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

<h2 style="font-size:1.1em">Chapter Goals:</h2>
<ul>
  <li>Learn about indexing arrays in NumPy</li>
  <li>Write code for indexing and slicing arrays</li>
</ul>

<h2>Chapter Goals:</h2>
<ul>
  <li>Learn about indexing arrays in NumPy</li>
  <li>Write code for indexing and slicing arrays</li>
</ul>

Index into NumPy arrays to extract data and array slices.

What is Data Science?

Applications of Data Science

Overview of Libraries

Data Manipulation with NumPy

Data Analysis with pandas

Probability and Statistics

Conclusion

Indexing

Chapter Goals: