On August 5, 2020, RStudio announced the general availability of RStudio Cloud, its cloud-based platform for doing, teaching, and learning data science using only a browser. We often recommend RStudio Cloud to teachers because it simplifies course setup, makes it easy to distribute and manage exercises, and helps the instructor track student progress. With COVID-19 driving more courses online this fall, RStudio has developed a number of resources for instructors to use with RStudio Cloud, including:
However, while we often hear from teachers about how RStudio Cloud has helped them, we don’t often get to hear what the experience is like from the student’s point of view. We recently had the opportunity to have an in-depth discussion with Lara Zaremba, a Master’s degree student in International Economics at Johann Wolfgang Goethe-Universität, in Frankfurt Germany. In the video below, Lara describes some of what she experienced collaborating with other students and being a mentor to others on the platform.
An earlier part of our conversation with Lara also highlighted the need for increased diversity within the R community. While Lara felt that RStudio Cloud empowered her to become successful as a student and mentor, she mentioned that she had not seen herself as a data scientist because of the stereotypes associated with “computer people”.
One of the most powerful forces helping overcome those stereotypes today is R-Ladies Global (rladies.org), a world-wide organization dedicated to promoting gender diversity through meetups, code, teaching, and leadership. We encourage all to support their work and to help everyone see themselves as full members of the R community. You can learn more about how you can participate and make our community more welcoming to all at https://rladies.org/about-us/help/.
We are excited to announce real-time collaborative editing on RStudio Cloud. Users can join the same project, edit code, and immediately see each other’s changes.
In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This third post focuses on features that save you time and trouble.