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

Co-founder and CEO of DataCamp

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

Data Science Instructor at DataCamp

This course provides a basic introduction to clustering and dimensionality reduction in R from a machine learning perspective.

Senior Data Scientist, Boeing

Learn to train and assess models performing common machine learning tasks such as classification, regression and clustering.

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

Data Scientist and cofounder of Science Craft

Learn to explore your data so you can properly clean and prepare it for analysis.

Director of Course Development at DataCamp

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

Master fundamental techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Data Scientist at RStudio

Strengthen your knowledge of the topics you learned in Intermediate R with a ton of new and fun exercises.

Learn the core techniques necessary to extract meaningful insights from time series data.

Assistant Professor at Cornell University

Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.

Author of data.table

Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.

Chief Scientist at RStudio, author of ggplot2, dplyr, and tidyr

Learn the language of data, study types, sampling strategies, and experimental design.

Associate Professor at Duke University

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

PhD in Electrical Engineering and Computer Science from M.I.T.

Learn to create interactive analyses and automated reports with R Markdown.

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

Assistant Professor at Smith College

This course was designed to get you up to speed with the most important and powerful methodologies in statistics.

DeWitt Wallace Professor of Mathematics, Statistics, and Computer Science at Macalester College

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Professor of Statistics at the University of Pittsburgh

Take your data visualization skills to the next level with coordinates, facets, themes, and general best practices in ggplot2.

Learn how to parse data in any format. Whether it's flat files, statistical software, databases, or date right from the web.

Learn the basics of the important features of the RStudio IDE.

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Data Scientist at Data Robot and co-author of caret

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Assistant Professor of Statistics at Reed College

Learn the bag of words technique for text mining with R.

Assistant Vice President of Innovation at Liberty Mutual Insurance

Learn to apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Data Scientist at DataCamp

This course will show you how to combine data sets with dplyr's two table verbs.

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

Creator of xts and quantmod

Learn the practice of drawing conclusions about a population from a sample of data, a process known as statistical inference.

Professor at Pomona College

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Professional Quantitative Analyst and R programmer

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

Professor of Finance and Econometrics at Vrije Universiteit Brussel and Amsterdam

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Assistant Professor at Oregon State University

Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

Use your data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Data Scientist, Stack Overflow

This course covers some advanced topics including strategies for handling large data sets and specialty plots.

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

Instructor at DataCamp

Further your knowledge of RStudio and learn how to integrate Git, LaTeX, and Shiny

In this follow-up course, you will expand your stat modeling skills from part 1 and dive into more advanced concepts.

Strengthen your knowledge of the topics covered in Manipulating Time Series in R with xts and zoo using real case study data.

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Analyst at DV Trading and co-author of PortfolioAnalytics R package

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Vice President at Compass Lexecon

Use a rich baseball dataset from the MLB's Statcast system to practice your data exploration skills.

Assistant Professor at the University of Florida

Learn about how dates work in R, and explore the world of if statements, loops, and functions. You'll practice this knowledge u...

Learn how to pull character strings apart, put them back together and use the stringr package.

Learn how to access financial data from local files as well as from internet sources.

Senior Quantitative Analyst and member of R/Finance Conference committee