I have recently took “R programming” course in Coursera. This is the second course I take there. Before that I took “Machine Learning” course which was much heavier course with respect both to what was taught, to the course length and to the assignments and other requirements.
- In the world of SciPy, Numpy, Pandas and others in Python I don’t really see the advantage in R. Those libraries have almost the same capabilities while Python is a much stronger and more common and therefore supported and documented tool.
- Visualizing the data – for me one of the best practices to gain better understanding of the data and to introduce the data to other people is creating a visualization. I really lack that part in Coursera course, I think that they should have done that extra mile, this would make the data processing more meaningful.
- I’m not an R expert now, not even close. However, I gained some background next time I will need to handle code in R or that I will need to consider using R in a project. I saw some similarity to Matlab syntax so this knowledge might be relevant there too.
- Language background, advantages, disadvantages, limits, theory (scoping, typing) etc. is important yet asking in a quiz from which university the language developers came from is not that interesting.
This is my code repository for this course, not brilliant implementation but those the job – https://github.com/tomron/rprog
Tom Ron 