Many Data Science teams today leverage both R and Python in their work, but struggle to use them together. Data Science leaders and their business partners find it difficult to make key data science content easily discoverable and available for decision-making, while IT Admins and DevOps engineers grapple with how to efficiently support these teams without duplicating infrastructure. Even experienced data scientists familiar with both languages often struggle to combine them without painful context switching and manual translations.
In this webinar, you will learn how RStudio helps organizations tackle these challenges, with a focus on some of the recent additions to our products that have helped deepen the happy relationship between R and Python:
Easily combine R and Python in a single Data Science project using a single IDE.
Leverage a single infrastructure to launch and manage Jupyter Notebooks, JupyterLab, VSCode and the RStudio IDE, while giving your team easy access to Kubernetes and other resources.
Share and manage access to R- and Python-based interactive applications, dashboards, and APIs, all in a single place.
Head of Product Marketing at RStudio
Lou is a passionate advocate for data science software and has had many years of experience in a variety of leadership roles in large and small software companies, including product marketing, product management, engineering, and customer success. He currently runs product marketing at RStudio, ensuring the best communication possible with RStudio's open-source and professional fans. In his spare time, his interests include books, cycling, science advocacy, great food, and theater.
Product Manager at RStudio
Sean leads teams to create useful, enjoyable products. Before RStudio he was a data scientist and worked on alternative vehicle models at NREL, infant sleep dynamics, and originally studied mathematics. He lives outside Denver, CO and skis and bikes with his family.
Jenny Bryan is a recovering biostatistician who takes special delight in eliminating the small agonies of data analysis. She’s part of Hadley’s team, working on R packages and integrating them into fluid workflows. She’s been working in R/S for over 20 years, serves in the leadership of rOpenSci and Forwards, and is an Ordinary Member of the R Foundation. Jenny is an Associate Professor of Statistics (on leave) at the University of British Columbia, where she created the course STAT 545.
Only 1,000 live attendees are allowed in the Webinar on a first come first serve basis. There will be approximately 45 minutes of presentation, followed by a live Q & A session.
We've started a Github repository with all webinar materials. Speakers for this webinar and all future webinars will add their materials to the repository. https://github.com/rstudio/webinars
If you can't attend, don't worry. We record (almost) every webinar and post all materials on our website within 48 hours. See past webinars at rstudio.com/resources/webinars
RStudio provides the premiere open source and enterprise-ready professional software for R, including RStudio Desktop, RStudio Server, RStudio Connect, RStudio Package Manager Shiny Server, and shinyapps.io. The tidyverse, shiny, ggplot, ggvis, dplyr, knitr, R Markdown, and packrat are R packages from RStudio that every data scientist will want to enhance the value, reproducibility, and appearance of their work.