Repositories list

• R-Causal-Inference

  Public
  D-Lab's 2-hour introduction to causal inference. Learn about core concepts in causal inference, including the potential outcomes framework and essential statistical techniques.

  0•0•0•0•Updated Oct 31, 2024Oct 31, 2024

• 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 RStudio.

  R

  •9•31•16•0•Updated Oct 31, 2024Oct 31, 2024

• R-Geospatial-Fundamentals

  Public
  D-Lab's 4-hour introduction to working with geospatial data in R. Learn how to import, visualize, and analyze geospatial data in R.

  2•4•3•0•Updated Oct 28, 2024Oct 28, 2024

• Python-Geospatial-Fundamentals

  Public
  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.

  Jupyter Notebook

  •5•2•0•0•Updated Oct 28, 2024Oct 28, 2024

• R-LLMs-Exploratory-Research

  Public
  D-Lab's 1-hour introduction to using LLMs for exploratory research in R.

  0•1•0•0•Updated Oct 28, 2024Oct 28, 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

  •

  Creative Commons Attribution 4.0 International

  •6•4•3•0•Updated Oct 23, 2024Oct 23, 2024

• D-Lab-Workshop-Template

  Public 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.

  Jupyter Notebook

  •1•3•0•0•Updated Oct 21, 2024Oct 21, 2024

• R-Machine-Learning

  Public
  D-Lab's 4-hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.

  1•1•0•1•Updated Oct 16, 2024Oct 16, 2024

• MAXQDA-Fundamentals

  Public
  D-Lab's 2 hour introduction to MAXQDA. Learn how to conduct qualitative data analysis using MAXQDA.

  qttmaxqdaqualitative-data-analysis

  Other

  •1•2•2•0•Updated Oct 9, 2024Oct 9, 2024

• Python-Fundamentals

  Public
  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.

  Jupyter Notebook

  •

  Other

  •20•33•1•1•Updated Oct 2, 2024Oct 2, 2024

• Python-Deep-Learning

  Public
  D-Lab's 2-hour introduction to deep learning in Python. Learn how to create and train neural networks using Tensorflow and Keras.

  Jupyter Notebook

  •0•0•0•0•Updated Oct 1, 2024Oct 1, 2024

• Python-Data-Wrangling

  Public
  D-Lab's 3-hour workshop diving deep into Pandas. Learn how to manipulate, index, merge, group, and plot data frames using Pandas functions.

  Jupyter Notebook

  •

  Other

  •12•9•2•0•Updated Oct 1, 2024Oct 1, 2024

• Python-Machine-Learning

  Public
  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.

  clusteringscikit-learnregression+ 4classificationauto-mlpythonmachine-learning

  Jupyter Notebook

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  Other

  •67•80•24•2•Updated Oct 1, 2024Oct 1, 2024

• Copilot-Fundamentals

  Public
  D-Lab's 2-hour workshop on AI-assisted coding in Visual Studio Code using GitHub Copilot

  3•3•1•0•Updated Sep 27, 2024Sep 27, 2024

• Python-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

  •5•0•0•0•Updated Sep 26, 2024Sep 26, 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

  •95•221•5•1•Updated Sep 26, 2024Sep 26, 2024

• R-Haas-Workshop

  Public
  D-Lab's 1.5 hour foray into R basics for the Haas MBA 200 course.

  rdata-framesdata-science

  Jupyter Notebook

  •2•0•0•0•Updated Sep 13, 2024Sep 13, 2024

• Python-Data-Visualization

  Public
  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.

  Jupyter Notebook

  •3•3•7•1•Updated Aug 29, 2024Aug 29, 2024

• Python-Text-Analysis

  Public
  D-Lab's introduction to text analysis with Python. Learn how to preprocess text data, apply bag-of-words methods, engage with word embeddings, and more, using Python.

  Jupyter Notebook

  •

  Creative Commons Attribution 4.0 International

  •1•2•0•0•Updated Aug 29, 2024Aug 29, 2024

• dlab-workshops

  Public
  Overview of D-Lab workshops and the order in which to take them.

  HTML

  •1•0•0•0•Updated Aug 13, 2024Aug 13, 2024

• Instructor-Training

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

  Jupyter Notebook

  •0•0•2•0•Updated Jul 25, 2024Jul 25, 2024

• Data-Science-Social-Justice

  Public
  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.

  Jupyter Notebook

  •7•11•13•0•Updated Jul 8, 2024Jul 8, 2024

• dlab-modules

  Public
  Listing for D-Lab courses

  HTML

  •1•0•1•0•Updated Jul 4, 2024Jul 4, 2024

• DIGHUM101-2024

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

  Jupyter Notebook

  •1•1•0•0•Updated Jun 17, 2024Jun 17, 2024

• python-berkeley

  Public
  python resources of berkeley curated at a place

  Jupyter Notebook

  •

  Other

  •49•47•1•3•Updated May 30, 2024May 30, 2024

• DH-Text-Analysis

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

  Jupyter Notebook

  •0•1•0•0•Updated Apr 25, 2024Apr 25, 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

  •1•0•0•0•Updated Apr 23, 2024Apr 23, 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

  •3•4•1•0•Updated Apr 9, 2024Apr 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

  nlptensorflowkeras+ 3biomedicalcloudmldeep-learning

  R

  •39•122•0•0•Updated Apr 9, 2024Apr 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

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  Creative Commons Attribution 4.0 International

  •5•10•8•1•Updated Apr 9, 2024Apr 9, 2024