posit::conf(2023) Workshop: Teaching Data Science Masterclass
Register now: http://pos.it/conf Instructor: Dr. Mine Çetinkaya-Rundel Workshop Duration: 1-Day Workshop This course is for you if you: • you want to learn / discuss curriculum, pedagogy, and computing infrastructure design for teaching data science with R and RStudio using the tidyverse and Quarto • you are interested in setting up your class in Posit Cloud • you want to integrate version control with git into your teaching and learn about tools and best practices for running your course on GitHub This masterclass is aimed primarily at participants teaching data science in an academic setting in semester-long courses, however much of the information and tooling we introduce is applicable for shorter teaching experiences like workshops and bootcamps as well. Basic knowledge of R is assumed and familiarity with the tidyverse and Git is preferred. There has been significant innovation in introductory statistics and data science courses to equip students with the statistical, computing, and communication skills needed for modern data analysis. Success in data science and statistics is dependent on the development of both analytical and computational skills, and the demand for educators who are proficient at teaching both these skills is growing. The goal of this masterclass is to equip educators with concrete information on content, workflows, and infrastructure for painlessly introducing modern computation with R and RStudio within a data science curriculum. In a nutshell, the day you’ll spend in this workshop will save you endless hours of solo work designing and setting up your course. Topics will cover teaching the tidyverse in 2023, highlighting updates to R for Data Science (2nd ed) and Data Science in a Box as well as present tooling options and workflows for reproducible authoring, computing infrastructure, version control, and collaboration. The workshop will be comprised of four modules: • Teaching data science with the tidyverse and Quarto • Teaching data science with Git and GitHub • Organizing, publishing, and sharing of course materials • Computing infrastructure for teaching data science Throughout each module we’ll shift between the student perspective and the instructor perspective. The activities and demos will be hands-on; attendees will also have the opportunity to exchange ideas and ask questions throughout the session. In addition to gaining technical knowledge, participants will engage in discussion around the decisions that go into developing a data science curriculum and choosing workflows and infrastructure that best support the curriculum and allow for scalability. We will also discuss best practices for configuring and deploying classroom infrastructures to support these tools
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Transcript#
This transcript was generated automatically and may contain errors.
Hi, I'm Mina Chetinkar-Randell. I'm a professor at Duke University and a developer educator at Posit. This year at Posit.conf, I'm teaching a one-day Teaching Data Science Masterclass. I've been teaching data science with R for over a decade, and I can't wait to share everything I've learned over this time about successful data science pedagogy, teaching with authentic tools, and doing so effectively and efficiently.
Three reasons to take this workshop
Here are the top three reasons why you should take this workshop. First reason is keeping up with the evolving data science ecosystem is not trivial. Keeping up with it and deciding whether it's the right time to update your curriculum to incorporate new tools or new features of existing tools, new data sources, or new workflows, and doing so while concurrently teaching can be overwhelming. This workshop is designed to share with you what's new in the land of teaching data science with R and to distill for you how you can implement these updates in your curricula.
Second, successful teaching doesn't end with successful curriculum design. The computational infrastructure you use for your teaching is an equally important part of a successful data science course, particularly if your definition of success takes into consideration the experience and enjoyment of your students as well as of yourself. In this workshop, we'll talk quite a bit about how to set up computational teaching environments with Posit Cloud as well as other server-based tools, how to use Git and GitHub for version control, collaboration, and as your course management system, and how to teach reproducible authoring with Quarto as well as how to use it to build your course materials and sites.
And third, this workshop will supercharge your learning and teaching prep. In one day of the workshop, you will pick up a wealth of information and tips that can save you weeks and months of trial and error on your own. Additionally, you'll meet a community of like-minded data science educators with whom you can stay in touch beyond the conference.
weeks and months of trial and error on your own. Additionally, you'll meet a community of like-minded data science educators with whom you can stay in touch beyond the conference.
One final comment is that this year the teaching data science workshop is offered as a one-day workshop, which means you can focus on your teaching on one of the workshop days and spend the other day learning something you've been hoping to make time for all year.
Go to posit.com slash conference to register for this workshop as well as to find out about all of the other fantastic workshops we're offering at posit.com this year. Looking forward to seeing you in Chicago in September!
