The course doesn't really develop an understanding of Data Management and Visualization outside of the context of SAS or Python syntax. Also there are a number of points throughout the course that would benefit from an update most particularly the initial documentation to get started with SAS. The LIBNAME in the downloadable PDF is incorrect and it took me a significant amount of effort to identify and resolve the error since I was unfamiliar with the process.

This course states that it is for people with no knowledge in SAS. I had to go online elsewhere to learn SAS before completing this course. There are free SAS tutorials on the SAS webpage - I highly recommend completing them before trying this course.

This course covers the basic data management and visualization using SAS and Python. I like the simplicity and straightforwardness of the contents. Will continue to explore this specialization.

I wanted to do the whole specialization this course is a part of, but the forums are inactive and questions go unanswered... You're also at the mercy of peer reviewers, who may grade unfairly if there are technical difficulties, and who may not grade you in a timely manner. (Or they don't submit their assignments so you can grade them in a timely manner.) The videos have WAY too much B-roll and not enough visual aids.

I am a beginning Python coder and took this class to expand my Python knowledge, and I have a science background so I understand a lot of the math going on here, but I don't think this course would be a good choice for anyone without familiarity with Python. Perhaps if I'd taken the SAS route with the intention of learning SAS I would've had a different experience.

I came into this course after getting a rough idea about data analysis (from the IBM introduction courses), and this definitely adds on to the experience. The instructors make sure that the student is conceptually sound by the end of the course. Highly recommended.

Felt like a lot of the lessons were more about just following the directions or structure of the videos and not really learning the actual language of SAS or Python and how to be creative with it. I feel like I know how to use them at this point, but only for the specific commands we were instructed on. However, material is clear and easy to follow. I am not a fan of the overall Coursera structure of peer graded assignments because it seems pretty arbitrary or you may do the work and just not get the right number of reviewers and then you're screwed.

The course has its positives, but overall does not perform well instructing on the use of the two statistical software offered (SAS & Python). At the beginning they offer multiple data sets to use and formulate a research question, but all the examples utilize only one data set and do not cover the differences you might face with the other data sets - leading to a lot of missed opportunities. Additionally, the tutorials for using the statistical software do not lend themselves towards a thorough understanding and more to a route learning.

They put a lot of effort into this course, but especially for the videos it was a bit too much. So many different visual backgrounds, sounds, music, text floating it... It's as if they just wanted to use everything, while never thinking about when it would start being too distracting.

The slides are excellent and instructions are clear and to the point. But that point is very limited. The main negative about this class is that there is absolutely no student/TA/teacher feedback and you're pretty much on your own learning.

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.

Course material needs to updated to reflect current software updates.

So many unanswered questions in the forum. Peer reviews suck

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.

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.

I was very enthusiastic at the beginning, althoug the lessons and how they were taught I did not like, I intended to complete the whole specialization courses. But soon I noticed this course is not attended by instructors or barely participants for many years -or so it seems-. The blog system was not very good, specially if the whole thing is not properly conducted and organized. Some informations are outdated and not corrected. The peer reviewing was bad, too. I was getting assignments to review, that are 2 to 7 years old and nobody cares if it blocks the whole reviewing process. Very annoying. I could not help peers and I could not get reviewed either, as one that I got to contact was also getting old assignments to grade until we graded each other. I wrote in Forums but no answer came. The participants, if any, did not appear to greet either. I am sad about this because I was eager to do the whole specialization but no way. I quit.

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.

Basically: The course is geared more towards those with quantitative research questions. While it's a good introduction to the theory of research data management, and they encourage you to choose your own research question/data set, it's quickly obvious that the lessons mostly apply to those with categorical data. As my research and work deals with qualitative data, there wasn't much for me until Week 4.

The support from the faculty and the website is beyond explainable bad. The user interface gets stuck without reasons. There is no direct way to contact the faculty, if you are stuck on any assignments. There is hardly anyone who responds to the feedback that is sought for!!

I will never recommend someone to do this course.