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


# Statistics

Statistics is a form of mathematical analysis that uses different tools on a given data set to describe and make an inference from it. 

# Types of statistics 

Statistics is further divided into two branches: descriptive and inferential

## Descriptive statistics

Descriptive statistics deals with summarizing and describing the data at hand. Descriptive statistics comes up with the following things to make sense out of the data.


### Elements of descriptive statistics

Learn about statistics, which focuses on methods for collecting, analyzing, and describing data.


Statistics

Learn about statistics, which focuses on methods for collecting, analyzing, and describing data.