Communicate and Automate with R: A Hands-On Interactive Course

An analysis is only finished when someone else can act on it. This three-lesson interactive course is about the last mile: turning your R work into a report that updates itself, a story a busy reader can act on in thirty seconds, and a careful use of AI to do the parts that used to take all afternoon.

You already know how to wrangle data and draw a chart. This course is about what happens next: getting the result out of your console and in front of a decision-maker, without copy-paste errors, without burying the headline, and without blindly trusting a model you cannot check.

Each lesson is a guided, interactive experience: you run live R in the browser, answer checkpoints as you go, and see each idea work on real data before you apply it yourself.

The three lessons

Lesson 1: Reproducible reports with Quarto

See the anatomy of a Quarto (and R Markdown) document: the YAML header, the prose, and the code chunks that compute every number so nothing is ever typed by hand. You learn what "render" turns your file into, how an inline expression kills copy-paste drift, and how to parameterize a report so one template re-runs for any store, any week, or any input.

Start Lesson 1: Reproducible reports with Quarto

Lesson 2: Telling a story with data

Lead with the answer. You learn to open with the executive summary a busy reader needs first, then structure a short, honest data story that carries them from the headline to the evidence to the recommendation, so the point lands before their attention runs out.

Lesson 2 is coming soon.

Lesson 3: AI-assisted analysis in R

Put a language model to work inside your analysis with ellmer: summarize free-text fields, label rows at scale, and draft the boring prose. Just as important, you get a clear-eyed guide to when an LLM is the right tool and when it is not, and how to verify what it gives you.

Lesson 3 is coming soon.

Who this is for

You can already load, filter and summarise data in R and build a basic chart, and now you want your results to travel. You do not need any prior Quarto, R Markdown or AI experience. By the end you will be able to ship a report that re-runs on new data, frame a result so a decision-maker acts on it, and use an LLM in your workflow without losing your skepticism.

What you will be able to do

• Name the parts of a Quarto document and explain what render produces
• Compute every number in a report from R, so changing the data re-flows the whole document
• Parameterize a report so one template serves many inputs
• Open with the answer and structure a data story a busy reader can act on
• Use an LLM to summarize and label data in R, and judge when to trust it

Ready? Begin with Lesson 1.