R Programming Learn about fundamental data types, logic, and how to create your own functions using the R language. Learn More
Importing & Cleaning Data with R Learn how to parse data from flat files, statistical software, databases, websites, and more. Learn More
Introduction to R Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.
Intro to SQL for Data Science Master the basics of querying databases with SQL, the world's most popular databasing language.
Intermediate R Continue your journey to become 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 Visualization with ggplot2 (Part 1) Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.
Importing Data in R (Part 1) In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Data Manipulation in R with dplyr Master techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.
Writing Functions in R Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.
Importing Data in R (Part 2) Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.
Intermediate R - Practice Strengthen your knowledge of the topics you learned in Intermediate R with a ton of new and fun exercises.
Intermediate SQL Server In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.
Joining Data in R with dplyr This course will show you how to combine data sets with dplyr's two table verbs.
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.