NumPy is a powerful python library that provides N-dimensional arrays and functions to perform scientific computing. In this course, you’ll learn the basics of NumPy, its data types and attributes, and NumPy array creation in different scenarios.
NumPy, which is short for Numerical Python, is a very crucial library of Python when working in the field of data science. In this course, Getting Started with NumPy, you'll learn everything about NumPy and the N-dimensional array (ndarray). First, you'll start by understanding what NumPy is and do an in-depth study on its history, purpose, usage, advantages, etc. Next, you'll see how to install the NumPy library into your system. Then, you'll take a look into ndarray and study its attributes and some basic but important functions. Finally, you'll dive into creating NumPy arrays in different ways, like creating an empty array, an array with a specified range, or an array from existing data, depending upon your requirements. When you’re finished with this course, you'll have a good understanding of NumPy and ndarray with the skills to create and maintain ndarray in various scenarios, and will be ready to move on to the next step where you can perform complex scientific computations using NumPy functions or use ndarray as an input in other Python libraries.
NumPy, which is short for Numerical Python, is a very crucial library of Python when working in the field of data science. In this course, Getting Started with NumPy, you'll learn everything about NumPy and the N-dimensional array (ndarray). First, you'll start by understanding what NumPy is and do an in-depth study on its history, purpose, usage, advantages, etc. Next, you'll see how to install the NumPy library into your system. Then, you'll take a look into ndarray and study its attributes and some basic but important functions. Finally, you'll dive into creating NumPy arrays in different ways, like creating an empty array, an array with a specified range, or an array from existing data, depending upon your requirements. When you’re finished with this course, you'll have a good understanding of NumPy and ndarray with the skills to create and maintain ndarray in various scenarios, and will be ready to move on to the next step where you can perform complex scientific computations using NumPy functions or use ndarray as an input in other Python libraries.
