16^th Advanced Scientific Programming in Python

You should be familiar with the following materials to participate:

• Python scientific computing ecosystem
  
• The Python language
  
• NumPy: creating and manipulating numerical data
  
• Getting help and finding documentation
  

The first eight chapters from the The Software Carpentry git introduction:

• Automated Version Control
• Setting up git
• Creating a Repository
• Tracking Changes
• Exploring History
• Ignoring Things
• Remotes in GitHub
• Collaborating

Additional materials for the curious:

• Python Tutorial - short, easy and comprehensive introduction to Python for programmers
• Python Challenge - are you already a Python guru? Challenge your Python knowledge with the Python puzzles.
• Library Reference - complete reference to Python standard library
• Dive into Python 3
• Python Introduction, Resources and FAQs - a catalogue of introductory python materials