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DAT209 - Programming with R for Data Science

Programming R for Data Science is taught by Anders Stockmarr (on the faculty of Technical University of Denmark.) For US audiences, his accent requires some getting used to. He places emphasis on unexpected syllables and has a unique way of pronouncing many things. I found it helpful to use headphones and to adjust the playback speed of the recordings. It is worth making the effort to understand Dr. Stockmarr because he has put together a course with a lot of substance, using a tight script and backed up by supporting exercises.

Programming R Course Highlights

I genuinely enjoyed this course, it goes a lot deeper than the introductory course in R taken earlier in the MPP sequence. For the first course, I used RStudio to experiment. With this course, I wanted to use the Visual Studio version of R to work the exercises and labs. The R Tools for Visual Studio ( required some fiddling to get installed, but were stable and had nice IDE features I've become used to with VS. Becoming familiar with R Tools for Visual Studio at this point will prepare you for taking DAT213 "Analyzing Big Data in MS R Server" which is the logical follow-on course in the MPP Data Science sequence.

Modules for the course:

Programming with R
Anders Stockmarr
  •     Introduction
  •     Functions and Data Structures
  •     Loops and Flow Control
  •     Working with Vectors and Matrices
  •     Reading in Data
  •     Writing Data to Text Files
  •     Reading Data from SQL Databases
  •     Working with Data
  •     Manipulating Data
  •     Simulation
  •     Linear Models
  •     Graphics in R

While taking the R courses in this sequence, I found two supporting references particularly helpful:

DAT209 Course Content

There are a total of 43 videos with playing time of about 4.5 hours. The course requirements include:

  1. Quizzes worth 40% of grade,
  2. Labs worth 40%,
  3. The final challenge was worth 20%. With the final, you have four hours to answer 50 questions, and a maximum of four minutes to answer any single question. It is very helpful if you've kept notes through the lectures. It is not feasible to Google responses to these questions.

All told, this course required about 25 hours for me to complete.