The swirl assignments follow a progressive structure and that's great, I was able to complete most of it even though I am totally new to programming. But the readings are not as easily comprehensible. There could be also more videos with examples. For instance, taking a look at the syllabus I don't think I'm completely able to import data from the web without a considerable amount of effort. And there was no swirl assignment on this specific subject. I've considered the course ok for a first approach to the R environment, but could improve a lot in the issues I've mentioned. Best regards, Henrique

There is no relation between the readings and assignments. At the first video they mentioned that this course is designed for students with few programming experience(not in R!!). I have 10 years of programming experience with R, and I am sure that this course needs at least many years of programming experience with R.

The funny part of this course is that, they have just copied some part of an advanced R book, but they ask some simple introductory questions.

I am completely confused with this course :(

The course readings and exercises did not line up well with each other, and neither lined up well with the final exam. I really wanted to know more about tidying data and merging datasets but I feel like I kind of only got through the final with trial and error, rather than true understanding. I explored the forums and saw other people being frustrated. One post says this is just how JHU courses are....so I think I will try some R courses next from a different source.

Good intro and base for learning R programming. SWIRL tutorial nearly perfect for beginners like me. Quiz questions are fair but some questions are a bit vague and can have multiple interpretations as to what it is actually asking. Perhaps if the questions removed any ambiguity it would make it easier for newbies to work though the quiz questions without getting too frustrated to the point that they want to give up.

This course provides an amazing learning path for people who don't know R. Week by week examinations and work in the Studio environment are great to keep learning in a proactive way. The book has a huge amount of info and it is perfect for approaching R. Just I think the level required for final examination is way higher than what it was very well taught during the course.

The difficulty with Week 2 Lesson 3 - Data Manipulation took months to find my own solution (one posted noted they used another computer). My resolution was not using Lab Sandbox. The 'SSL connect error' online help was somewhat instructive but did not resolve my issue with the constant error when attempting to download ‘titanic’ package.

Beyond Frustrating!

The course content itself is good and easy to follow, but one assignment has a recurring bug since at least 2 years back that prevents other students from successfully submitting a required assignment. Despite a long and active thread regarding this bug, the problem has yet to be addressed, preventing some students from completing the course.

There are a lot of typos, spelling errors, and oftentimes you need to do your fair share of StackExchange, forum, or book research to get an answer. I learned a lot, I just wish it was better organized. You'll learn more experimenting yourself than you will from the class.

While I learned much from this course, I would say that the readings contained enough type-o's and broken links that it became slightly annoying. Also, the final Quiz was much more difficult than the readings/practice that came before it.

I feel that the training could be more extensive prior to assignments. The assignments often cause me to randomly search packages for correct functions to use and how to apply proper syntax, etc.

Aunque el curso está bien explicado y maneja buenos contenidos, hay varios problemas al subir las tareas por el programa que se maneja, los cuales son muy molestos y hacen perder mucho tiempo

You can learn most of it through the package swirl but the quiz at the end was a rewarding challenge that gave good practice. Would make it much better if it had video tutorials however

This is a fairly good course.The interactive R environment is a little rigid and acknowledges correct answers only when certain specific codes are used but all in all .its good

This is a refresher course for someone who already knows R. For anyone starting to learn R and Data Science, Data Science Specialization is a good curriculum to start with.

The instructors did nothing. They did not even respond to a single question through the entirety of the course. The information in the readings was helpful though.

If I didn't already have experience in R, and with tidyR in particular, I'm not sure this course would have been that helpful. As it was, it was a good review.

One must have some R knowledge prior to take this course. I would recommend to take the other R programming course from the Data Science track before.

The use of swirl proved to be confusing to do week 2 test. I had to read the comment threads to figure out which subjects were needed for the quiz.

The course difficulty abruptly increased in the last week.Especially with the last quiz. A swirl exercise before the quiz would have been helpful.

Leaves you in the dark A LOT. Outside resources like google very necessary for learning extra programming/shortcuts for the course.

Quick and easy introduction to R. Doesn't go into any depth, no videos and not very challenging assignments. Would not recommend.

Wrong tutorial on swirl that obliges you to follow the course twice to get the code for the quix and to take the points to go on

This course is very hard to follow at times as it is not explained what needs to be done and you need to guess couple of steps

Less practice items in this course. Majority is theory. Would have preferred if it had a some more practice material.

low production value at times, frustrating errors in the course data and instructions, but got me there in the end