Physics 39: Scientific Computing with Python

This “book” is a collection of course notebooks that cover the main topics in the course. The notebooks themselves are available on my github page (see the syllabus for the link).

The course and notes are organized as follows:

• Topic 0: Introduction
• Topic 1a: Basics of Python
• Topic 1b: Functions and Basic Operations
• Topic 2a: numpy
• Topic 2b: Mathematical Operations in Numpy
• Topic3: Plotting and Data Visualization
• Topic 4a: Scipy and Numerical Techniques
• Topic 4b: Integration
• Topic 4c: Solving Ordinary Differential Equations
• Topic 5: Intro to Data Analysis
• Topic 6a: Bayes’ Theorem
• Topic 6b: Intro to Machine Learning
• Topic 6c: Monte Carlo Methods
• Topic 6d: Symbolic Computing