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Have you ever attended a webinar or workshop where you understood everything, but when you tried to use it on your own, you realized that you had no idea where to begin? It is a common experience; and it means that you learned the facts, but not the skills.
RStudio Academy is a hybrid learning platform that provides better data science training by developing skills, rather than over-focusing on facts. You can deploy Academy as a “turn-key” solution within your organization to cultivate the skills your team needs in an effective and lasting way.
Over our past decade of teaching data science, we’ve asked a lot of questions about how students learn best.
How do people really build long-lasting skills? With apprenticeships, internships, residencies, and coaching. Each emphasizes the two things we need to build a neural network: practice and feedback. Practice helps you build a neural network to guide the skill. Feedback ensures that you encode useful knowledge into your network, and not bad habits.
Each of these training styles also incorporates a social component to learning. When you work alongside a mentor or group of peers, you have a community of people to hold you accountable and support you as you learn.
Academy combines practice, feedback, and a motivating social component to create a learning experience akin to a data science residency that you can employ in house to create productive data scientists.
Academy replaces the traditional workshop with a project-based apprenticeship. We carefully design projects that students find personally motivating and relevant to their daily work. Each student works in parallel with 5-6 fellow students to complete the project under the close guidance of a mentor.
The student’s project work is central to the learning experience. Academy divides projects into progressive milestones that students complete one week at time, building towards a final data science analysis and polished report. The students’ goal each week is to recreate the milestone, applying what was learned during the week, and then to extend it in a personalized way by incorporating something they’ve learned on their own. This second piece is crucial to learning because students get explicit practice teaching themselves something new about R – a skill that is necessary for becoming a competent R coder in the long-run. To aid in this task, students:
Complete 4-5 interactive lessons that teach the fundamentals needed for the milestone, as well as strategies for self-directed learning with R. Academy’s lessons have students work in the real tools used by data scientists, such as the RStudio IDE.
Complete 30 - 60 minutes of adaptive practice drills that are designed to cement mastery with spaced repetition.
Consult one-on-one with an Academy mentor for 15 minutes.
Present their project progress to their peer group during a group session and receive valuable feedback.
Academy’s format is designed to teach students how to explore R on their own, as well as to encourage cross-pollination of ideas. On average, Academy students will spend 45-60 minutes per day.
Academy mentors and projects can come from RStudio—or from your own company. When you supply your own mentors, the relationship between data scientists and mentors continues within your organization after the apprenticeship is over. Mentor time requirements during the project are minimal: mentors meet with each student for 15 minutes once per week and host a weekly group discussion.
Many training companies exist to maximize training profits, but RStudio exists to maximize the number of skilled software users. In fact, we are not a training company at all. We are a Public Benefit Corporation whose mission is to provide excellent open source software to the scientific community and to train the community to use it.
Our decade of experience teaching scientists how to use our software has revealed that common training formats, such as workshops and online courses, do not provide lasting results.Schedule a meeting