Hello,
Welcome to Numpy Library for Data Science Course
In both cases, you are at the right place! The number of companies and enterprises using Python is increasing day by day. The world we are in is experiencing the age of informatics. Python and its Numpy library will be the right choice for you to take part in this world and create your own opportunities,
Numpy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
Numpy aims to provide an array object that is up to 50x faster than traditional Python lists. The array object in Numpy is called ndarray , it provides a lot of supporting functions that make working with ndarray very easy. Arrays are very frequently used in data science.
In this course, we will open the door of the Data Science world and will move deeper. You will learn Numpy step by step with hands-on examples. Most importantly in Data Science, you should know how to use effectively the Numpy library. Because this library is limitless.
In this course you will learn;
Introduction and Installation
Similarities and difference in a list and an array
Declare an array
Array function in numpy library
arange function
ones, zeros and empty function
linspace function
identity and eye function
Attributes of array
Indexing in array
Slicing in array
Arithmetic operators in an array
reshape and resize function in an array
flatten function in an array
ravel function in an array
transpose function
swapaxes function
Concatenate function
Different matrices function like finding inverse , matix multiplication etc.
This course will take you from a beginner to a more experienced level.
If you are new to data science or have no idea about what data science is, no problem, you will learn anything from scratch you need to start data science.
If you are a software developer or familiar with other programming languages and you want to start a new world, you are also in the right place. You will learn step by step with hands-on examples.
See you in the course!
