Module 3: NumPy
Vector Programming and Numerical Computing
This module introduces NumPy, Python’s main library for numerical computing. You will learn to represent numerical data with arrays, operate on entire arrays at once, simulate random processes, and apply linear algebra to practical problems.
NumPy has hundreds of functions, and nobody expects you to remember them. In this module you will see some of what NumPy can do, so that you know which kinds of operations exist. In the exams you will have a cheat sheet with the functions you need.
What you must master is the core, which is common to every function and submodule: how to work with arrays, their shape, their dimensions, their axes, and how to index them.
Session Structure
Session 14:
Session 15:
Array Arithmetic and Broadcasting Array Functions
Session 16:
Session 17:
Session 18:
Masking: Sets and Logic Masking with Images Extra practice: Masking with the Cardboard
Session 19:
Random Numbers and Fancy Indexing
Session 20:
Session 21:
Session 22:
Session 23:
Practice and Review
Side Projects
Want to get extra credit? Try one of the NumPy side projects. They work like the side projects of Module 2, and they are not part of the session schedule.