Open Winnie-Chan-StatCan opened 1 year ago
Hi @Winnie-Chan-StatCan! Thank you so much for your time taken to provide feedback. To answer your questions:
There are separate R and Python curriculums. You can find the Python curriculum here: https://github.com/UNECE/ModernStats_Python
In the most recent round of changes, we've tried to unify the R and Python courses. For example, I added a lesson on data visualization (this was a highly requested addition)
I agree that working with large datasets is a useful skill to have in official statistics, and also that this may be outside the scope of a course for beginners. One option could be to link some resources at the end of the training to supplement this topic.
We hope to see you on Monday to discuss further. Thanks again for your input, it is really appreciated!
General comment to both the R and Python course structure:
Is there going to be one course, each for R and Python? The reason I ask is to understand whether we want to bring in chapters for more types of users in the course (that can range from fundamentals, data analytics, data cleaning, data pipeline, data visualization, etc.).
For the moment, I feel that the R course contains more fundamental concepts while the Python course contains more different components. Will we consider having a beginning course for both R and Python that contains similar topics? For the moment, I can see that the Python course has a chapter in data visualization, but this component is not covered in R (or is it covered under R fundamentals of plotting)?
In addition to fundamentals for beginners, I think many national statistics agencies would have to deal with large datasets and so probably introduction to how large datasets can be taken care of in the two languages would be helpful (e.g., processing, data pipeline, otpmization), but probably this would be best to be placed in a follow-up course as more packages might need to be introduced in addition to the base commands introduced in the first course (e.g. Panda and NumPy in Python).