NumPy: Fundamentals Of Python Data Science

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NumPy is written specifically for working with large quantities of numbers. It can be used by itself, but it’s also at the core of the most popular data science and machine learning packages, like Pandas and TensorFlow.

NumPy has a strong focus on performance. For this reason, NumPy is written mainly in a low-level programming language called C. It offers easy-to-use bindings for us Python users, so we don’t have to worry about low-level stuff.

In this course, you will learn NumPy from the ground up. We cover all the essential concepts and work up to some pretty advanced topics.

You won’t regret learning NumPy using this course if you are serious about:

  • Scientific computing
  • AI and machine learning
  • data science and data analysis

It offers a great starting point and lays a solid foundation to build on.

Several examples in this course use synthetical crypto currency data. You can download this data below:

Disclaimer: The cryptocurrency data presented here is entirely artificial; any resemblance with actual prices and volumes is coincidental. No example where such data is manipulated constitutes investment or trading advice.

Course Content

Introduction
Linear Algebra Basics
Array Fundamentals
Working with multidimensional arrays
Our example dataset and basic plotting
ndarray methods
Array Axes
Vectorized Computing
Universal Functions (ufuncs)
Advanced array manipulation
Randomness
Selected Topics in Mathematics and Statistics