Competency: Research

Topic Modeling. How do we identify topics within a corpus of documents? In this part, we study unsupervised learning of text data. Specifically, we use topic models such as Latent Dirichlet Allocation and Non-negative Matrix Factorization to construct “topics” in text from the statistical regularities in the data.

Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research. Python Geospatial Fundamentals: Part 1 This workshop is the first one of…

Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research. Python Geospatial Fundamentals: Part 1 This workshop is the first one of…

This three-part interactive workshop series is a follow-up to D-Lab’s Python Fundamentals. It covers loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project. Learning Objectives After completing Python Intermediate, you will be able to: Understand and…

This three-part interactive workshop series is a follow-up to D-Lab’s Python Fundamentals. It covers loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project. Learning Objectives After completing Python Intermediate, you will be able to: Understand and…

This three-part interactive workshop series is a follow-up to D-Lab’s Python Fundamentals. It covers loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project. Learning Objectives After completing Python Intermediate, you will be able to: Understand and…

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching…

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching…

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…

It is said that 80% of data analysis is spent on the process of cleaning and preparing the data for exploration, visualization, and analysis. This R workshop will introduce the dplyr and tidyr packages to make data wrangling and manipulation easier. Participants will learn how to use these packages…

It is said that 80% of data analysis is spent on the process of cleaning and preparing the data for exploration, visualization, and analysis. This R workshop will introduce the dplyr and tidyr packages to make data wrangling and manipulation easier. Participants will learn how to use these packages…

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching…

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching…

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching…

Calling all digital humanities enthusiasts! If you are interested in presenting for this session please complete this google form. We encourage everyone to participate, regardless of your experience level. The DH Working Group is a welcoming and supportive community for all things digital humanities. About the Digital…

Calling all digital humanities enthusiasts! If you are interested in presenting for this session please complete this google form. We encourage everyone to participate, regardless of your experience level. The DH Working Group is a welcoming and supportive community for all things digital humanities. About the Digital…

This workshop is part of a loosely-coupled 4-part text analysis workshop series that will prepare participants to move forward with research that uses text analysis, with a special focus on social science applications. We explore fundamental approaches to applying computational methods to text in Python. We cover some of the…

This workshop is part of a loosely-coupled 4-part text analysis workshop series that will prepare participants to move forward with research that uses text analysis, with a special focus on social science applications. We explore fundamental approaches to applying computational methods to text in Python. We cover some of the…

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. We start with a review of what deep learning is and then unpack what neural networks…

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. We start with a review of what deep learning is and then unpack what neural networks…