Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language. And it boasts a rich set of libraries for working with data.
We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research.
Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.
Programming concepts and techniques
Basic syntax, control structures and data types in Python
How to import powerful libraries that support numerical analysis (NumPy) and visualisation (Matplotlib)
Approaches to debugging, testing and defensive programming
How to blend code, output and documentation with Jupyter notebooks