These are some example template emails that can be used for communicating with applicants:
Subject: "Reproducibility and Data Science in R Workshop Series"
Congratulations! You have been accepted into the Reproducibility and Data Science in R Fall workshop series. The short course will meet every Tuesday and Thursday from 11am to 1pm from <start> through <end> ending with a reproducibility colloquium on <date> to allow you to showcase what you’ve learned. Please let us know if you can no longer commit to attending most sessions by <final deadline> so we can open up spaces for additional applicants.
Keep an eye out for a follow up email in the next couple of weeks with more details including an invite to our Slack channel. We are looking forward to meeting you all, and in the meantime, please don’t hesitate to reach out with any questions you might have.
Subject: "Reproducibility and Data Science in R Workshop Series"
Dear applicant,
Thank you for applying to our Fall Reproducibility and Data Science in R workshop series. We received a large number of applications this year, and, unfortunately, your application was not selected for participation in this year's workshop.
We encourage you to apply again next year (and remind us that you applied previously when you do) and to continue to reach out to us with data science and reproducibility questions via email, our weekly drop-in hours, and in the UA Data Science Slack group.
If you’re up for doing some self-study in lieu of attending the workshop series this Fall, here are some suggested places to get started:
Excuse me, do you have a moment to talk about version control? (https://peerj.com/preprints/3159v2/)
6 Steps Towards Reproducible Research (https://zenodo.org/records/12744715)
Happy Git and GitHub for the useR (https://happygitwithr.com/)
R for Data Science (2e) (https://r4ds.hadley.nz/)
Our previous workshops on YouTube (https://www.youtube.com/@cctdatascience2556)
Instructor notes and slides for the workshop series (https://cct-datascience.github.io/repro-data-sci/)
The start of the Reproducibility and Data Science in R workshop series is about a week away! We have a website for the series here (work in progress) with a schedule, a code of conduct, and contact information for us.
We’ll use Slack extensively for communication throughout this course, so we ask that you join our private Slack channel before next week and introduce yourself. We just sent out invites, so please let us know if you haven’t gotten one!
We’ll be meeting on Zoom at the same link every session: <Zoom link>
This link is pinned to the top of our Slack channel as well.
Before the first session, we also ask that you make sure your versions of R and RStudio are updated. Get the most recent version of R here: https://cran.r-project.org/. Get the most recent version of RStudio here: https://posit.co/download/rstudio-desktop/. Also, having two monitors (e.g. a laptop and an external monitor) is helpful for this course, although not required.
Looking forward to meeting you all at our first session at 11am on <date>!\
\
- Eric & Renata
To send to all learners after the last session.
Thank you all for participating in the CCT Data Science Reproducibility & Data Science in R workshop series! It was really wonderful working with you all for the past 6 weeks and we appreciate your questions and comments. Please help us improve this workshop series by taking a short survey. We hope you'll encourage your lab-mates to apply to attend this workshop series when we offer it again in Fall 2025.
In case you missed it, we recorded the presentations made at our wrap-up Reproducibility Colloquium—feel free to share the recording.
Although we won't be meeting formally as a group again, you'll all retain access to our Slack channel and are encouraged to use it. I'd also like to encourage you to help answer questions in the #r-help and #git channels. All of the recordings of our sessions will also remain on YouTube on this unlisted playlist and you can access the slides on our workshop website.
You are also welcome to come by our drop-in hours every Tuesday morning to get help with any of the topics we covered in the workshop series (and more!). Our group can also help out in more hands-on ways—you can see some examples of past data science incubator projects and other collaborations on our website.
See you around, and please reach out with any questions or suggestions!
-Eric