Making the most of artificial and human intelligence for data science (Hadley Wickham, Joe Cheng) @PositPBC

Uploaded November 2025 | Updated September 2026, 1 week ago

Making the most of artificial and human intelligence for data science

💬 Speaker(s): Hadley Wickham; Joe Cheng

📝 Abstract:

This presentation explores the complex and often contradictory nature of large language models (LLMs) in data science, acknowledging the simultaneous excitement and apprehension that we feel toward these technologies. We’ll provide a practical framework to help you understand the LLM ecosystem (from foundation models and hosting to SDKs and applications) that supports our current philosophy: augmenting, not replacing human intelligence. The talk demonstrates how Posit is addressing this space through two complementary approaches: building SDKs and tools that help you create your own LLM-powered solutions, and developing integrated LLM capabilities directly into data science workflows through tools like Positron assistant and databot. We’ll showcase practical, immediately useful applications while addressing current limitations, providing you with both the emotional preparation and technical foundation needed to effectively leverage LLMs in their data science practice today. posit::conf(2025) Subscribe to posit::conf updates: posit.co/about/subscription-management

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$Using R package structure for data science projects | Kylie Ainslie | Data Science Lab The Data Science Lab is a live weekly call. Register at pos.it/dslab! Discord invites go out each week on lives calls. Wed love to have you! The Lab is an open, messy space for learning and asking questions. Think of it like pair coding with a friend or two. Learn something new, and share what you know to help others grow. On this call, Libby Heeren is joined by Kylie Ainslie who walks through how structuring data science projects as R packages provides a consistent framework that integrates documentation for you and facilitates collaboration with others by organizing things really well. Kylie says, I stumbled on using an R package structure to organize my projects a number of years ago and it has changed how I work in such a positive way that I want to share it with others! In a world where our attention is constantly being pulled in many directions, efficiency is crucial. Structuring projects as R packages is how I work more efficiently. Hosting crew from Posit: Libby Heeren, Isabella Velasquez Kylies Bluesky: @kylieainslie.bsky.social Kylies LinkedIn: https://www.linkedin.com/in/kylieainslie/ Kylies Website: https://kylieainslie.github.io/ Kylies GitHub: https://github.com/kylieainslie Resources from the hosts and chat: 🔗 posit::conf(2026) call for talks: https://posit.co/blog/posit-conf-2026-call-for-talks/ 🔗 Kylies posit::conf(2025) talk: https://www.youtube.com/watch?v=YzIiWg4rySA 🔗 {usethis} package: https://usethis.r-lib.org/ 🔗 R Packages (2e) book: https://r-pkgs.org/ 🔗 Paquetes de R (R Packages in Spanish): https://davidrsch.github.io/rpkgs-es/ 🔗 {box} package: https://github.com/klmr/box 🔗 extdata docs in Writing R Extensions: https://cran.r-project.org/doc/manuals/R-exts.html#Data-in-packages-1 🔗 Tan Hos talk on NFL data: https://tanho.ca/talks/rsconf2022-github/ 🔗 {rv} package: https://a2-ai.github.io/rv-docs/ 🔗 Whether to Import or Depend: https://r-pkgs.org/dependencies-mindset-background.html#sec-dependencies-imports-vs-depends 🔗 {pkgdown} package: https://pkgdown.r-lib.org/ 🔗 Edgar Ruizs {pkgsite} package: https://github.com/edgararuiz/pkgsite Attendees shared examples of data packages in the chat! Here they are: https://kjhealy.github.io/nycdogs/ https://kjhealy.github.io/gssr/ https://github.com/deepshamenghani/richmondway https://github.com/kyleGrealis/nascaR.data https://github.com/ivelasq/leaidr ► Subscribe to Our Channel Here: https://bit.ly/2TzgcOu Follow Us Here: Website: https://www.posit.co The Lab: https://pos.it/dslab Hangout: https://pos.it/dsh LinkedIn: https://www.linkedin.com/company/posit-software Bluesky: https://bsky.app/profile/posit.co Thanks for learning with us! 💛 Timestamps: 00:00 Introduction 06:17 Reviewing the disorganized project example 10:01 Creating the package structure using create_package 17:50 Organizing external data and scripts in the inst folder 22:55 Adding a README and License 29:06 What are the advantages to packaging a project? 33:35 Writing Roxygen2 documentation 36:06 Do you type return at the end of your functions? 41:55 Handling dependencies with use_package 43:53 Can you just use require(dplyr) at the top? 47:45 Setting up a pkgdown site 50:11 Creating vignettes 52:22 What is the role of the usethis package? 54:18 Loading the package with devtools::load_all$

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