I like the specialization quite a bit as it contains real world data and difficult enough exercises. This particular course is maybe not as good as the other courses I have taken (1,2,5) as the instructions lack a bit of clarity sometimes. However, the peer reviewed assignments are quite tricky and an excellent opportunity for learning. Took my some serious work to get this course done.

The first thing about the course is that the learning objective was clearer. And the content tied back to it, while also leaving room for self research and study. The project instructions could be a bit clearer, but perhaps the availability of the discussion forum allows this to foster curiosity and community interaction. Overall, it was a worthwhile course.

All Coursera data science courses have been designed very carefully. I found this course very beneficial as it explains the concepts and also tests the knowledge of the learner through tests.

In this course I learnt basics of fetching data from different sources like, API, Text-file, web-page e.t.c. Also I learnt cleaning data using various techniques.

Excellent course! Very useful videos, quizzes, and assignments. Provided the hands-on experience I was looking for. Improvement needs to be done to provide more technical information for doing the quizzes and assignments. Many critical details are being left out and students end up spending way too much time in digging them up via Forum, Google, etc.

Good introduction to getting and cleaning data and very useful learning about the principles of tidy data.

Jeff Leek isn't as good a tutor as Roger Peng and it was a bit frustrating following along at times as no hyperlinks are available for the data. The lessons are just recycled content from Jeff's lectures.

The course project was a good challenge!

Really great course material. I spent way too much time on the exams and projects, because i believe not enough information was given (had to spend a lot of time searching through discussion forums, stackoverflow, help files etc...and while that is useful experience, it was a lot more time commitment than expected from course description)

Honestly, I wanted to give complete 5 rating to this course, because the content of the lecture is well explained. But one feature I didn't like at all and that is Coursera has made it mandatory for the users to purchase the course in order to submit the quiz/assignment which I personally didn't like it. Except that the course is awesome.

Good course, better structured than course 1 and 2 of this programme. However, still a few of frustrating moments when the lecturers all of a sudden use language/jargon that cannot be understood by a beginner with little background in computer science (like me). Final coursework is ambitious, but answers can be found on the internet.

The course is more challenging than the prior two courses, but also very rewarding. I can apply the skills from this course directly to my work, and produce results.

A bit drawback is the some quiz questions and the final assignment can use more detailed instructions. Providing the clarity doesn't necessarily gives away the answers.

It's pretty good. It should provide a high-level approach to "getting and cleaning data"....and how it fits into the high-level roadmap of what Data Scientists do. Some of the quiz questions were written poorly - I expect better from an online course from a prestigious institution. I may have caught a few words misspelled as well.

The assignments were tough for me to handle. There should have been a step by step guide for the programs to be written just as in SWIRL exercises. Otherwise, the lectures are well understood. In general, I am quite fascinated by this course and look forward to learning more and better from other sources as well.

Very useful concepts taught in this course, one would be crawling data consistently as a full time data scientist. But even thought the pacing and project were good, I found the videos a touch boring. Nevertheless, it is part of the whole specialization, which in itself is serious education :)

Good course. I like it. However, it looks a lack of explanations or training for me. It possible, there too much material for this number of lectures, or just I haven't due background. Maybe, it makes sense to add more swirl courses for people like me to gain a proper comprehension.

I think the course in general is really good. The videos are very useful and although the subjects are not that intuitive, I find the materials very clear. The only negative point I can find is the fact that the quizzes are much harder than the final project and a bit to complicated!

The course of getting data is a little difficult, however, the cleaning data course is excellent. Using the package of "dplyr", I learn how to clean data effectively. My suggestion is that getting data from website can teach less, and the cleaning data course can add more practices.

A nice course overall, perhaps a few more excercises on the cleaning data side would have been helpful. In particular the melt, dcast and tidyR functions are tough to understand when seen for the first time. I did do the swirl activities for these and that helped some.

The course has very valuable information and teaches many useful skills. I would absolutely recommend it to anyone with an interest in programmatic data analysis and/or data science. It's not a flashy course, but it teaches very necessary support skills.

The material seems to be a bit outdated: some websites used in the web scrapping example, JSON APIs etc. seem to have changed they structure so the examples don't really work anymore. Also it's really annoying to have to type out all the URLs by hand.

Good course, although I felt that the outcome of the project should have been better defined. A mockup of the final results would have save me from wasting time through a misunderstanding of what was required (there is more than one interpretation).

Easy to follow. It would be beneficial to recommend this course before or with Introduction to R. Most courses that start teaching R programming, start with teaching about cleaning data before detailing other functionality. Nonetheless, good course.

Easy to follow. Might be too easy for some people with experience in data analysis. However, the instructors also talk about some frameworks and insights from their experience which could be helpful even for those who have some prior experience.

This course itself is quite nice and important.

However, I think that the instructor should have set more assignments to lead us know those techniques better.

Moreover, the ppt can be more detail-oriented.

Overall good but need improvement.

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!