Below are links to materials from past RDS workshops organized by topic. Only materials from the most recent iteration of the workshop are provided. Past workshops taught by Research Computing are available at the RC Learning Portal.
R | Python | Stata | SPSS | Tableau | Computational Workflow Tools | Writing Workflow Tools
Reproducible Workflow | Qualitative Analysis | Data Management | Miscellaneous
R
- Linear Modeling in R (Clay Ford, 2024)
- Linear Mixed-Effect Modeling in R (Clay Ford, 2024)
- Count Modeling in R (Clay Ford, 2024)
- Getting Started with R (Jenn Huck, 2024)
- Parallel Computing in R (Jacob Goldstein-Greenwood, 2024)
- Fundamentals of Package Development in R (Jacob Goldstein-Greenwood, 2024)
- Power and Sample Size Analysis (Clay Ford, 2024)
- Bayesian Data Analysis, Part 1 (Clay Ford, 2024)
- Bayesian Data Analysis, Part 2 (Clay Ford, 2024)
- Data Wrangling Techniques in R: Beyond the Basics (Jacob Goldstein-Greenwood, 2023)
- Data Visualization in R with ggplot2 (Jacob Goldstein-Greenwood, 2023)
- Data Wrangling in R with dplyr and tidyr (Jacob Goldstein-Greenwood, 2023)
- Binary Logistic Regression in R (Clay Ford, 2023)
- Survival Analysis Modeling in R (Clay Ford, 2023)
- Ordinal Logistic Regression in R (Clay Ford, 2022)
- Data Wrangling Strategies with R (Clay Ford, 2021)
- Basic Statistics Refresher with R (Clay Ford, 2021)
- Visualizing Models, Communicating Results in R (Clay Ford, 2019)
- Interactive Web Apps in R with shiny (Clay Ford, 2019)
- Working with tidycensus in R (Jenn Huck, 2019)
- Data Wrangling with R, Part I (Clay Ford, 2018)
- Data Wrangling with R, Part II (Clay Ford, 2018)
- Data Wrangling with R, Part III (Clay Ford, 2018)
- Text Analysis with R, Part I (Michele Claibourn, 2018)
- Text Analysis with R, Part II (Michele Claibourn, 2018)
- Text Analysis with R, Part III (Michele Claibourn, 2018)
- Text Analysis in R: Quanteda (Michele Claibourn, 2018)
- Exploratory Factor Analysis (Clay Ford, 2018)
- Confirmatory Factor Analysis (Clay Ford, 2018)
- Web Scraping in R with rvest, (Clay Ford, 2017)
- Sentiment Analysis in R (Michele Claibourn, 2017)
- Character Manipulation in R (Clay Ford, 2017)
- Topic Modeling in R (Michele Claibourn, 2017)
- Text Classification in R (Michele Claibourn, 2017)
- Introduction to R Markdown (Clay Ford, 2017)
- Introductory Categorical Data Analysis in R (Clay Ford, 2016)
- Intro to Machine Learning, with Support Vector Machines (Bommae Kim, 2016)
- Matching Methods for Causal Inference (Michele Claibourn, 2016)
- Intro to Social Network Analysis (Yun Tai, 2016)
- Intro to Machine Learning, Classification and Regression Trees (Clay Ford, 2016)
- Geospatial and Census Data in R (Yun Tai, 2016)
- Multiple Imputation for Missing Data (Michele Claibourn, 2015)
- Resampling Methods (Clay Ford, 2014)
- Introduction to Structural Equation Modeling (SEM) (Siny Tsang, 2014)
- Cluster Analysis (in R) (Michele Claibourn, 2014)
- Spatial Analysis (in R), Part 1 and Part 2 (Adam Slez, Sociology, 2014)
- Multilevel Models I: Introductions, implementation, interpretation (in R and Stata) (Michele Claibourn, 2013)
- Multilevel Models II: Model assessment, estimation, and generalizations (in R and Stata) (Michele Claibourn, 2013)
- Matching Methods I: Logic, limitations, and algorithms for matching on covariates (in R) (Michele Claibourn, 2013)
- Matching Methods II: Propensity score approaches (in R) (Michele Claibourn, 2013)
Python
- Intro to Python (Erich Purpur, 2024)
- Python Data Analysis and Visualization (Erich Purpur, 2024)
- Python Geospatial Data and Mapping (Erich Purpur, 2024)
- Python and APIs (Erich Purpur, 2023)
- Python Geospatial Data and Mapping (Erich Purpur, 2023)
- Python Web Dashboards w/ Streamlit (Erich Purpur, 2023)
- Python Web Scraping (Erich Purpur, 2023)
- Python Sentiment Analysis and Natural Language Processing (Erich Purpur, 2023)
- Interactive Visualization with Python/Bokeh (Pete Alonzi, 2017)
- Machine learning with Python-scikit (Pete Alonzi, 2017)
- Text Classification in Python (Pete Alonzi, 2017)
Stata
- Introduction to Stata (Clay Ford, 2018)
- Exploratory Factor Analysis (using Stata) (Chelsea Goforth, 2016)
- Survey Data Analysis in Stata (Chelsea Goforth, 2015)
- Intro to Graphics in Stata (Chelsea Goforth, 2015)
- Logit and its GLM Friends (using Stata) (Chelsea Goforth, 2015)
- Regression Discontinuity (in Stata) (Brenton Peterson, 2014)
- Duration/Survival/Hazard Models (in Stata) (Michele Claibourn, 2013)
- Missing Data and Multiple Imputation (in Stata) (Michele Claibourn, 2013)
SPSS
- Data Analysis with SPSS for Thesis Writers (Michael Hull, 2015)
- Principal Component Analysis and Exploratory Factor Analysis (Michael Hull, 2015)
- Getting Started with SPSS Syntax (Michele Claibourn, 2015)
- Introduction to SPSS (Siny Tsang, 2014)
Tableau
- Data Visualization Using Tableau - Part 1 (Nancy Kechner, 2023)
- Data Visualization Using Tableau - Part 2 (Nancy Kechner, 2023)
Computational Workflow Tools
- Intro to Version Control with Git + Github (Erich Purpur, 2024)
- Intro to Regular Expressions (Erich Purpur, 2023)
- Introduction to the Command Line (Ricky Patterson, 2023)
Writing Workflow Tools
- Intro to Overleaf for LaTeX (Ricky Patterson, 2023)
- BibLaTeX for your Dissertation (Ricky Patterson, 2023)
- Overleaf/LaTeX for Tables and Figures (Ricky Patterson, 2023)
- Introduction to Zotero (Maggie Nunley, 2022)
- Advanced Zotero (Jeremy Garritano, 2020)
- MS Word for Theses and Long Documents (Christine Slaughter, 2019)
Reproducible Workflow
- Reproducible Analysis and Documentation with R and R Markdown/Quarto (Michael Lenard, 2024)
- Organizing Transparent and Reproducible Research (Jenn Huck, 2023)
Qualitative Analysis
- Introduction to Qualitative Analysis Principles (Christine Slaughter, 2023)
- Intro to Qualitative Analysis Using Dedoose (Christine Slaughter, 2023)
- Intro to Qualitative Analysis Using NVivo (Christine Slaughter, 2023)
Data Management
- Preparing Datasets for Publishing (Michael Lenard, 2024)
- Data Management for Humanists (Jenn Huck, 2023)
- Writing Data Management Plans with the DMPTool (Bill Corey, 2020)
- Research Data Management Practices (Bill Corey, 2019)
- LibraData and Dataverse: UVA’s Data Sharing Repository (Sherry Lake, 2019)
- Research Data Management Fundamentals (Bill Corey, 2018)
- Data Storage Best Practices (Bill Corey, 2018)
- Data Sharing and Archiving for Engineering (Bill Corey, Erich Purpur, 2018)
- Research Management and Reproducible Practices with the Open Science Framework (Ricky Patterson, Sherry Lake, 2018)
- Creating a Data Management Plan (Sherry Lake, 2015)
- Introduction to Database Design (Sherry Lake, 2015)
- Building Databases and Querying with MySQL (Sherry Lake, 2015)
- Introduction to Designing and Building Databases (Sherry Lake, Nancy Kechner, 2014)
- Documentation and Metadata (Anne Gaynor, Sherry Lake, 2014)
- Data Management for Graduate Students I: Why Should You Care about Managing Your Research? (Sherry Lake, Bill Corey, Purdom Lindblad, 2014)
- Data Management for Graduate Students II: Data Management for Humanists (Bill Corey, Sherry Lake, Purdom Lindblad, 2014)
- Finding and Acquiring Data (Bill Corey, Summer Durrant, 2014)
- Managing Collaborations (Bill Corey, 2014)
- Planning for Data Management (Ricky Patterson, Andrea Denton, 2014)
- Building and Using MS Access Databases (Sherry Lake, 2014)
- Best Practices for Data Management (Ricky Patterson, Andrea Denton, 2014)
- Creating a DMP (Sherry Lake)
- Collaboration Management Tools (Bill Corey, 2014)
- Decennial Census: Finding and Accessing Data (Summer Durrant, 2014)
- Data Preservation (Bill Corey, Kara McClurken, 2014)
- Preserving and Sharing Data: Best Practices & Requirements for Selecting a Data Sharing Repository (Bill Corey, 2014)
- Data Management: Documentation and Metadata (Sherry Lake, Bill Corey, Jeremy Bartczak, 2013)
- Gaining an Advantage by Sharing Your Research Data (Andrew Sallans, Bill Corey, 2013)
- Versioning (Sherry Lake, Bill Corey)
- Data Wrangling and Interoperability (Ricky Patterson, Andrea Denton, 2013)
- Choosing between data sharing repositories for Engineering (Sherry Lake, 2013)
- Choosing between data sharing repositories for the Humanities (Bill Corey, 2013)
- Choosing between data sharing repositories for the Life Sciences (Andrea Denton, 2013)
- Choosing between data sharing repositories for Social Sciences (Bill Corey, 2013)
- Best Practices for Collecting Data (Bill Corey, Andrea Denton, 2013)
- Data Management: Documentation and Metadata for Engineering and Physical Sciences (Ivey Glendon, Jeremy Bartczak, 2013)
- Introduction to Databases for Managing Research Data (Sherry Lake, Bill Corey, 2013)
- Workflow Systems for Life Sciences and Social Sciences (Bill Corey, Andrea Denton, 2013)
- Workflow Systems for Engineering and Physical Sciences (Andrew Sallans, 2013)
Miscellaneous
- Funding Discovery Tools (Ricky Patterson, 2020)
- Census Data Basics (Jenn Huck, 2019)
- Introduction to QGIS, additional materials (Erich Purpur, 2019)
- Publish or Perish! Research Metrics for Academics (Erich Purpur, 2018)
- Websites with GitHub and Jekyll (Doug Chestnut, 2017)
- Introduction to ORCID (Ricky Patterson, 2017)