Date: May 14-16, 2024

Times: 9:00 AM – 1:00 PM (Eastern)

Location: Virtual (Online)

Instructors: Nathan Byers and Eric Bailey (Fluent Data, LLC)

Course Registration Link – Register by May 7, 2024

Who Should Attend: This course is designed to address the needs of state, local, and tribal air agency personnel involved in data analysis. This class is intended for staff who are beginners at using R. No prior experience with R or any other programming language is required.

About the Course: This course guides students through training materials for learning the R
programming language, specifically tailored towards air quality data science. The goal of this course is to introduce students to R and help them learn the basic skills to use R. Students will learn how to subset, sort, and combine data frames; writing functions, conditionals, and loops; and basic plotting and statistics in R.

Learning Objectives: Those completing this course will be able to do basic programming in R, including data organization and basic plotting and statistics. Students will be able to apply these skills to analysis of air quality monitoring data, emissions data, or any other data set.

Course Delivery: This is a virtual, instructor-led training. Materials will also be available online for self-
instruction following the live course.

How to Register: See the U.S. EPA LMS Frequently Asked Questions for how to create an account, register for a course, and other common functions.  


Agenda

View the agenda


Questions?

LADCO Data Scientist: Angie Dickens (dickens@ladco.org)


 Accessibility Statement

LADCO strives to host inclusive, accessible training events that enable all individuals, including individuals with disabilities, to engage fully with the instructor and course content. To request an accommodation or for inquiries about accessibility, please contact Zac Adelman (adelman@ladco.org | 847-720-7880).

About Author

Zac is LADCO's Executive Director. He's an environmental scientist with 20+ years experience in emissions and air quality modeling.