[Adam_O]

From the perspective of a student, most of the good online analytics/data analysis/stats courses use R, so it is hard to get away from it while learning the material. Once you get the base concepts down, switching to python shouldn't be hard. I think most people still prefer ggplot2 for visualization though. Whenever I use R I feel like a statistician, I can feel that 'cold rigor' emanating from the language. But in the end I think it is advantageous to wield both languages.

Also I really see Jupyter as a new standard for communication. Your narrative and supporting code all in one place, ready for sharing.

[rasbt]

Yes, I think you are right. Out of curiosity, when I browsed over Coursera's course catalog, most data science related material seems to be taught in Matlab or R (however, there are also others, e.g., Klein's Linear Algebra class in Python). Personally, I think that instructors shouldn't enforce a language requirement. I believe for big platforms such as coursera it shouldn't be to hard to run an respective interpreter to check the code/answer uploaded by a student.

[digitalzombie]

Most classes have to teach the subject and how to program. Programming is beginning to be an essential skills so they have to choose a language to teach.

Also those classes that chose R, from my experiences, are non CS classes, the professor are from other discipline. They just want a tool that solve their need quick. An example is the Princeton's Stat class, the professor is a humanity major. The class gave us tons of data and we had to do ANOVA and such and we needed a computer to crunch so number can't do by hand. So he chose R which he uses a lot.

[IndianAstronaut]

Jupyter is amazing. It is great to see workflow and makes it easy to graph and find trends in the data, as well as mistakes in a data flow.