Learn the basics of data science and how to work with important libraries such as NumPy, pandas, Beautiful Soup, etc.

Become a Data Scientist

This module will get us familiar with the state of data science and its fundamental concepts. We'll be going through the applications of data science and a few libraries which are essential to solve any problem in this field, such as Beautiful Soup, Scrapy, NumPy, pandas, spaCy, etc.
We'll also learn about data manipulation with NumPy as well as probability and statistics.
By the end of this module, we'll have basic and essential knowledge of data science and its libraries.

Getting Started with Data Science

# NumPy array creation operations

## `np.empty`
It creates a NumPy array of specified shape and size without initializing it.

## `np.eye`
It creates a 2-dimensional NumPy array with diagonal entries as ones and the rest as zeros. It takes in a parameter `k`, which is zero by default. This means that the main diagonal entries are made as one. A positive value indicates making the upper diagonal entries as one, and a negative value indicates making the lower diagonal entries as one.

## `np.identity`

It makes an identity array. An identity array is a square array, meaning the number of rows and columns is equal to one on the main diagonal.

## `np.linspace`

It returns an evenly spaced array over a specified interval, with a start and stop value defining the first and last elements in the sequence. The inclusion of the stop value can be controlled using a parameter, which allows it to be included or excluded. This will be discussed further in the coding example.

## `np.ones`

It makes an array of a specified shape and size initialized with only ones.

## `np.zeros`
 
It makes an array of specified shape and size initialized with only zeros.


# Coding exercise






Explore NumPy in more detail, along with the functions used to operate on arrays.


NumPy Array Creation

Explore NumPy in more detail, along with the functions used to operate on arrays.

Numpy Array Creation

NumPy array creation operations

np.empty

np.eye

`np.empty`

`np.eye`