Course Description

  • Why use NumPy?
  • NumPy Arrays
  • Array Math
  • Array Indexing
  • Advanced Indexing
  • Broadcasting

Hello Everyone! In this course, we will cover the basics of using numbers and have several interactive course videos that will challenge you to learn how to use NumPy. I've also included a Python course as bonus content, in case you haven't used Python before.

NumPy is a powerful library for numerical computing in Python. It provides support for multidimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. By mastering NumPy, you will be able to efficiently perform numerical computations for data science, machine learning, and scientific research.

Why use NumPy?

NumPy is widely used in the data science community for its efficiency and ease of use. It allows for fast computation of large arrays and provides a wide range of mathematical functions for data manipulation.

NumPy Arrays

NumPy arrays are the core data structure in NumPy. They are homogeneous, multidimensional containers that allow for efficient storage and manipulation of numerical data.

Array Math

NumPy provides a wide range of mathematical functions for performing operations on arrays. These functions are optimized for performance and allow for efficient computation of complex mathematical operations.

Array Indexing

Array indexing in NumPy allows for easy access and manipulation of array elements. You can use slicing, fancy indexing, and boolean indexing to select specific elements or subsets of an array.

Advanced Indexing

Advanced indexing in NumPy allows for more complex selection of array elements. You can use integer arrays, boolean arrays, and arrays of indices to select elements based on specific conditions.


NumPy broadcasting allows for efficient computation of operations between arrays of different shapes. This feature automatically aligns arrays of different dimensions to perform element-wise operations.

By the end of this course, you will have a solid understanding of NumPy fundamentals and be able to apply this knowledge to your data science projects. Join us on this learning journey and unlock the power of NumPy for your data analysis needs.