Introduction to R
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
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 collection of data science tools within R.
Data Manipulation with dplyr
Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.
Joining Data with dplyr
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Introduction to Statistics in R
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.
Introduction to Data Visualization with ggplot2
Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.
Intermediate Data Visualization with ggplot2
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
Data Communication Concepts
No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.
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.
Cleaning Data in R
Learn to clean data as quickly and accurately as possible to help your business move from raw data to awesome insights.
Working with Dates and Times in R
Learn the essentials of parsing, manipulating and computing with dates and times in R.
Introduction to Writing Functions in R
Take your R skills up a notch by learning to write efficient, reusable functions.
Exploratory Data Analysis in R
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
Introduction to Regression in R
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Intermediate Regression in R
Learn to perform linear and logistic regression with multiple explanatory variables.
Hypothesis Testing in R
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Experimental Design in R
In this course you'll learn about basic experimental design, a crucial part of any data analysis.
Supervised Learning in R: Classification
In this course you will learn the basics of machine learning for classification.
Supervised Learning in R: Regression
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
Prepare for certification by completing this track, or target the lessons you need with a personal learning plan.Learn More