Considering AI for Data Analysis, using RStudio and Lumen

Have you considered using AI to help you make sense of data, or looked for an alternative to copy-pasting tables and code into ChatGPT?
Are you excited about the possibilities? Or apprehensive about data privacy, ethics, and other concerns?

Either way, this workshop is for you. We’ll discuss general benefits and concerns around using generative AI to help analyze quantitative data; factors that affect how well an AI model works, such as the model size, how you access it, and the “tools” it has access to. Then, I’ll demonstrate how I’ve been using a tool called Posit Assistant in RStudio, powered by models from NCSA’s Lumen, to gain the speed and efficiency of using AI while mitigating the potential costs.

About this event:

Presenters:

• Nathan Jeffery, Research & Survey Scientist, CITL Data Analytics

Track:

Summoning Tools — Reveal AI companions and productivity-enhancing powers. Showcase the tools, techniques, and automations that helped you clear your toughest encounters.

Experience Needed:

Beginner

Learning Outcome:

Participants will be able to:
– Identify available AI tools for data analysis
– Define terms relevant to using LLMs, such as “tool,” “API key,” and “agent harness”
– Analyze the pros and cons of using generative AI (in general) and various AI tools (specifically)
– Use an API key to access Lumen models in RStudio
– Perform exploratory data analysis using Posit Assistant

Additional Keywords:

quantitative methods, data analysis, AI, LLMs, AI agents, Lumen, RStudio, Posit Assistant,