Next week I will be delivering a free online R training. This is a new course I’ve created called Mastering Data Structures in R. This course is for you if:

• You are new to R, and want a rigorous introduction to R as a programming language
• You know how to analyze data in R, but want to take the next step and learn to program in it too
• You already know R, but find yourself frequently confused by its “idiosyncracies”

R as a Tool for Data Analysis

When clients reach out to me for training, they normally want help learning R as a tool for Data Analysis. Most of my students are already experts at Excel. They want to learn R because they have heard that it is more powerful than Excel. For these clients I normally propose a two-day course that focuses on the Tidyverse and R Markdown:

• Day 1: learn to use ggplot2 and dplyr on datasets that have already been cleaned.
• Day 2: in the morning, learn to import and clean data using the Tidyverse. In the afternoon, learn to use R Markdown to do reproducible research.

In general, this sort of course helps people learn to use R to do much of what they were already doing in Excel.

R as a Programming Language

The biggest problem with my 2-day workshop is this: while I intend it to be a starting point for learning R, many of my students think that it’s all that they need to know! In fact, though, I only consider it to be a starting point.

For example, when I was working at an online Real Estate company, I needed to analyze our website’s sales lead data. I started by using R as a data analysis tool. I used packages like ggplot2 to explore the ebb and flow of our sales leads over time for each metropolitan area. But I eventually hit a wall. What I really wanted to do was map our data at the ZIP code level, and mash it up with data from the Census Bureau. Of course, no package existed to do this: it’s too specific. But since I knew R as a programming language, I was able to create functions (and eventually a package) to answer the exact question I had.

And this is the level that I want all my students to get to. Every analyst has a unique problem. Learning to use R as a programming language allows you to answer the exact question you have.

Why Data Structures?

Most of my students struggle to learn the “programming language” aspect of R  because they never formally studied Computer Science. I decided to address this by creating a course that resembles an introductory Computer Science course but uses R as the language of instruction.

My undergraduate Computer Science curriculum focused on Data Structures and Algorithms. This is why Mastering Data Structures in R provides a rigorous introduction to the basic data structures in R. The course contains dozens of exercises, and will increase your fluency at the console. 

I recently gave a pilot version of this course that was well received. To celebrate, I will be running the course online, for free, next week. Here is the syllabus:

• Monday 11/18: Data Types
• Tuesday 11/19: Vectors
• Wednesday 11/20: Factors and Lists
• Friday 11/21: Data Frames

All sessions will start at 10am PT and last approximately 90 minutes.

If you are interested in the course but cannot attend live, then you should still register: I will be sending recordings to everyone who registers.