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This is an archive of our past training offerings. We are looking to include workshops on topics not yet covered here. Is there something not currently on the list? Send us a proposal.
R Fundamentals Part 3: Data Exploration and Analysis
Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.
Tableau Fundamentals 1 & 2
Add data visualization to your communication toolbox without learning to code. Tableau cuts down the time you need to spend creating visualizations through an intuitive graphical user interface. Learn the basics in this hands-on, two-part workshop.
No prerequisites
This training will introduce you to open-source, user-friendly tools for analyzing and visualizing intonation and timing patterns in recordings of performative speech, from poetry readings to political speeches to podcasts.
TBD.
Tableau Fundamentals 1 & 2
Add data visualization to your communication toolbox without learning to code. Tableau cuts down the time you need to spend creating visualizations through an intuitive graphical user interface. Learn the basics in this hands-on, two-part workshop.
No prerequisites
It is often said that 80% of data analysis is spent on the process of cleaning and preparing the data. This workshop will introduce tools (notably dplyr and tidyr) that makes data wrangling and manipulation much easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful stuff.
Come learn how to turn your data into beautiful webmaps using R and Leaflet, one of the most popular libraries for creating web maps. We’ll cover how to build the entire workflow from raw data to interactive map all within R, so your analysis and mapping are entirely reproducible.
R Fundamentals Part 2: Subsetting and Reshaping
This session focuses on explaining the proces of creating, organizing, and applying codes within the context of qualitative research. An overview of qualitative data analysis (QDA) software will be provided, noting general advantages and disadvantages, as well as comparing popular programs. Participants will also be introduced to analysis using QDA software.
Pandas is a Python package providing 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.
We plan to cover:
This workshop will be open to anyone interested in having the guidance, feedback and structure for writing a grant.
Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills for free at our R workshops!
This session introduces qualitative research, and is recommended for folks who are new to research in general or to qualitative research in particular.
The agenda will be as follows:
This workshop introduces the basic concepts of Deep Learning - the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data.
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:
This four-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.
Raster data are used to represent geographic phenomena that are present and can be measured anywhere in a study area, like elevation, temperature, rainfall, land cover, soil type, etc. These data are a valuable resource for social scientists, planners, and engineers as well as natural scientists. This workshop will introduce basic raster concepts and methods for working with raster data in R.
This workshop introduces the basic concepts of Deep Learning - the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data.
This four-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.
Part 3 Topics:
