Data Analysis Tutorials

Master SQL for Data Reporting & daily data analysis by learning how to select, filter & sort data, customize output, & how you can report aggregated data from a database!

Get introduced to Asymptotic Analysis. Learn more about the complexity of the algorithm as well as asymptotic notation, such as Big O, Big θ, and Big Ω notation. Along with the examples of complexity in a different algorithm.

In this tutorial, you'll learn how to use R PCA (Principal Component Analysis) to extract data with many variables and create visualizations to display that data.

Cluster analysis is an important problem in data analysis. Data scientists use clustering to identify malfunctioning servers, group genes with similar expression patterns, or various other applications.

In this tutorial, you will learn the basics behind a very popular statistical model; the linear regression.

This article covers how and when to use Random Forest classification with scikit-learn. Focusing on concepts, workflow, and examples. We also cover how to use the confusion matrix and feature importances.

Start analyzing titanic data with R and the tidyverse: learn how to filter, arrange, summarise, mutate and visualize your data with dplyr and ggplot2!

Learn how you can parse, explore, modify and populate XML files with the Python ElementTree package, for loops and XPath expressions.

Dive into the lyrics of Prince's music with R: use text mining and Exploratory Data Analysis (EDA) to shed insight on The Artist's career.

Get Google Trends data of keywords such as 'diet' and 'gym' and see how they vary over time while learning about trends and seasonality in time series data.

In this Kaggle tutorial, you'll learn how to approach and build supervised learning models with the help of exploratory data analysis (EDA) on the Titanic data.

Discover why you should use Amazon Web Services Elastic Compute Cloud (EC2) and how you can set up a basic data science environment on a Windows instance.