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

# Beautiful Soup

Have you ever wondered how people extract data from the public web and analyze it? They use libraries and other resources that ease the process of extracting the data from the public web. Beautiful Soup is the library that is meant for such purposes. The data science community has used it for a long time to scrape data from the public web because it pulls data from HTML and XML files. It has comprehensive documentation that makes it easy to use.    


Web pages are made up of HTML (Hypertext Markup Language). Beautiful Soup gets the data straight out of it by specifying the individual elements of HTML. 

Below is an example of how HTML markup is built and an overview of its different tags:








Learn how Beautiful Soup is used to extract data from the public web.

Beautiful Soup (Scraping Data from Simple HTML)

Beautiful Soup