Designing Online Data Science Training for the Modern Age

[This article was first published on RStudio | Open source & professional software for data science teams on RStudio, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

In the early days of film, directors referenced their knowledge of theater to visualize a screenplay. The camera was static. Actors walked in and out of the screen. The techniques that we now know are possible were yet to be developed. It would take time for film to become a medium in its own right. A scene from Blue Beard with a static camera showing people coming in and out of the scene

A scene from Blue Beard (1901), Georges Méliès

In the modern day, we encounter online courses that feel like someone placed a camera in front of a lecturer. While this may work in person, it does not deliver on the promise of e-learning.

  • The instructor cannot be responsive to the audience or their skill set.
  • The content concentrates on sharing facts rather than providing feedback.
  • Once the video is over, learners are on their own.

However, we believe we are entering a golden age. We do not need to recreate the lecture hall; we can design courses that take advantage of being online.

This is our approach with Academy, RStudio’s mentor-led data science apprenticeship for professional teams. Academy takes what we’ve learned from years of teaching to provide the most effective way to learn data skills online.

Our Response to the Old Way of Learning Data Science

With Academy, we strived to go beyond the typical e-learning experience to provide what data scientists need to build skills with a new tool.

  • Learners apprentice under an Academy mentor to solve a real-world data science problem drawn from their job.
  • Mentors prescribe a syllabus of interactive tutorials for the learners to complete, customized to their project.
  • The apprenticeship is a social experience: 5-7 learners work in parallel to complete their apprenticeships together, sharing ideas, posing questions—and holding each other accountable.
  • Mentors meet weekly with the cohort of learners to provide coaching and feedback as they apply what they’ve learned to their project.

These features create an online environment that is:

  • Outcome-based
  • Comprehensive
  • Iterative
  • Inclusive

We believe that these qualities are necessary for an effective e-learning environment, regardless of whether learners are in a classroom or at a laptop.

Taking Advantage of the Medium

In addition to recognizing and combating the shortcomings of e-learning, we’ve also incorporated online advantages into Academy.

  • Cohorts are structured around teams: like-minded people with similar goals, regardless of location.
  • Due to the internet, learners can meet regularly as a group to present their progress and share feedback.
  • Learners can learn on their own time, completing tutorials asynchronously whenever convenient and adapting their learning to their individual work schedules.
  • Learners have a support network they can use during — and after — the apprenticeship.
  • They can meet with a real R expert for mentoring, even if one doesn’t exist in their company or office.
  • We can — and do — use grading software that goes beyond unit tests. We don’t just tell learners how their result was incorrect. We analyze their code and make suggestions.
  • Because the group meets weekly, there is a short amount of time to finish and apply the lesson. Learners must take the lead: what they do at home matters.

Learn More About How Academy Is Designed for the Learners of Today

We are excited to provide data science teams with a learning experience that is the next frontier of online training.

To leave a comment for the author, please follow the link and comment on their blog: RStudio | Open source & professional software for data science teams on RStudio. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)