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When & Where
Sat, August 19, 2017 - 8:00 AM to Sun, August 20, 2017 - 4:30 PM
Genetics and Plant Biology (GPB) 100

The workshop will be an intensive two-day introduction to R using RStudio. Topics will include

  • R basics - reading and manipulating data, working with R data objects, doing calculations, making plots
  • programming in R
  • doing statistics/data analysis/data science in R
  • a brief intro to more advanced topics: efficiency, object-oriented programming, parallel processing in R

No prior experience with R is expected, but some familiarity with programming concepts such as variables, loops, if-then-else statements, functions, etc. will be helpful.

The course website is on Piazza.  If you have an @berkeley.edu email address you should be able to sign up yourself. If not, we'll have to add you, but we plan to add everyone who is signed up for the bootcamp soon. The Piazza site will also have instructions on how to prepare for the course, which is basically just getting the software set up on your laptop.

Course content will also be available and updated in real-time on Github: https://github.com/berkeley-scf/r-bootcamp-2017. See the Piazza site for further instructions on downloading material from Github through RStudio.

Registration: To attend you must register. Please fill out this form and we'll let you know within a week whether you're registered or on the wait-list. Priority will be given to Berkeley grad students, postdocs, staff, and faculty, followed by those affiliated with another university or government agency, then Berkeley undergrads, and finally participants from for-profit organizations. Undergraduates interested in R should consider taking Statistics 133. 

Cancelling your registration: If you have registered and realize you cannot attend, PLEASE let us know via this form so that we can let people on the wait-list attend. 

Questions? Email r-bootcamp@lists.berkeley.edu.

Co-Hosts: Statistics & D-Lab

D-lab Facilitator: 
Jon Stiles
Format Detail: 
combination of lectures/demonstrations, hands-on coding, and help from circulating assistants
Participant Technology Requirement: 
laptop with R and RStudio installed in advance