One of the modules I teach is called "Programming for Big Data". It is normal when creating module descriptors not to be specific on what technologies will be used. So the module descriptor for this module does not specify what language will be used - it just states in general that "...programming languages such as R, Python, Java, etc" will be used. Last year I took over this module and decided to create a brand new set of course resources (I always do this when taking over a module, I just cannot use other lecturer's notes). As R is the preferred language in most other modules on our data analytics courses, and I was far more familiar with it - I decided to switch from Python, which had been used previously, to R.
Last evening at an Information Session for incoming students I was asked about this again, and would the students be learning Python. The answer is "No", and that we are continuing with R (students can choose in their Project module to use any language they wish). Today I decided to take a quick look at the 20th annual KDnuggets Software Poll (which had over 1,800 participants - so good sample size), and Python stands out the leading language. In 2017 Python and R were neck-and-neck (59% and 57% respectively), but this has changed in 2019 (66% for Python, and 47% for R). I am very glad to see that other technologies that we use in the Data Analytics programmes (RapidMiner, Excel/SQL/Tableau) feature strongly in the poll.
|Image source: KDnuggets.|
Much debate ahead!