Browse our complete catalog of workshops from Google Sheets
Browse all available workshops. Workshops with Available badges have upcoming sessions: orange = within 7 days, green = more than 7 days.
Learn how to use GitHub Copilot in VS Code to get AI-powered help while coding in Python.
Learn how to code with GitHub Copilot in VS Code and get started using AI to assist with R programming.
Learn how to use your computer’s terminal with a beginner-friendly intro to Bash and Zsh.
Stay current with the rapidly evolving landscape of artificial intelligence at our bi-weekly AI Pulse clinic.
Beginner-friendly intro to how AI tools like ChatGPT work, what they can do, and where they fall short.
Learn Excel basics with functions, charts, and pivot tables in this hands-on intro for absolute beginners.
An introduction to today's AI landscape, designed to help you navigate and make use of AI tools in your personal and professional life.
Learn Git from the command line to track changes, manage branches, and collaborate more effectively.
Learn Git and GitHub basics using GitHub Desktop—no coding experience needed.
Learn how to navigate the IRB process at UC Berkeley and get your human subjects research approved with confidence.
Explore how researchers can use LLMs like ChatGPT for early-stage research in this practical, tool-focused workshop.
Learn how to use Ollama to run local models for research
Learn MaxQDA from scratch in this hands-on intro.
Learn to read LLM “spec sheets”—tuning, distillation, parameters, benchmarks etc.—so you can choose models on OpenRouter and Hugging Face with conf...
Learn how to talk to AI tools like ChatGPT using simple, effective prompts in this hands-on intro to prompt engineering.
Learn Python from scratch in this beginner-friendly series covering coding basics, data structures, and intro data analysis with Pandas.
Build on your Python basics with loops, functions, data analysis, and a final project in this hands-on follow-up series.
Qualitative research overview. Departmental workshop.
Learn how to extract data from the web with APIs using Python.
Learn R from scratch in this beginner-friendly series covering data frames, summary stats, and visualizations with ggplot.
Learn Stata from scratch in this three-part series covering data cleaning, analysis, visualization, and basic programming.
This two-hour introductory workshop will teach you Tableau from scratch with clear introductions, concise examples, and support documents.
This workshop introduces researchers to using AI assistants like ChatGPT and Claude to create computational tools through natural language conversa...
Build on your Excel skills with deeper dives into charts, pivot tables, and the VLOOKUP function.
Learn how to call LLM and other web APIs from Python and parse structured results.
An introduction to visualization with Python using Matplotlib and Seaborn.
Manipulating data frames in Python.
Get a non-technical intro to how GPT models work, from transformer architecture to text prediction.
Learn to map and analyze geospatial data in Python using GeoPandas and matplotlib in this beginner-friendly workshop.
Learn the basics of SQL, with a focus on using SQLite for data science tasks.
Build stronger SQL skills for real-world analysis by learning joins, subqueries, CTEs, and window functions in Python.
Learn how to access, analyze, and visualize U.S. Census data in R using the tidycensus package.
Learn the basics of data visualization in R using ggplot2, including common plot types and core design principles.
Learn how to wrangle and tidy your data in R using the tidyverse for easier analysis and visualization.
Learn the basics of spatial analysis in R using sf and terra, from handling spatial data to creating effective maps.
Learn how to use SQL in R to access and query relational databases with DBI and dbplyr.
Learn deep learning basics in Python using Keras to build and test neural networks on image data.
Get hands-on with machine learning in Python using scikit-learn and TPOT, no theory required.
Learn core NLP techniques in Python, from preprocessing to word embeddings, with a focus on social science research.
Get started with supervised machine learning in R using tidymodels and learn when and how to apply these techniques.