Monday, May 15, 2017 in San Francisco
Two and a half hour morning workshop: 9:00-11:30am
R Bootcamp: For Newcomers to R
Intended Audience: Practitioners who wish to learn the nuts and bolts of the R language; anyone who wants "to turn ideas into software, quickly and faithfully."
Knowledge Level: Experience with handling data (e.g. spreadsheets) or hands-on familiarity with any programming language.
This half-day workshop launches your tenure as a user of R, the well-known open-source platform for data analysis. The workshop stands alone as the perfect way to get started with R, or may serve to prepare for the more advanced full-day hands-on workshops, “R for Predictive Modeling”.
Designed for newcomers to the language of R, "R Bootcamp" covers the R ecosystem and core elements of the language, so you attain the foundations for becoming an R user. Topics include common tools for data import, manipulation and export. If time allows, other topics will be covered, such: as graphical systems in R (e.g. LATTICE and GGPLOT) and automated reporting.
The instructor, a leading R developer and the creator of six R packages, including CARET, a core R package that streamlines the process for creating predictive models, will guide attendees on hands-on execution with R, covering:
- A working knowledge of the R system
- The strengths and limitations of the R language
- Core language features
- The best tools for merging, processing and arranging data
Hardware: Bring Your Own LaptopEach workshop participant is required to bring their own laptop running Windows or OS X. The software used during this training program, R, is free and readily available for download.
Attendees receive an electronic copy of the course materials and related R code at the conclusion of the workshop.
- Workshop starts at 9:00am
- End of the Workshop: 11:30am
Max Kuhn, Software Engineer, RStudio
Max Kuhn is a software engineer at RStudio, a leading company for R software and tools. He is currently working on improving R's modeling capabilities. He has a Ph.D. in Biostatistics.
Max was a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years.
Max is the author of eight R packages for techniques in machine learning and reproducible research and is an Associate Editor for the Journal of Statistical Software. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015.
He has taught courses on modeling, including many classes for Predictive Analytics World, the useR! conference, the Open Data Science Conference, the India Ministry of Information Technology, and others.