Data Science Tutorials

Subsetting datasets is a crucial skill for any data professional. Learn and practice subsetting data in this quick interactive tutorial!

In this tutorial, you'll learn with the help of an example how "Contingency Analysis" or "Chi-square test of independence" works and also how efficiently we can perform it using R.

Learn the techniques to deal with an imbalanced dataset.

Networks today are part of our everyday life. Let's learn how to visualize and understand a social network in Python using Networks.

This tutorial takes course material from DataCamp's Cleaning Data in Python course and allows you to clean strings using regular expressions.

This tutorial takes course material from DataCamp's free Intro to R course and allows you to practice Factors.

Learn about the basic statistics required for Data Science and Machine Learning in Python.

Practice Lists in R by using course material from DataCamp's Intro to R course.

When you know how many times you want to repeat an action, a for loop is a good option. Master for loops with this tutorial.

In this tutorial, you're going to learn how to implement customer segmentation using RFM(Recency, Frequency, Monetary) analysis from scratch in Python.

In this tutorial, you will learn how to analyze and display data using Tableau and make better, more data-driven decisions.

In this tutorial, you will learn how to use a very unique library in python, TPOT. The reason why this library is unique is that it automates the entire Machine Learning pipeline and provides you with the best performing machine learning model.