D-Lab

Overview of D-Lab workshops and the order in which to take them.

This workshop teaches participants how to create clear, effective, and accessible visualizations in Excel by starting with an analytical question, preparing chart-ready data, and choosing the right chart type. Participants will also build Pivot Tables and Pivot Charts while learning how to use AI as a reviewer for visualization decisions.

This workshop focuses on using Excel formulas and functions to build clear, scalable analytical workflows. Participants will learn how Excel evaluates calculations, apply math, text, logic, lookup, and aggregation functions, and use audit tools and AI assistance critically to verify their work.

This workshop introduces core Excel skills for working with data, including navigating workbooks, entering and formatting data, using shortcuts, and identifying common data issues. Participants will also practice basic formulas, sorting, filtering, pivot tables, and creating simple charts from clean data.

Python Programming for Digital Humanities, UC Berkeley Summer 2026, taught by Matthew Kollmer

D-Lab's 1-hour introduction to prompt engineering with ChatGPT. Learn what prompt engineering is, best practices for prompting, and techniques to resolve errors.

D-Lab's 4.5 hour "push-in" introduction to R, providing a brief survey of foundational R concepts and operations.

D-Lab's 4-hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.

D-Lab's 4-hour introduction to working with geospatial data in R. Learn how to import, visualize, and analyze geospatial data in R.

D-Lab's 4 part, 8 hour introduction to R Fundamentals. Learn how to create variables and functions, manipulate data frames, make visualizations, use control flow structures, and more, using R in RStudio.