Introduction to Python

A series of 3 Jupyter notebooks for Python beginners with emphasis on physics. No previous experience required, though familiriaty with college-level physics will help. Intended for Berkeley physics undergrads to help them use Python in their coursework.

The intended order of notebooks is:

1. Intro to Python.ipynb
2. Intro to numerics.ipynb
3. Intro to stats.ipynb

Please fill out the feedback survey here after completing the tutorials

Click here to open the first notebook at datahub.berkeley.edu. This will ask you log in via CalNet, then create a Jupyer server for you, clone this repository to your account on DataHub, and then launch and direct you to the first notebook. You can also run the notebooks in your own environment by cloning/downloading this repo and launching the Jupyter notebooks. For more information see the first notebook.

This series of notebooks is intended to

• introduce you to concepts and paradigms that are commonly used when programming
• introduce you to the syntax and quirks of Python and NumPy
• give you a rough idea of the advantages and limitations of numerical computation
• convince you of the power/utility of numerics
• show you how to use some commonly used techniques and tools
• help you get over the intial intimidation of learning how to code
• force you to learn how to read documentation, and help you get over the fear of unknown packages
• give you the ability and confidence to solve new problems yourself

This is NOT supposed to be a comprehensive guide to all numerical coding in Python.

Other (better) Berkeley resources

• CS 61A
• Physics 77
• Python for astronomers
• Python practice