This is a follow-up discussion thread for the webinar, "Debunking the R vs. Python Myth Webinar "
What You'll Learn
How many times have you heard the phrase "X is better than Y for data science"? This is a very common misconception among data scientists. For data science to be impactful, it needs to be credible, agile, and durable. To be able to do this, we need to embrace the differences between R vs. Python. Maybe you prefer R for data wrangling and Python for modeling - that's great! Why should serious data science be stifled for the sake of language loyalty? Data science teams need to use the wealth of tools available to them to deliver the most impactful results. This webinar will be a discussion among data science leaders, debunking this common myth.
Daniel Chen - PhD Student, Lander Analytics
Daniel Chen is a PhD student at Virginia Tech in Genetics, Bioinformatics, and Computational Biology ( GBCB ). He is a former RStudio intern working on the gradethis package and Author of Pandas for Everyone, the Python/Pandas complement to R for Everyone.
Data Management / GIT
Jared Lander - Chief Data Scientist, Lander Analytics
Jared Lander is Chief Data Scientist at Lander Analytics, Adjunct Professor at Columbia Business School, organizer of the New York Open Statistical Programming Meetup and the R Conferences in New York, Washington DC and Dublin. He is a Series Editor for Pearson and author of the best-selling book “R for Everyone.”
Carl Howe - Content Marketing Lead, RStudio
Carl drives RStudio's product marketing content strategy. Based on prior roles as both an educator and professional data scientist he is currently writing a series of thought leadership articles outlining the challenges facing Data Science Leaders today and how open source software can help Data Science teams thrive in today's business environment.
Sean Lopp - Product Manager, 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.
Lander Analytics is a New York-based data science firm, whose staff specializes in statistical consulting and infrastructure, running the full gamut of RStudio product assistance from procurement, implementation, and installation to ongoing maintenance and support. The firm also provides open-source training services for R, Python, Stan, Deep Learning, SQL, and numerous other languages. We assist organizations of all sizes on a global basis in a diverse set of enterprises that include financial services, government, energy, consumer goods, pharmaceutical, educational and professional sports.
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.