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R Open Data Labs – Series 1, Part 1

This month’s R Open Data Lab is is the first of an 8 month series of Open Data Labs dedicated to helping people learn more about the capabilities of R and advance their personal R goals.

Each of these labs will start with a very short (~15 minute) review of available R programming environments for those who are entirely new to R.

The next part of the session will be a brief sightseeing tour of a particular R package + technique, for those who are looking for a better understanding of what R can do (~ 0.5 hrs).

The rest of the lab (~1.5 hrs) will be devoted to moving people forward with their specific R goals, through guided self learning. For this last part, a laptop with R installed is a must. We have two extra laptops that we can lend out during the lab if you are having a hard time getting access to your own laptop with R installed.

To help you focus in on your goals, you can start by filling out this R goals sheet.

In addition, for the sight-seeing part of the lab this week, we’ll be taking a look at the R randomForest package, which is used to create random forest models.

Post Author: Jen Schellinck

Jen Schellinck is the principal of Sysabee and an adjunct professor at Carleton's Institute of Cognitive Science. She founded Sysabee in 2012 with the goal of taking analysis techniques from machine learning and systems modeling and making these available to organizations who are seeking to gain the benefits of technology supported analysis and decision making. For each project, she draws from a pool of expert consultants to create a team customized to the specific needs of the project. She is also the founding member of the Data Science Experts Group, an association of data professionals that build flexible, customized solutions for data-driven companies and organizations. She remains an active participant in academic research via Carleton’s Cognitive Modeling Lab.