Session 1: Open-Source computing Tools and AI Basics
Session 1: Open-Source computing Tools and AI Basics
Format: Webex Webinar
Date: August 4, 2026
Time: 10am – 12pm EST
Speaker: Dr. Eric Stokan
Description:
This introductory session will provide an overview of the training series, including the topics, tools, and learning opportunities that will be offered. Participants will learn what is meant by open-source software, how open-source tools differ from commercial platforms, and which tools can support data management, analysis, visualization, and organizational decision-making.
The session will also introduce the fundamentals of artificial intelligence and generative AI. Topics will include:
- What do we mean by artificial intelligence and generative AI?
- What can—and cannot—current AI tools do?
- What are appropriate use cases for nonprofit and community organizations?
- What are the limitations and risks of using AI?
- How can organizations use tools like R to automate processes, increase transparency, analyze, and visualize data?
A brief baseline survey will be administered during the session. Participants may be eligible to earn UMBC microcrodential badges.
Session 2: Data Wrangling and Management with Open-Source Tools (R Programming)
Session 2: Data Wrangling and Management with Open-Source Tools (R Programming)
Format: In-person at UMBC
Type: Data Acquisition and Cleaning Lab
Date: TBD
Day/Time: Thursday: 10am-2pm (Lunch provided)
Length: 4 hours
Speaker: Eric Stokan
REGISTER
Description:
This introductory session will provide an overview of the training series, including the topics, tools, and learning opportunities that will be offered. Participants will learn what is meant by open-source software, how open-source tools differ from commercial platforms, and which tools can support data management, analysis, visualization, and organizational decision-making.
The session will also introduce the fundamentals of artificial intelligence and generative AI. Topics will include:
- What do we mean by artificial intelligence and generative AI?
- What can—and cannot—current AI tools do?
- What are appropriate use cases for nonprofit and community organizations?
- What are the limitations and risks of using AI?
- How can organizations use tools like R to automate processes, increase transparency, analyze, and visualize data?
A brief baseline survey will be administered before the session.
Session 3: Data Visualization, Dashboards, and Github (R Programming- GGPLOT2, Shiny App, and Github)
Session 3: Data Visualization, Dashboards, and Github (R Programming- GGPLOT2, Shiny App, and Github)
Format: In person at UMBC
Type: Hands-on lab
Date: TBD
Day/Time: Thursday: 10am-4pm (Lunch provided)
Speaker: Dr. Eric Stokan
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Description: This session translates data into clean visualizations that can be used to address questions of funders and boards. This session will start with the basics of data visualization in GGPLOT. Beyond learning how to produce several types of visualizations, this session will cover how to host them on a dashboard in R.
The session will include:
- Using Gemini/ChatGPT to generate ggplot code to work with data
- Asking AI to handle messy data (missing values, reformatting columns)
- Describing data and developing charts, tables, and figures
- Refining colors, themes, and labels of visualizations
- Using AI to generate a Shiny UI for a web-interface and hosting on Github pages
Session 4: Working with open-ended data like feedback from a survey
Session 4: Working with open-ended data like feedback from a survey
Format: In Person: Urban Institute, Washington, DC
Type: Hands-on lab
Date: TBD
Day/Time: Thursday: 10am-1pm
Speaker: Dr. Eric Stokan
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Description: Many organizations collect feedback but do not have an efficient way to analyze open-ended responses, notes, focus-group comments, or surveys.
This section would be divided into two sessions. The first session covers survey data basics: frequencies, cross-tabs, missing data, and basic plots. The second covers qualitative feedback using R and AI: coding themes, identifying common concerns, and turning qualitative comments into a short findings memo.
Session 5: LLMs and Prompting Practices for Best Use Cases
Session 5: LLMs and Prompting Practices for Best Use Cases
Format: Virtual
Type: Virtual lab-oriented
Date: TBD
Day/Time: Thursday: 10am-1pm
Speaker: Dr. Eric Stokan
REGISTER
Description: Many organizations collect feedback but do not have an efficient way to analyze open-ended responses, notes, focus-group comments, or surveys.
This section would be divided into two sessions. The first session covers survey data basics: frequencies, cross-tabs, missing data, and basic plots. The second portion will cover qualitative feedback using R and AI: coding themes, identifying common concerns, and turning qualitative comments into a short findings memo by detecting consistent themes.