r-bootcamp-fall-2022

2022 R bootcamp schedule

The bootcamp will be held August 20-21, so Day 1 is August 20 and Day 2 is August 21.

Unless otherwise noted, modules are about 75 minutes long: 40 minutes for presentation, 25 minutes for breakout and 10 minutes for discussion of solutions.

Day 1

Day 1 morning (8:30-12:15) (learning R)
- Module 0: Introduction, what is R, starting R, why R? (Chris) (15 minutes)
- Module 1: Basics of R, with RStudio (Chris presents)
  - R as a calculator
  - helpful shortcuts: tab-complete, up arrow, Ctrl-{up arrow}
  - vectors, indexing, and subset assignment
  - some basic functions; help()
  - vectorized calculations
  - basic R objects: vectors, dataframes, lists
  - basic graphics
  - breakout problems
- Break (15 minutes)
- Module 2: Managing R and your analyses (Chris presents)
  - managing R objects, the R workspace
  - using packages (installing, loading, namespaces)
  - the working directory
  - file reading/writing
  - Git, GitHub and version control
  - getting R help online
  - breakout problems
- Module 3: Working with data (Chris presents) (45 minutes)
  - dataframes, lists, and matrices
  - attributes, missing values and factors
  - subsetting
  - strings
  - breakout problems
Lunch (on your own) (12:00-1:30)
Day 1 afternoon (1:30-5:00) (data processing and manipulation)
- Finish Module 3 as needed
- Module 4: Calculations (Alan presents)
  - vectorized calculations and efficiency
  - apply, lapply (map operations)
  - tabulation, stratified analyses,
  - merging/joining tables
  - breakout problems
- Break (15 minutes)
- Module 5: Programming in R (Chris presents)
  - writing your own functions, function arguments, functions as objects
  - basic scoping and environments
  - loops, if-else
  - breakout problems/homework

Day 2

Day 2 morning (9-12:45) (programming and data analysis)
- Module 6: Data manipulation using the tidyverse (Corrine presents)
  - dplyr overview and piping
  - stratified analyses: groupwise operations and split-apply-combine using dplyr
  - reshaping and tidying data
  - breakout problems
- Break (15 minutes)
- Module 7: Graphics (Florica presents)
  - base R and ggplot2 overview
  - ggplot2 basics
  - using aesthetics to control plotting
  - exporting graphics (vector/raster formats)
  - breakout problems
- Module 8: Data analysis (Chris presents)
  - regression, GLMs
  - smoothing
  - optimization
  - simulation, sample()
  - dates and times
  - breakout problems
Lunch (on your own) (12:45-2:00)
Day 2 afternoon (2:00-4:30) (more advanced topics)
- Module 9: Workflows, coding practices, and project management (Chris presents) (60 minutes)
  - debugging, timing, memory use
  - scripting, source(), batch jobs
  - good coding practices
  - reproducible research
- Break (20 minutes)
- Module 10: Advanced topics morsels (Chris presents) (60 minutes)
  - object-oriented programming (S3, S4, R6)
  - computing on the language (using R to write and evaluate R code)
  - errors and try-catch
  - encodings
  - working with databases
  - parallel processing: future, parallel lapply, parallel for loops, RNG issues
- Module 11: Wrapping up (Chris presents) (5 minutes)
  - R inconsistencies and different ways to do things
  - Where to learn more (campus and non-campus resources)

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