Data Science Tutorials

Develop your data science skills with tutorials in our blog. We cover everything from intricate data visualizations in Tableau to version control features in Git.

Discover categories

Training 2 or more people?Try DataCamp for Business

Trae AI: A Guide With Practical Examples

Learn what Trae AI is, its features, pricing, installation process, practical applications, and how it compares to Cursor AI.

Bex Tuychiev

July 29, 2025

Matrix Diagonalization: A Comprehensive Guide

Understand when and how matrices can be diagonalized, and why it matters for data science and computational linear algebra.

Arunn Thevapalan

July 29, 2025

dbt Snapshot: A Comprehensive Tutorial

Learn what a dbt snapshot is, how to create one, and how to configure it to track your data changes in this tutorial.

Austin Chia

July 28, 2025

How to Change Date Format in Excel: What You Need to Know

Learn how to create a bar graph in Excel with this beginner-friendly guide. Explore chart types, formatting tips, dynamic features, and troubleshooting techniques.

Laiba Siddiqui

July 28, 2025

Qwen Code CLI: A Guide With Examples

Learn how to set up and use Qwen Code CLI for agentic coding tasks, including codebase exploration, refactoring, and more.

Aashi Dutt

July 28, 2025

KL-Divergence Explained: Intuition, Formula, and Examples

Explore KL-Divergence, one of the most common yet essential tools used in machine learning.

Vaibhav Mehra

July 27, 2025

Introduction to Maximum Likelihood Estimation (MLE)

Learn what Maximum Likelihood Estimation (MLE) is, understand its mathematical foundations, see practical examples, and discover how to implement MLE in Python.

Vaibhav Mehra

July 27, 2025

Excel UNIQUE(): The Fastest Way to Filter Duplicates

Discover how to use the Excel UNIQUE() function to instantly remove duplicates and extract distinct values from any list. Learn how to apply it to both rows and columns.

Josef Waples

July 25, 2025

P-Hacking: How to (Not) Manipulate the P-Value

Dive deep into the world of p-hacking, where manipulating the p-value is tempting. Learn the different traps of p-hacking, and how to detect and prevent them.