by Ari Lamstein, Software Engineer and Data Analyst
Creating an email course for my R packages has significantly increased the number of people who use the packages. It has also reduced the learning curve for the packages and brought me into greater contact with my users. In this post I will share the 5 steps I took to create my course Learn to Map Census Data in R.
My hope is that this will encourage other package authors to create similar courses, which will in turn improve the accessibility of R to the public.
Before explaining the steps, though, I’d like to share how the course came to be. When I first started blogging in March I took John Somnez’s free email course on blogging. I found the format to be both novel and effective. The lessons were small, well spaced and contained manageable homework assignments. Also, following up with John was as easy as hitting “reply” on the email. So when I started getting requests for an online version of the tutorial I ran in May, I decided to create my own email course.
Step 1: Create a Website
Your course needs an online “home” where you can announce it, people can signup, and so on. WordPress has become the most popular option for this. While you can host your site for free at wordpress.com, it will limit the amount of customization you can do. I pay $3.49/month to host my site with bluehost. Bluehost allows me to customize the site in any way I see fit.
After creating your blog, be sure to add it to R-bloggers. This will make your posts immediately visible to the R world.
Step 2: Learn About Email Automation
WordPress comes with functionality that allows anyone to subscribe to your blog. This allows them to be emailed when you publish new posts. Email courses, however, are more complicated than this. You want people to receive a series of pre-written emails that are spaced over several days.
To achieve this I use the email automation feature in MailChimp. It costs $10/month. Automation (sometimes called “autoresponders”) is now a fairly standard feature among email providers. Other companies in the space are AWeber and Drip.
Step 3: Write the Course
How you structure your course is up to you. When creating an automation MailChimp defaults to five emails. I decided to stick with that, which meant that the first email would be an introduction and the last email would be a conclusion. This left three emails to be the main content of the course. What were the three most important things I wanted people to learn? My answer was: “Create maps of census data for states, counties and ZIP codes.”
My next question was how to structure the lessons. In each email I walk thru one example and then assign a closely-related homework assignment. Because I want to communicate with my students, and because one-to-one email doesn’t scale, I asked people to tweet me their solutions using the hashtag #CensusCourse. This format seems to have worked well.
Step 4: Create a Signup Form
Now that you have a course you need people to sign up for it. Signup forms (or “Opt In Forms”) are the forms that make this happen. The signup form needs to be clearly visible and easy to understand while while not being spammy. There are countless WordPress plugins for this. I personally like Optin Cat, which is free
Step 5: Announce the Course
Once people can sign up for your course you need to announce it to the R community. I recommend writing a blog post that explains the goal and lessons of the course in some detail. You can see the post I wrote introducing my course here.
Note that if your blog is a part of R-bloggers (see Step 1) then a large number of people will automatically know about your course. I also recommend tweeting about your course with the hashtag #rstats.
These are the 5 steps I took to create my R email course Learn to Map Census Data in R. While some industries have embraced email courses as a way to introduce people to a product, it has not yet caught on for R packages. That being said, my experience using it has been very favorable. More importantly, my users seem to have really enjoyed it. I hope that after reading this post more package authors give email courses a try, and that it leads to greater engagement in the R community.