Materials for the August 2019 R bootcamp at UC Berkeley. See below (under the listing of files) for information about the bootcamp, including logistics, how to get the course content, and how to install the software you need for the bootcamp on your laptop.
Note that the actual content of the modules is still under construction. Materials from last January's bootcamp are similar, so if you'd like to look at materials before I have finalized this site, please see you may want to view https://github.com/berkeley-scf/r-bootcamp-winter-2019.
Co-trainers: UC Berkeley Statistics, D-Lab, and the Statewide Database at Berkeley Law
This is the website for the seventh annual R bootcamp at Berkeley. The bootcamp 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 statistical work in R
- more advanced topics: efficiency, object-oriented programming, advanced graphics, batch jobs, parallel processing
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.
Course logistics
Location: Koret 105 (UC Berkeley Law School), UC Berkeley campus (map).
Time:
- Saturday, August 24, 8:15 am - 5 pm
- Sunday, August 25, 9 am - 4:30 pm
We'll start formally on Saturday morning at 8:30 am, but please plan to get here by 8:15 so you can sign in and get settled. And if you need help with any software installation please come at 8 am.
Note that street parking in Berkeley near campus on Saturdays is generally subject to two hour limits.
Course content is available through Github. Please download a copy of the course materials before arriving at the bootcamp using one of the two options below (if you're familiar with Git you'll also know how to do this by cloning the repository):
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open RStudio. Go to “File→New Project” and select “Version Control” and “Git”. Enter 'https://github.com/berkeley-scf/r-bootcamp-fall-2019' as the “Repository URL” and click “Create Project” (you can choose the directory in which to place the project with the “Create project as subdirectory of” option). It should create a “r-bootcamp-fall-2019” directory with all of the materials within whichever directory you chose. To open one of the R Markdown files, go to the lower right panel, click on 'Files', then 'r-bootcamp-fall-2019', then 'modules' and finally click on the .Rmd file of interest. It will open in the upper left panel.
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Alternatively, simply download a zip file containing all the content at https://github.com/berkeley-scf/r-bootcamp-fall-2019/archive/master.zip.
Here is the schedule for the main track of the bootcamp. We will also offer a second track that allows those first encountering R or programming to have time for more intensive practice with the initial material. Here is the schedule for the second track. After lunch on the first day you'll have the opportunity to decide whether you want to stay with the main track or attend the second track. You do NOT need to decide in advance.
We recommend that you take a look at the syllabus and the background module (https://htmlpreview.github.io/?https://github.com/berkeley-scf/r-bootcamp-fall-2019/blob/master/modules/module0_induction.html) in advance to get a sense for what we'll cover. And for those of you with absolutely no experience with R, it will help with your learning curve if you try to play around with R using the material in (https://htmlpreview.github.io/?https://github.com/berkeley-scf/r-bootcamp-fall-2019/blob/master/modules/module1_basics.html) beforehand.
For the presentation materials (including embedded demo code), see the html files in modules. The slides files have individual pages, while the other html files are one continuous page per module. To run the demo code, open the .Rmd file for the module in RStudio. You can then run individual chunks of code.
Please come with a fully-charged laptop (Mac, Windows, or Linux are all ok) with R, RStudio, and Git installed. RStudio and Git are optional but highly recommended.
To install the software, it's best if you can install software directly on your laptop.
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Install the following directly on your laptop:
- R (details here)
- RStudio (optional but highly recommended) (details here)
- Git (optional but recommended for obtaining course content) (details here)
Alternatively, IF INSTALLING ON YOUR LAPTOP FAILS, the following is an alternative way to access R and RStudio through a browser:
- Please use your CalNet ID and password to login here. Once logged in, you should be in an RStudio session in the browser. At this point you can get a copy of the bootcamp files that your RStudio session can access by following instruction #1 above under the section "Preparing for the course - course content".
Note that our ability to troubleshoot R or RStudio installed directly on your machine is limited (particularly in Windows). We'll try to help, but if we run into roadblocks, we'll direct you to the browser option.
In general, please use the Google group discussion board for questions during the bootcamp or if you have software installation problems or logistical questions before the bootcamp. The discussion board can be accessed through your browser or by email to [email protected].
If you need to contact us directly with an administrative question you can email [email protected].
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