D-Lab

The social science data lab at UC Berkeley

Social Sciences Building, Berkeley, CA

Pinned Repositories

Bash-Git
D-Lab's 3 hour introduction to basic Bash commands and using version control with Git and Github.
131 10 5181
Computational-Social-Science-Training-Program
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.
Language:Jupyter Notebook179 13 880
Excel-Fundamentals
D-Lab's six-hour introduction to the basics of Microsoft Excel (with support materials for Google Sheets). Learn Excel functions for handling text, math, dates, logic, and calculations; learn to create charts and pivot tables.
9 4 27
Machine-Learning-in-R
Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
Language:CSS186 19 1372
Python-Fundamentals
D-Lab's 3-part, 6 hour introduction to Python. Learn how to create variables, distinguish data types, use methods, and work with Pandas, using Python and Jupyter.
Language:Jupyter Notebook20 6 4012
Python-Fundamentals-Legacy
D-Lab's 12 hour introduction to Python. Learn how to create variables and functions, use control flow structures, use libraries, import data, and more, using Python and Jupyter Notebooks.
Language:Jupyter Notebook169 36 68112
Qualtrics-Fundamentals
D-Lab's 3 hour introduction to Qualtrics Fundamentals. Learn how to design and manage your own surveys in Qualtrics.
13 9 63
R-Fundamentals
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.
Language:R25 4 384
R-Fundamentals-Legacy
D-Lab's 12 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.
Language:R140 23 7553
Stata-Fundamentals
D-Lab's 9 hour introduction to performing data analysis with Stata. Learn how to program, conduct data analysis, create visualization, and conduct statistical analyses in Stata.
Language:Stata77 19 1341

D-Lab's Repositories

dlab-berkeley/Computational-Social-Science-Training-Program
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.
Language:Jupyter Notebook179 13 880
dlab-berkeley/Bash-Git
D-Lab's 3 hour introduction to basic Bash commands and using version control with Git and Github.
131 10 5181
dlab-berkeley/R-Deep-Learning
Workshop (6 hours): Deep learning in R using Keras. Building & training deep nets, image classification, transfer learning, text analysis, visualization
Language:R118 13 938
dlab-berkeley/Python-Machine-Learning
D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn in Python.
Language:Jupyter Notebook78 14 4362
dlab-berkeley/R-Machine-Learning
D-Lab's 4-hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.
Language:HTML47 3 01
dlab-berkeley/python-berkeley
python resources of berkeley curated at a place
Language:Jupyter Notebook4648
dlab-berkeley/R-Data-Wrangling
D-Lab's 4 hour two-part workshop on data wrangling in R using tidyverse.
Language:R37 3 181
dlab-berkeley/R-Data-Visualization-Legacy
D-Lab's 3 hour introduction to data visualization with R. Learn how to create histograms, bar plots, box plots, scatter plots, compound figures, and more using ggplot2 and cowplot.
28 12 2420
dlab-berkeley/R-Fundamentals
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.
Language:R25 4 384
dlab-berkeley/Python-Fundamentals
D-Lab's 3-part, 6 hour introduction to Python. Learn how to create variables, distinguish data types, use methods, and work with Pandas, using Python and Jupyter.
Language:Jupyter Notebook20 6 4012
dlab-berkeley/Excel-Fundamentals
D-Lab's six-hour introduction to the basics of Microsoft Excel (with support materials for Google Sheets). Learn Excel functions for handling text, math, dates, logic, and calculations; learn to create charts and pivot tables.
9 4 27
dlab-berkeley/Python-Web-Scraping
D-Lab's 2 hour introduction to web scraping in Python. Learn how to scrape HTML/CSS data from websites using Requests and Beautiful Soup.
Language:Jupyter Notebook7 4 94
dlab-berkeley/Python-Data-Wrangling
D-Lab's 3 hour introduction to data wrangling in Python. Learn how to import and manipulate dataframes using pandas in Python.
Language:Jupyter Notebook6 3 157
dlab-berkeley/Python-Intermediate
D-Lab's 3-part, 6 hour workshop diving deeper into Python. Learn how to create functions, use if-statements and for-loops, and work with Pandas, using Python and Jupyter.
Language:Jupyter Notebook5 6 175
dlab-berkeley/Python-Web-APIs
D-Lab's 2 hour introduction to using web APIs in Python. Learn how to obtain data from web platforms using the New York Times API as a case study.
Language:Jupyter Notebook4 4 75
dlab-berkeley/Survey-Fundamentals
Language:Jupyter Notebook3 3 01
dlab-berkeley/MAXQDA-Fundamentals
D-Lab's 2 hour introduction to MAXQDA. Learn how to conduct qualitative data analysis using MAXQDA.
2 8 41
dlab-berkeley/Python-Data-Visualization-Pilot
D-Lab's 4-hour introduction to data visualization with Python. Learn how to create histograms, bar plots, box plots, scatter plots, compound figures, and more, using matplotlib and seaborn.
Language:Jupyter Notebook21
dlab-berkeley/Python-Geospatial-Fundamentals
About D-Lab's 4-hour introduction to working with geospatial data in Python. Learn how to import, visualize, and analyze geospatial data in Python.
Language:Jupyter Notebook2 3 24
dlab-berkeley/R-Geospatial-Fundamentals
D-Lab's 6-hour introduction to working with geospatial data in R. Learn how to import, visualize, and analyze geospatial data in R.
Language:Jupyter Notebook2 3 217
dlab-berkeley/D-Lab-Workshop-Template
This repository serves as a template for all D-Lab workshops stored on GitHub. Use this template if you're creating a new D-Lab workshop.
Language:Jupyter Notebook1 4 01
dlab-berkeley/DH-Text-Analysis
D-Lab's introduction to text analysis for Digital Humanities.
Language:Jupyter Notebook1
dlab-berkeley/DIGHUM101-2024
Python Programming for Digital Humanities, UC Berkeley Summer Session 2024
Language:Jupyter Notebook1 3 0
dlab-berkeley/R-Data-Visualization
D-Lab's 2-hour introduction to data visualization with R. Learn how to create histograms, bar charts, box plots, scatter plots, and more using ggplot2.
Language:R1 3 11
dlab-berkeley/dlab-workshops
Overview of D-Lab workshops and the order in which to take them.
Language:HTML
dlab-berkeley/FSRDC-Fundamentals
Language:Jupyter Notebook3 0
dlab-berkeley/GPT-Fundamentals
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.
Language:Jupyter Notebook3 0
dlab-berkeley/Natural-Language-Processing-Part-Two-DS-Discovery
Language:Jupyter Notebook3 0
dlab-berkeley/prompt-engineering
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.
Language:Jupyter Notebook
dlab-berkeley/R-Haas-Workshop
D-Lab's 1.5 hour foray into R basics for the Haas MBA 200 course.
Language:Jupyter Notebook5 01