Videos from Coursera’s four week course in R

December 11, 2012
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

Coursera's Computing for Data Analysis course on R is now over, with four weeks of free, in-depth training on the R language. While you'll have to wait for the next installment of the course to participate in the full online learning experience, you can still view the lecture videos, courtesy of course presenter Roger Peng's YouTube page. The course materials are helpfully organized into four video playlists by week; I've embedded each week's content below with an index to the individual video chapters.

Week 1:

  1. Introduction
  2. Setting working directory and getting help (Mac)
  3. Setting working directory and getting help (Windows)
  4. How to get help
  5. Overview and history of R
  6. Data Types
  7. Subsetting
  8. Vectorized Operations
  9. Reading/Writing Data: Part 1
  10. Reading/Writing Data: Part 2
  11. The 'str' function

Week 2:

  1. Control Structures in R
  2. Writing Functions
  3. Scoping Rules for R
  4. Optimization Application
  5. The mapply function in R
  6. Using tapply and split in R
  7. Using the apply function in R
  8. Using the lapply function in R
  9. Debugging tools in R

Week 3:

  1. Plotting (base graphics)
  2. Plotting with base graphics demo
  3. Plotting with lattice
  4. Plotting with lattice demo
  5. Mathematical annotation in plots
  6. Simulation in R

Week 4:

  1. Plotting and color in R
  2. Regular expressions
  3. Introduction to the Baltimore homicide data
  4. Regular expressions in R
  5. Classes and methods in R

These videos are a great resource for learning R at your own pace, but if you want the full Coursera experience with exercises and class interaction, you'll be able to find the next instance of the Computing for Data Analysis course when it next runs in January 2013 at the link below.

Coursera: Computing for Data Analysis

To leave a comment for the author, please follow the link and comment on his blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.