Learning To Program With R
Presented by Stuart Greenlee
Get started on your path by learning how to install and navigate R, then tackle basic operations like statistical functions, matrix operations, and string functions. As you work through this course, you’ll pick up everything you need to use R for developing statistical software and data analysis tools.

Introduction to Data Science with R
Presented by Garrett Grolemund
Learn the three skill sets of data science: computer programming (with R), manipulating data sets (including loading, cleaning, and visualizing data), and modeling data with statistical methods. Get lots of hands-on experience as you learn how to load, save, and transform data, generate beautiful graphs, and fit statistical models to the data.

Expert Data Wrangling with R
Presented by Garrett Grolemund
Analysts often spend 50-80% of their time preparing and transforming data sets before they begin more formal analysis work. In this segment of the Learning Path, you’ll learn how R and its packages can help you save time and tackle three main issues: data manipulation, data tidying, and data visualization.

Writing Great R Code
Presented by Richie Cotton
Modern data analysis requires that you have two jobs: being a statistician and being a programmer. This is especially true with R. Fortunately, the jump from “writing code like a statistician” to “being a statistical programmer” isn’t that far. This course guides you through a few simple skills that will vastly improve the quality of your code.

Data Science with Microsoft Azure and R
Presented by Stephen Elston
This next segment of your Learning Path teaches you how to develop and deploy effective machine learning models in the Microsoft Azure Machine Learning (ML) environment. Start with an overview of Azure ML, and then learn to apply your R skills to create your own ML models.