this course, we will remove that barrier. You will learn the fundamentals of Python for environmental data analysis through hands-on exercises using freely available software. Python is one of the world's most widely used programming languages, with an enormous ecosystem of open-source libraries for data analysis and visualization. Its open-source nature means that it is continually improved by a global community, and thousands of specialized tools are freely available.
By the end of the course you have the foundation needed to continue developing your skills independently, with the support of online resources and modern AI tools, and the confidence to use Python routinely in your day-to-day work.
Course Outline
Learning competencies:During the course, participants will develop the following practical skills:
• Install and run Python on your own laptop.
• Use the JupyterLab interface and create Jupyter Notebooks.
• Perform calculations on a dataset using the NumPy library.
• Read and process time series data using the Pandas library.
• Produce high-quality figures using Matplotlib.
• Perform basic statistical analyses and summarize datasets.
By the end of the course, you will be able to read environmental datasets into Python, explore and analyze the data, perform basic statistical analysis, produce high-quality figures, and know how to save scripts to reproduce your analysis.