Designing Online Data Science Training for the Modern Age

Thumbnail Three Academy logos of a mountain with a flag on top, a discussion bubble, and a cohort of students. Sepia color is being peeled away to show a colored set of logos.

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.


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