It was good overall, some of the course materials were a bit sparse. You had to do your own research into getting packages working in spyder etc.

I'd probably recommend that learners learn some python separately and read the docs for pandas.

A great idea to create a project based online course. We should focus on application based learning not on lectures. You need improve this course still. 4 weeks are to short.

We need more deep and more weeks.

It is a good beginners course but I think there are better lessons in SAS and Python if learning these is your goal, and the content in data cleaning and visual analysis is very basic.

Course content good but a little too basic in my eyes. I think the addition of more functions in SAS/Python would be useful. Having to do peer reviews is also not ideal.

Nice course to learn Python and some graphing libraries besides doing your own study from real-life data

good but i thought it will cover most of SAS technology. But it has covered basics only .

Course material needs to updated to reflect current software updates.

Very superficial. Too few in statistics, too much in python and SAS.

So many unanswered questions in the forum. Peer reviews suck

The course is good, although it goes a little to fast.

course should've had deeper python content.

Very basic level.

Better

The content is OK, but that's about it. Near zero interaction from staff, short videos leave a lot to be desired, and worst of all, there seems to be a problem getting everyone's assignments peer reviewed (which makes no sense).

There is a somewhat comical thread wherein staff direct students to contact coursera directly via a "contact us" link on a page, but get this, the link isn't there. Students repeatedly pointed this out only to get directed again to the non-existant link. In an online forum it's important to actually address concerns. Replys that avoid directly addressing concerns sound like automated messages. And that's the feeling I get here.

This course requires a DIY attitude and a willingness to proceed without feedback.

If you're looking for a good example of online learning, look elsewhere.

Some of the presented python code has been depreciated; this would be particularly challenging for students new to the code. The use of quantitative variables is not well described at the start of the course which would add challenges for students who choose these variables and are marked by students who have not. Having beginners marking beginners is not an effective evaluation technique. I did not receive useful feedback on assignments; typical statements included ".", "good work", and, "needs improvement".

A very beginner level course aimed at starters who dont have much experience with Data. Emphasis was on teaching Data Management with area of our interest. In Order to support this, assignments didnt had clear objective. I would have learnt a lot more through a course had they been more defined assignments.

Not a course if you are looking to be ready for data related interviews. However, this course will be okay if you are working on some other field and want data management as an extra skillset.

It is too small and shallow. Whole specialization is actually one full course split into 4 tiny parts.

I'M only 5 and i do not understand what x=x+5 means so make the quiz eazyer thx

Took way to long and tomuch effort to get assignments evalueted by peers

Some of the python code is not actual and has been deprecated

I felt like I was missing reading material throughout the entire course and had to search on the internet to figure out the answers to my questions. I discovered at the end of the final week assignment there was additional reading material that I should have seen at the beginning.

Throughout the course, no explanation was given for the code we were using and I do not feel I was taught to use Python or SAS in a way I could repeat outside of this course.

I chose to use the Gapminder dataset, which turned out to be a big mistake since it has no categorical variables. I could not complete assignments without learning Python from other sources, such as stackoverflow, since so little direction or explanation was given in the lesson.

At the end of each video a question is asked, but they often use terms that were never mentioned in the lesson. Again, it is as if there was a textbook I was supposed to read but I was not told about.

I am going to continue with the specialization, but I suspect online learning is not for me, since there is nobody to ask for help and the discussion forums are empty except for posts from several years ago.

The highest video production values of any class I've seen on Coursera so far. Unfortunately, that's the best part of the class; the support is simply nonexistent (a post by someone associated with the staff from a previous run of the course suggests getting help troubleshooting Python from Coursera staff), the instructions for the class software are out of date, the source material for the assignments is sometimes unsuitable to the task you're asked to perform (e.g. statistical analysis on a data set aggregated from disparate sources), and the pretty videos are at times completely unrelated to the actual assignments (the very first week with the literature review). Dropping this specialization like a hot coal; it looked quite promising, but the aggravation over the poor organization and lack of support considerably outweighs anything I could get out of it.

I am disappointed because the course doesn't provide profound material on data analysis with python. The videos are too short and the samples demonstrated in the videos aren't thoroughly explained. For instance, the speaker often only says what she is doing but not WHY she is doing it or what the function of a particular parameter is. I felt left alone and forced to google. In my opinion it cannot be the purpose to make your student google basic things that could easily be integrated into the course.

Considering that this is labelled as a beginner course I was expecting much more theoretical input. Other courses offer additional slides and scripts that are aligend with the course videos and allow the students to look things up.

Very disappointed about this course. The topic is very interesting, for me at least, but the course organization is horrible. Lectures do not provide enough information to complete the assignments. Zero interaction from course staff. Issues with getting assignments graded. In previous session the staff just refered you to the coursera helpdesk, but you cannot easily contact coursera directly.

Main focus of course seems to be earning money and not educating. Be warned and don't pay for this course!

I really don't get why this course has so many good reviews.

The professor and instructors don't understand how to properly write SAS programs and ignored constructive feedback. It's very sad to see students follow suit by producing hard to read codes, ignoring programming conventions.

As an analytic leader in healthcare industry (I am supervising some of my junior level team members to get some basic training), I want to say something to the students graduated from this course: if you program the same way as being taught, you will lose a competitive advantage during job interview.