Good way to get introduced to the tiny verse packages and importing, prepping datasets before they can used for exploratory analysis and modelling.

Could have gone a bit more in depth on how to deal with dates, and regular expressions.

Course is great, specially the assignments. Don't depend on lecture videos too much, this is a programming course so you'll have to get your hands dirty. Don't forget to work on swirl() package, its a great way to learn interactively.

The content is good for the most part. There are some errors in the instructions to the assignment which make the assignment more like a real-world spec than the authors probably intended, but that's not necessarily a bad thing!

Great course. Could be more interactive and could have more detailed instructions for the Course Project. Last task for the Course Project uses a function that is not covered in previous lessons, which I think is not OK.

I really started to get interested in R only when I started this course.

Before that, it was just an old, cryptic language that could not do more than what I can do with Excel.

Now I am starting to see the full potential

It is a good course. I believe that the final project is challenging but quite extensive and requires dedication to solve it. I would have liked for this course, to establish a formal methodology for data cleansing.

Some files that were used for the examples were no longer accessible. Updates to the xlsx package also were not reflected or discussed. As I noticed on the forums several students had issues with java dependencies.

The 3rd course in the specialization was great in terms of the materials presented.

But the "homework" requirements were a little bit unclear most of the times, even though the actual solution was fairly simple.

Capstone project is a little ambiguous. Although that's good experience having to find a way to reason out what the objective is based on limited information.

Introduction to chained dplyr is incredibly useful.

Clearly structured course, but as with previous courses of the Data Science program, there is a gap regarding coding skills which the course does not till for those of us lacking a programming background.

Most of the course was interesting, well-designed and useful. Some lectures and links have to be upgraded. This is a really good course if you want to know what possibilities you have to get data with R.

Good course, instructors are very knowledgeable. Would be good to add more practical lessons and extend the course. As they say, repetition is the law of learning. Thank you for helping me get this far!

The assignment was excellent but challenging, instruction wasn't too clear or obvious though, struggled for a while (good kind of struggle)

The lecture was okay but the Swirl part is always fantastic.

I think that the level of difficulty of the exercises and final assignment does not match with the depth of the lectures; without a textbook, I feel lost, don't have a reference, and have to guess.

The 'cleaning data' part was explained pretty well... I do feel he could've gone into more detail for the 'gathering data' part- especially the webscraping part. Other than that, great course!

Very interesting and enjoyed doing the Assignment.

but the assignment instructions are not clear.A lot of time was wasted trying to figure out what data is what are what are we interested in.

The course was very helpful & guided but since I don't have a strong coding background I felt myself getting lost often. It would be really helpful if there is some guidance in assignments.

The course material is ok - it would really need a book like the other courses have. It is much easier to check something from a book than slides/video when doing the assignments etc. .

The Swirl practice part is great! But there is a big gap between what we learned from video/swirl and the course project! The project is much harder than what I learn from the course.

Good coverage of topics. A bit scattered in early slides and assignments were often inconsistent with coursework. Overall a great introduction of what to expect when gathering data.

Sometimes the instructions are not clear enough, and it was necessary to ask in the forums. Sometimes it feels "tricky" and makes harder to find the solution even in simple problems.

I found the last project insufficiently explained. I was struggling in understanding what the task is. A bit more clear task description (as in Course 2) would be really appreciated.

Actually, very interesting and helpful class. The one area around more complex structures (API, XML) warrants more attention, since I assume those are more dominant access methods.

good introduction and practice being given on handling data cleaning. Lesser thought on getting data merely introduction. Still good to give a try if you are new in data analysis.

The course is good, but I have met some inconveniences with week 4 tasks because of bugs in swirl ( they can be met when you in not USA timzone) and not-so-clear course project.