Gov R Conference
As the Government & Public Sector R Conference celebrates its 7th year, we are excited to bring together top-tier data scientists once again, fostering the exchange of groundbreaking research and presentations both in Washington D.C. and virtually worldwide on October 29th & 30th! The talks will highlight work in government, defense, the public sector and non-governmental organizations.
Workshops: October 28 | Location: Georgetown University
Conference: October 29-30 | Location: Georgetown University
Workshops: October 28
Location: Georgetown University
Conference: October 29-29
Location: Georgetown University
Speakers
Tyler Morgan-Wall
Research Staff
Institute for Defense Analyses
Talk: Quarto, AI, and the Art of Getting Your Life Back
Selen Stromgren
Associate Director
U.S. Food and Drug Administration
Talk: Document Detective Work: Harnessing NLP in R to Create a Concept of Operations for a Large Organization (Joint Talk with Danielle & Evgeny)
Alex Gold
Director of Solutions Engineering
Posit
Talk: Everything You Never Wanted to Know About Auth
Abigail Haddad
Machine learning engineer -- AI Corps
Department of Homeland Security
Talk: Finding Your Next Federal Data Job
Princess Onyiri
Senior Data Scientist
Bloomberg Law
Talk: SEC Board Diversity Requirements: Are NASDAQ Companies Disclosing Their Data? (Joint Talk with Brittany Long)
Rachel Gidaro
Assistant Professor
United States Military Academy
Talk: An Introduction to Estimation and Comparison of Discrete Variate Time Processes
Jared P. Lander
Chief Data Scientist
Lander Analytics
Talk: Mapping Ever Larger Data with PostGIS, DuckDB, GeoArrow and deck.gl
Jessica Klein
Data Scientist
United States Census Bureau
Talk: The Role of R in Census Bureau Data Reporting
Frederick Thayer
Data Scientist
NAVAIR Proposal Analysis Team
Talk: Defending Your Data: When Best Practices Don’t Apply
Laura Gast
Data Science & Analytics Manager
USO
Talk: Making Things Difficult: The Role of Disfluency in Science Communication
Brittany Long
Assistant Team Lead, Data & Surveys
Bloomberg Law
Talk: SEC Board Diversity Requirements: Are NASDAQ Companies Disclosing Their Data? (Joint Talk with Princess Onyiri)
Danielle Larese
Chemist/Scientific Coordinator
U.S. Food and Drug Administration
Talk: Document Detective Work: Harnessing NLP in R to Create a Concept of Operations for a Large Organization (Joint Talk with Selen & Evgeny)
Alex Gurvich
Senior Graphics Designer & Data Visualization Specialist
NASA's Science Visualization Studio
Talk: Using Visual Perception in Data Visualization
Travis Riddle
Senior Research Fellow
Consumer Financial Protection Bureau
Talk: Who Are Your Consumers? Understanding Selection Bias Into Government Programs
Mary Gibbs
Senior Applied Scientist
Relativity
Talk: What's Your Vector, Victor?: Navigating Your Way through the FAA Order JO 7110.65 with RAG (Because GPS Doesn't Work Here)
Richard Schwinn
Financial Analyst
U.S. Securities and Exchange Commission
Talk: What is the best data format for your Shiny project?
Tommy Jones
CEO
Foundation
Talk: Detecting Automotive Quality & Safety Issues from Consumer Complaints
Evgeny Kiselev
Chemist/Scientific Coordinator
U.S. Food and Drug Administration
Talk: Document Detective Work: Harnessing NLP in R to Create a Concept of Operations for a Large Organization (Joint Talk with Selen & Danielle)
More speakers coming soon!
Speakers are subject to change.
Workshops
Better Development Practices with Large Language Models (LLMs)
Hosted by Abigail Haddad & Benjy Braun
Monday, Oct 28 | 9:00am - 5:00pm
In recent years, data scientists have increasingly adopted best practices from software engineering to improve code quality and project management. These practices are ideal candidates for leveraging Large Language Models (LLMs), as they are well-documented online and often involve tasks performed infrequently enough that memorization is impractical. This workshop will guide you through key software development practices tailored for data science. Participants will learn how to use LLMs to enhance their documentation, version control, and other essential tasks. The goal is to produce code that's easier to run, build upon, and understand, ultimately leading to more efficient and reproducible data science projects.
Workshop Highlights:
- Writing Cleaner, More Readable Code: Learn techniques to improve code readability and maintainability, with LLMs assisting in generating clearer syntax and structure.
- Improving Documentation: Discover how LLMs can help create comprehensive and understandable documentation, making your projects easier to use and collaborate on.
- Using Git for Version Control: Gain proficiency in using git for version control, with LLMs offering support in managing branches, resolving conflicts, and maintaining a clean commit history.
- Docker/Virtual Environments: Understand the benefits of containerization and virtual environments in development, and how LLMs can assist in setting up and managing these environments
- Debugging and Error Handling: Learn effective debugging techniques and use LLMs to interpret error messages and suggest fixes Participants will engage in practical examples using either Python or R, exploring how LLMs can be integrated into their development processes. While LLMs do not produce perfect code instantly, they are invaluable for iterative development, particularly in data pipelines and analyses. We will practice effective prompting strategies to guide LLMs towards better solutions and explore their ability to interpret error messages and suggest fixes in data science contexts.
Requirements:
- Comfortable writing a function in either Python or R
- Laptop with Python or R and git installed
By the end of this workshop, participants will have a toolkit of best practices and the skills to utilize LLMs for enhancing their development workflows, leading to more efficient and error-resistant coding practices. This workshop is ideal for developers, data scientists, and analysts looking to integrate advanced AI tools into their everyday coding routines.
(In-Person & Virtual Ticket Options Available)
Dashboards and CRUD Apps: Managing Data For Your Organization
Hosted by Maxine Drake
Monday, Oct 28 | 9:00am - 5:00pm
This class focuses on working with your organization’s data from data collection to data management to data visualization. We will learn how to build a dashboard with Shiny, including dynamic calendars perfect for large-scale event tracking. We will also build a CRUD (create, read, update, delete) application that allows users to manage data themselves. In addition to these technical skills, we will cover concepts, such as multi-tiered architectures, modularizing code, clear data visualizations, and managing user permissions in your Shiny apps.
(In-Person & Virtual Ticket Options Available)
Sponsors
Gold
Silver
Bronze
Supporting
If your organization is interested in being an event sponsor, please contact us at info@landeranalytics.com.