This class is designed to introduce core programming principles as we work through real world analyses and build your knowledge and capabilities as we progress. No prior programming or statistics experience is required.

After completing the course, you will have developed a foundation of basic ability to program in R, be capable of performing statistical analyses using R, and be familiar with how to generate meaningful graphical output of results.

R is like any other programming language in that it has a steep learning curve. This class will reduce that learning curve through active learning whereby you learn by doing as everything we do in this class will involve real-life data and hands-on activities.

Throughout this course you will learn R programming through hands-on practical examples using real data. These examples are drawn from a variety of fields including social and physical sciences as well as business. Through this hands-on approach you will actively learn how to solve multiple common problems facing R users in academia, private industry, and data science in general. This unique approach will foster your ability to solve problems using R and it will allow the relevance and power of R’s tools to become apparent.

We will begin by exploring the core principles of programming, basic statistical analyses and data visualizations. Then we will continue to build your knowledge and progress on to more powerful techniques that are widely used by data scientists, including time series analysis and forecasting, and machine learning. The course contains many hours of hands-on tutorials and multiple exercises where you will test your ability to apply analysis techniques to real world datasets.

I’m looking forward to beginning our journey into R and turning you into a confident and accomplished R user!

I’ll see you in class,

David Keellings