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Introduction to R
Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.
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.
Joining Data with dplyr
Learn to combine data across multiple tables to answer more complex questions with dplyr.
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.
Reporting with R Markdown
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
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.
Intermediate Importing Data in R
Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.
Cleaning Data in R
Develop the skills you need to go from raw data to awesome insights as quickly and accurately as possible.
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.
Case Study: Exploratory Data Analysis in R
Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.
Introduction to Statistics in R
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from 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.
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.
Unsupervised Learning in R
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.