Data Science Tutorials

Many Python users are familiar with using asterisks for multiplication and power operators, but in this tutorial, you'll find out additional ways on how to apply the asterisk.

To be an adept data scientist, one must know how to deal with many different kinds of data. Learn to read various formats of data like JSON and HTML using pandas.

Go through the ten most important updates introduced in the newly released TensorFlow 2.0, and learn how to implement some of them.

Learn how to use spreadsheets to calculate an inventory demand model that helps determine how much inventory a business should hold moving forward.

In this tutorial, you will learn why it is important to pre-process data and how to do it in pandas.

In this tutorial, learn how to parse one or more arguments from the command-line or terminal using the getopt, sys, and argparse modules.

Learn how to apply operations like add, subtract, divide, multiply, and a lot more in Google Spreadsheets with the help of an actual dataset.

Learn how to utilize conditional formatting with one or multiple conditions and how to color cells by custom criteria with the help of a dataset.

Learn how to store the results of a query with the help of materialized views in PostgreSQL.

Learn how to use Python and R in conjunction with each other to utilize the best of both in a single data science project.

In this tutorial, you'll learn how to create visualizations to display data and gain more meaningful insights with spreadsheets.

In this tutorial, you'll learn techniques on how to clean messy data in SQL, a must-have skill for any data scientist.