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@dlab-berkeley

D-Lab

The social science data lab at UC Berkeley

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  1. Python-Fundamentals Python-Fundamentals Public

    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.

    Jupyter Notebook 20 12

  2. R-Fundamentals R-Fundamentals Public

    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 RS…

    R 25 3

  3. Bash-Git Bash-Git Public

    D-Lab's 3 hour introduction to basic Bash commands and using version control with Git and Github.

    131 80

  4. Qualtrics-Fundamentals Qualtrics-Fundamentals Public

    D-Lab's 3 hour introduction to Qualtrics Fundamentals. Learn how to design and manage your own surveys in Qualtrics.

    13 3

  5. Stata-Fundamentals Stata-Fundamentals Public

    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.

    Stata 76 40

  6. Excel-Fundamentals Excel-Fundamentals Public

    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 cr…

    9 6

Repositories

Showing 10 of 108 repositories
  • DH-Text-Analysis Public

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

    Jupyter Notebook 0 0 0 0 Updated Apr 25, 2024
  • Computational-Social-Science-Training-Program Public

    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.

    Jupyter Notebook 176 78 5 0 Updated Apr 25, 2024
  • GPT-Fundamentals Public

    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.

    Jupyter Notebook 0 0 0 0 Updated Apr 24, 2024
  • prompt-engineering Public

    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.

    Jupyter Notebook 0 0 0 0 Updated Apr 23, 2024
  • DIGHUM101-2024 Public

    Python Programming for Digital Humanities, UC Berkeley Summer Session 2024

    Jupyter Notebook 0 0 0 0 Updated Apr 10, 2024
  • R-Data-Visualization Public

    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.

    R 1 1 1 0 Updated Apr 9, 2024
  • R-Deep-Learning Public

    Workshop (6 hours): Deep learning in R using Keras. Building & training deep nets, image classification, transfer learning, text analysis, visualization

    R 118 38 0 0 Updated Apr 9, 2024
  • Python-Web-Scraping Public

    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.

    Jupyter Notebook 7 CC-BY-4.0 4 8 1 Updated Apr 9, 2024
  • Python-Web-APIs Public

    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.

    Jupyter Notebook 4 CC-BY-4.0 5 3 0 Updated Apr 9, 2024
  • Python-Data-Wrangling Public
    Jupyter Notebook 6 6 13 0 Updated Apr 9, 2024
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