R

The goal of this workshop is to build intuition for deep learning by building, training, and testing models in Python. Rather than a theory-centered approach, we will evaluate deep learning models through empirical results.

Advanced Data Wrangling aims to help students to learn powerful data wrangling tools and techniques in R to wrangle data with less pain and more fun. This workshop will show how R can make your data wrangling process faster, more reliable, and interpretable.

Since 1790, the US Census has been THE source of data about American people, providing valuable insights to social scientists and humanists. Mapping these data by census geographies adds more value by allowing researchers to explore spatial trends and outliers. This workshop will introduce three key packages for streamlining census data workflows in R: tigris, tidycensus and tmap. Participants will learn how to download census tabular data for one or more geographic aggregation units or years, download the associated census geographic data and then join these data for analysis and mapping.

This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.