Programming Languages

Python Deep Learning: Parts 1-2

March 12, 2024, 2:00pm
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.

R Fundamentals: Parts 1-4

October 3, 2022, 4:00pm
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.

Python Text Analysis: Topic Modeling

April 4, 2024, 10:00am
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

R Data Visualization

November 7, 2022, 2:00pm
This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures.

Python Data Wrangling and Manipulation with Pandas

September 20, 2023, 2:00pm
Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python. In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

Python Fundamentals: Parts 1-2 (4pm-7pm)

March 29, 2022, 4:00pm
Evening workshop 4-7pm. This two-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

CANCELED: QGIS Geospatial Fundamentals: Parts 1-2

November 15, 2022, 3:00pm
This workshop will introduce methods for working with geospatial data in QGIS, a popular open-source desktop GIS program that runs on both PCs and Macs as well as linux computers. Participants will learn how to load, query and visualize point, line and polygon data. We will also introduce basic methods for processing spatial data, which are the building blocks of spatial analysis workflows. Coordinate reference systems and map projections will also be introduced.

Python Text Analysis: Topic Modeling

October 16, 2023, 2:00pm
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

R Fundamentals: Parts 1-4

May 2, 2022, 10:00am
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.

Python Data Visualization

March 13, 2023, 2:00pm
For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook.