Welcome!

Data Science for Environmental Health (DaSEH) is a short course that combines online learning and an in-person project-focused intensive. DaSEH is tailored for beginners and novices in R programming, offering instruction on importing, wrangling, visualizing, and analyzing data. It provides hands-on training in using R for statistical computing, a widely-used open-source tool for data analysis and visualization.

This training initiative is funded by National Institute of Environmental Health Sciences 1R25ES035590-01.


DaSEH participants in person in a classroom learning about reproducibility.


Format

Online course

September 30 - October 10
10:30am - 2pm Pacific Time

Two-week online course in R programming foundations.


Code-a-thon

October 23-25 (in person in Seattle)
9:30am - 4pm Pacific Time

Three-day in-person intensive “Code-a-thon”. Here, we’ll work on authentic environmental health projects. We’ll also practice data ethics skills in peer code review, reproducibility, and transparency in a supportive environment.


Instructors

Carrie Wright (cwright2 @ fredhutch.org), Ava Hoffman (ahoffma2 at fredhutch.org), Elizabeth Humphries (ehumphri at fredhutch.org)

The lead instructors have earned recognition for excellence in teaching and have trained hundreds of professional learners. We can’t wait to have you in class, too!

We’re also supported by our data scientist, Candace Savonen (csavonen at fredhutch.org).


Testimonials from our other courses:

“Thanks all for a wonderful course! I feel super confident in R now and I am excited to apply what we learned to future projects. Cheers !!”

“I feel like a data witch now! I just say poof and the data looks the way I want”

“OK - this is getting to be too much fun now”

“My 14 year old thinks this class looks cool and wants to take it (she’s a wanna be engineer)”


Find an Error!?

Feel free to submit typos/errors/etc via the GitHub repository associated with the class: https://github.com/fhdsl/DaSEH

This page was last updated on 2024-08-19.

Creative Commons License


This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

DaSEH is funded by the National Institute of Environmental Health Sciences 1R25ES035590-01.