Pinned Repositories
Bash-Git
D-Lab's 3 hour introduction to basic Bash commands and using version control with Git and Github.
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.
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.
Machine-Learning-in-R
Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
Python-Fundamentals
D-Lab's 6-part, 12-hour introduction to Python. Learn how to create variables, use methods and functions, work with if-statements and for-loops, and do data analysis with Pandas, using Python and Jupyter.
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.
Qualtrics-Fundamentals-Legacy
D-Lab's 3 hour introduction to Qualtrics Fundamentals. Learn how to design and manage your own surveys in Qualtrics.
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.
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.
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.
D-Lab's Repositories
dlab-berkeley/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.
dlab-berkeley/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.
dlab-berkeley/Bash-Git
D-Lab's 3 hour introduction to basic Bash commands and using version control with Git and Github.
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
dlab-berkeley/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.
dlab-berkeley/R-Geospatial-Fundamentals-Legacy
This is the repository for D-Lab's Geospatial Fundamentals in R with sf workshop.
dlab-berkeley/python-berkeley
python resources of berkeley curated at a place
dlab-berkeley/R-Machine-Learning-Legacy
D-Lab's 6 hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.
dlab-berkeley/R-Data-Wrangling-Legacy
D-Lab's 6 hour introduction to data wrangling with R. Learn how to manipulate dataframes using the tidyverse in R.
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.
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.
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.
dlab-berkeley/Qualtrics-Fundamentals
D-Lab's two-part introduction to Qualtrics. Learn how to design and manage your own surveys in Qualtrics.
dlab-berkeley/Geospatial-Fundamentals-in-QGIS
dlab-berkeley/Data-Science-Social-Justice
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.
dlab-berkeley/DIGHUM101-2023
Practicing the Digital Humanities, UC Berkeley Summer Session 2023
dlab-berkeley/Python-Intermediate-Legacy
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.
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.
dlab-berkeley/R-Data-Wrangling
D-Lab's 4 hour two-part workshop on data wrangling in R using tidyverse.
dlab-berkeley/DIGHUM101-2024
Python Programming for Digital Humanities, UC Berkeley Summer 2024, taught by Prashant Sharma
dlab-berkeley/Survey-Fundamentals
dlab-berkeley/IRB-Fundamentals
D-Lab's 3 hour introduction to the fundamentals of navigating Institutional Review Boards (IRB).
dlab-berkeley/DH-Text-Analysis
D-Lab's introduction to text analysis for Digital Humanities.
dlab-berkeley/HAAS-Python-Workshop
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.
dlab-berkeley/FSRDC-Fundamentals
dlab-berkeley/dlab-modules
Listing for D-Lab courses
dlab-berkeley/Natural-Language-Processing-Part-Two-DS-Discovery
dlab-berkeley/Practical-Programming-Working-Group
dlab-berkeley/Python-Machine-Learning-DS-Discovery
D-Lab's 6 hour introduction to machine learning in Python, tailored for DS Discovery Fellows. Learn how to perform classification, regression, clustering, and do model selection using scikit-learn in Python.