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

# Structured Data

It comes with a predefined format and structure. Structured data is usually stored in relational databases. It is easy to deal with in the data science domain.

## Examples 

* Here's a simple table with columns of diverse types. It can be stored in any relational database, Excel file, etc.

|Sepal_length     |Sepal_width     |Petal_length     |Petal_width     |Species     |
| --- | --- | --- | --- | --- |
|  5.1   | 3.5    | 1.4    |0.2     | setosa    |
| 4.9    |  3.0   |  1.4   | 0.2    |  versicolor   |
| 4.7    | 3.2    | 1.3   |  0.2   | setosa    |
| 4.6    |  3.1   | 1.5    | 0.2    | virginica    |







Uncover the details of structured, semi-structured, and unstructured data. Identify how structured data follows a specific format, unstructured data lacks a defined structure, and semi-structured data falls between the two.

Structured vs. Semi-Structured vs. Unstructured Data

Structured Data

Examples