Gain insights into utilizing NumPy for data manipulation and analytics. Learn about implementing concepts in both Python and NumPy through coding challenges and quizzes.

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If you're looking to grow your career in machine learning or data science in this day and age, adding a powerful library to your skill set is an important place to start. In that vein, Python has become one of the most widely used tools in the industry for serious data analytics, and NumPy is probably the most widely used data analytics library. With NumPy, you can manipulate data involving multi-dimensional arrays and matrices (think linear algebra).

Join us as we venture into the vast world of NumPy in this comprehensive course. Each lesson dive into the actual implementation of concepts in both pure Python and then NumPy, exploring how NumPy vectorization compares to traditional Python that uses a procedural and object-oriented approach.

Practice and test yourself along the way with in-browser coding challenges, quizzes, and more.

This course is intended for users who are already familiar with intermediate level Python.

From Python to Numpy

## What is Uniform Vectorization?

> *Uniform vectorization* is the simplest form of vectorization where all the
elements share the same computation at every time step with no specific processing for any element.



One stereotypical case is the **Game of Life** that has
been invented by John Conway  and is one of the earliest examples of
cellular automata(see below). Those cellular automata can be conveniently regarded as
an array of cells that are connected together with the notion of neighbors and
their vectorization is straightforward.


Let me first define the game and we'll
see how to vectorize it!


# What is Uniform Vectorization?

> *Uniform vectorization* is the simplest form of vectorization where all the
elements share the same computation at every time step with no specific processing for any element.



One stereotypical case is the **Game of Life** that has
been invented by John Conway  and is one of the earliest examples of
cellular automata(see below). Those cellular automata can be conveniently regarded as
an array of cells that are connected together with the notion of neighbors and
their vectorization is straightforward.


Let me first define the game and we'll
see how to vectorize it!


This lesson discusses uniform vectorization and introduces the next case study that we are going to look at, i.e, Game of life. 

Introduction

Anatomy of an Array

Code Vectorization

Problem Vectorization

Custom Vectorization

Beyond NumPy

Conclusion

Uniform Vectorization

What is Uniform Vectorization?