Scientific
Computing using Python (image)

Support material used in this course

Slides - as used in lectures
Textbook - background reading for this module
Snippets: files that have been developed during lectures
Installation of Python on your own machine
Notes on Spyder, and recommended steps for beginners
Introduction to IPython Notebook (html, ipynb)
- More details about the IPython Notebook (html, ipynb)
Introduction and brief reference for Matplotlib (html, ipynb)
Introduction to Testing (html, ipynb)

Other support material

Official Python Tutorial
MIT Course Introduction to Computer Science and Programming (providing videos and podcasts, thorough introduction to Python from computer science point of view).
First steps using the Python debugger (pdb)
Very nice overview of matplotlib (in ipython notebook)
Python Style Guide (PEP8)
Python Docstring Guide (PEP257)

Additional (brief) materials

Talk on how YouTube is built around Python
Why floating point number representation usually works, but not always: Floating point numbers are a leaky abstraction
Using Eclipse environment and Python
How to format source code: Code like a Pythonista: Idiomatic Python

Additional material (reference)

Google Python Style Guide
The Hitchhikers guide to Python
Another lecture course for Scientific Python
Another Python Course
Google's course on Computational Thinking (in Python)
Another introduction to computational modelling using Python: http://software-carpentry.org/
Interactive Python tutorials: http://interactivepython.org
How to think like a Computer Scientist (interactine): http://interactivepython.org/courselib/static/thinkcspy/index.html