D-Lab's 2-part, 3.5 hour introduction to workshop instruction.

This course is a rigorous, year-long introduction to computational social science. We cover topics spanning reproducibility and collaboration, machine learning, natural language processing, and causal inference. This course has a strong applied focus with emphasis placed on doing computational social science.

Materials for D-Lab / UC Berkeley Graduate Division's Data Science for Social Justice summer workshop. These materials provide an introduction to Python, natural language processing, text analysis, word embeddings, and network analysis. They also include discussions on critical approaches to data science to promote social justice.

Listing for D-Lab courses

Python Programming for Digital Humanities, UC Berkeley Summer 2024, taught by Prashant Sharma

python resources of berkeley curated at a place

D-Lab's 6-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.

D-Lab's introduction to text analysis for Digital Humanities.

D-Lab's 2-hour introduction to Generative Pretrained Transformers (GPT) for beginners. Learn about text encoding, word embeddings, and the transformer architecture upon which GPT is based. Create texts using a GPT model with the Transformers library in Python, and learn about hyperparameters such as temperature.