Old Version Importing & Cleaning Data with R Learn how to parse data from flat files, statistical software, databases, websites, and more. Learn More

Machine Learning Fundamentals in R Predict categorical and numeric responses via classification and regression, and discover the hidden structure of datasets with unsupervised learning. Learn More

Introduction to R Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

Intermediate R Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

Introduction to the Tidyverse Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collect...

Data Manipulation in R with dplyr Master techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Introduction to Importing Data in R In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Data Visualization with ggplot2 (Part 1) Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

Exploratory Data Analysis in R Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Supervised Learning in R: Classification In this course you will learn the basics of machine learning for classification.

Introduction to Machine Learning Learn to train and assess models performing common machine learning tasks such as classification and clustering.

Intermediate Importing Data in R Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

Supervised Learning in R: Regression In this course you will learn how to predict future events using linear regression, generalized additive models, rand...

Data Analysis in R, the data.table Way Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.

Unsupervised Learning in R This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Data Visualization in R This course provides a comprehensive introduction to working with base graphics in R.

Data Visualization with ggplot2 (Part 2) Take your data visualization skills to the next level with coordinates, facets, themes, and best practices in ggplot2.

Machine Learning with caret in R This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Working with the RStudio IDE (Part 2) Further your knowledge of RStudio and learn how to integrate Git, LaTeX, and Shiny

Machine Learning in the Tidyverse Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.

Data Visualization with ggplot2 (Part 3) This course covers some advanced topics including strategies for handling large data sets and specialty plots.

Importing & Cleaning Data in R: Case Studies In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

Analyzing Survey Data in R Learn survey design using common design structures followed by visualizing and analyzing survey results.

Supervised Learning in R: Case Studies Apply your supervised machine learning skills by working through four case studies using data from the real world.