Week 1: October 14, 16
Week 2: October 21, 23
Week 3: October 28, 30

4:30 PM – 6:30 PM ET

Agenda

Register

Researchers are increasingly needing data science skills. In this skill-building training course, learn intermediate aspects of R, the free modeling program, and how it can enhance your regional and local research methods. This workshop will provide hands-on experience and relevant use cases for analyzing economic and community data.

This Intermediate R workshop will provide a attendees with a how to on a data science workflow in R, from cleaning and wrangling to data visualization and mapping. Instructors will cover the essentials of popular R packages, including ggplot2, tidyr, dplyr, and tidycensus. The objective of the course is to provide economic developers and labor market analysts with the basic skills they’ll need to collect and analyze relevant datasets with the efficiency and power of R.

Code will be made available to attendees before and after this hands-on-keyboard session, allowing beginner-level users to dive right in and revisit materials after training. No programming experience is required for the workshop; however, interested attendees are encouraged to explore the online book R for Data Science, which can be found at https://r4ds.had.co.nz/. The curriculum will be tailored to the C2ER and LMI Institute audience, featuring Census and BLS data, as well as easy ways to include economics and labor data in your code.

By the end of this course participants will:

• Have R, RStudio, and necessary packages installed and ready to use.
• Learn the advanced components of R and RStudio including scripts, the console, environments, directory, history, and R Markdown, as well as the fundamentals of effective R workflows.
• Be able to use key functions from base R and the tidyverse for data cleaning and munging with examples and hands on tutorials to start coding on your own.
• Expand on working knowledge of API packages that allow for easy retrieval of public data from sources including the Census Bureau, BLS, and BEA.
• Be able to generate frequently used plots and understand the basics of data visualization in R using the ggplot2 package.
• Enhance your skills in R by exploring advanced spatial data manipulation and mapping techniques.

Requirements:
Attendees will attend classes over Zoom and need to use their own laptop for the training class – we do not recommend iPads or tablets.

Pricing:

Trainers:

Dr. Ezgi Karaesmen Instructor R Studio Education	Dr. Katie Sasso Schafer Instructor R Studio Education	Dr. Abbas Rizvi Instructor R Studio Education