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/Machine-Learning-in-R
Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
dlab-berkeley/Python-Geospatial-Fundamentals-Legacy
D-Lab's 6 hour introduction to working with geospatial data in Python. Learn how to import, visualize, and analyze geospatial data using GeoPandas in Python.
dlab-berkeley/Python-Data-Visualization-Legacy
D-Lab's 3 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.
dlab-berkeley/Python-Data-Wrangling-Legacy
D-Lab's 3 hour introduction to data wrangling in Python. Learn how to import and manipulate dataframes using pandas in Python.
dlab-berkeley/Python-Text-Analysis-Fundamentals
D-Lab's 9 hour introduction to text analysis with Python. Learn how to perform bag-of-words, sentiment analysis, topic modeling, word embeddings, and more, using scikit-learn, NLTK, gensim, and spaCy in Python.
dlab-berkeley/python-data-from-web
API and web scraping workshops
dlab-berkeley/R-Functional-Programming
The joy and power of functional programming in R
dlab-berkeley/ANN-Fundamentals
dlab-berkeley/sql-for-r-users
SQL for R Users, Workshop
dlab-berkeley/DIGHUM101-2020
dlab-berkeley/Python-Deep-Learning-Legacy
D-Lab's 6 hour introduction to deep learning in Python. Learn how to create and train neural networks using Tensorflow and Keras.
dlab-berkeley/advanced-data-wrangling-in-R-legacy
Advanced-data-wrangling-in-R, Workshop
dlab-berkeley/R-Census-Data-Legacy
Workshop on fetching and mapping census data with tidycensus
dlab-berkeley/Data-Science-Social-Justice-2022
Materials for D-Lab / UC Berkeley Graduate Division's Data Science + 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/efficient-reproducible-project-management-in-R
Efficient and Reproducible Project Management in R
dlab-berkeley/Fast-R
A scalable distillation of D-Lab's R-FUN!damentals series to help you get onboarded to R fast!
dlab-berkeley/Geocoding-in-R
dlab-berkeley/fairML
Bias and Fairness in ML workshop
dlab-berkeley/Python-Web-Scraping-Legacy
D-Lab's 3 hour introduction to web scraping in Python. Learn how to use APIs and scrape data from websites using the New York Times API and BeautifulSoup in Python.
dlab-berkeley/data-security-fundamentals
Data Security Fundamentals
dlab-berkeley/DIGHUM101-2021
dlab-berkeley/DIGHUM101-2022
Practicing the Digital Humanities, UC Berkeley Summer Session 2022
dlab-berkeley/R-package-development
R package development workshop
dlab-berkeley/intro-maxqda
dlab-berkeley/DEVP229-Spring2021
dlab-berkeley/R-Push-Ins
D-Lab's 4.5 hour "push-in" introduction to R, providing a brief survey of foundational R concepts and operations.
dlab-berkeley/R-Research-Design
dlab-berkeley/design-your-research
dlab-berkeley/TextXD-Python-Text-Analysis
D-Lab's 3 hour introduction into bag-of-words and word embeddings for TextXD 2022.
dlab-berkeley/web-scraping-examples
Examples of using a variety of web scraping tools and methods for various kinds of data extracted from the web