This course was hard to follow. I spent too much time figuring out how to access the required tools (e.g., Watson Studio). Video lectures go over irrelevant terminology that has little to do with applied skills in data science. Most of the quiz questions focus on minute details and not on the big picture. I eventually received the certificate but don't feel like I gained much from this course, especially considering how much time I spent on it.

Overall intro for open source tools that could be four stars if updated for current layout and usage of its star tool, IBM Watson. The inaccurate videos for Watson make this course very frustrating, and moreso because the final, graded project is expected to be completed on Watson despite the course's acknowledgement that the lectures need updating for that tool. It's doable, thanks to the other students posting tips in the discussion forums.

The course was like a search on a browser search engine. It is expansive in topics, but not thorough and deep on practical application. IBM courses should focus on deepening the knowledge, instead of stuffing definitions difficult to remember and history/power talks. I regret taking a course telling me about everything without teaching me a thing. I could only take the topics and learn them deeper on outside the course and very far from it.

This course is poorly designed and the material structure is so badly jumbled especially during peer review assignment where there's no consistency between one part and another. Plus, IBM Watson is a total headache where the version used in this course is totally outdated in terms of user interface so I have to find my own workaround plus the limitation from free version got me locked out until next month, so I have to use the lab version.

5 stars for the first two weeks, but the week about Watson is just terrible. The discussion board is full of complaints.

IBM should not promote itself this way.

Coursera should not spread this content and charge for it. It's a rip off.

The videos are totally outdated and it took literally hours and looking on the discussions on how to get to the point that I could do the application and the final assessment. IBM wasted my valuable time here.

HI,

I bought The specialized program with high hope of learn about Data Science with cero knowledge about it , but honestly it’s not a good course, the videos are totally out of date so you will find yourself lost on each lesson, your peers graded you assessments (someone as you without the knowledge to give a good feedback and grade you assessments) and many features of Watson Studio are not available in countries different from US.

I am personally found it very difficult to create a notebook on IBM Watson because course take the tutorial videos from IBM Watson itself without checking whether there is any updates where the UX changed significantly. I have to research Google and forums to find out the ways to create a notebook on IBM Watson. I hope that this review will help the authors of the course find it easier to update the course content.

Too much lip service to too many tools. After the first course in the specialization sets expectation that no tech or programming skills are essential as pre-requisites, this course comes along and introduces in the briefest possible way a plethora of tools.

The course will benefit by focusing on only IBM tools and one example from the open source world rather than the mention of so many tools all around the place.

Far too much focus on the proprietary IBM tools - in places the course felt like an advertising event to me. I had hoped that this course would provide a better overview of the many tools, but unfortunately other tools were only mentioned once at most. If this course was not part of the "Data Science" course, I would have dropped it. But I hope that the following courses will be more general again.

Well structured layout and solid indications of what the knowledge necessary for a learning path to data science. Which is appreciated as there is a lot information out there and difficult to filter out the noise. The course however is very light and lacks some real educational information. The content would need to be 'beefed' up considerably. And more rigorous quizzes and questions needed.

A lot of good information here which should have been rated higher, but everything took so much longer than it ought to have, because it was so poorly presented. The materials are outdated (or missing/difficult to find with the IRIS dataset) and difficult to follow. The course needs a complete update and overhaul by someone who understands online learning and user interface/user experience.

What they explain in video doesn't have similarity in accessing the real assignment, since its a paid course, they should at least review the content yearly the least.

It took away 2 days to figure it out on my own, in order to complete the assignment, and also disappointing there is no easy access to help of coursera.

Wasted a lot of time and energy, looks like learnt this one on my own.

It is basically just a brief overview off the interface and a narrator who reads the text of the tutorial. some of the R video's are out of sync. The Watson Studio one is so outdated that you have to find out yourself how the program works instead of watching a good introduction. overall I've learned nothing this entire course besides opening the program and clicking on the tutorial.

From Week 2 to Week 3 some video is not clear, not understable and not enough for video explanation. Some video rectiure video and voice is not clear voice. So, it is very difficult understand how to use IBM Watson studio. And, final assignment also is not enough information from lad. I have to check other outside site for IBM Watson studio Juypter notebook how to process and use.

The tools described didn't follow a clear flow making it hard to recall the purpose of each. It seemed odd to start off with Jupyter Notebooks and GitHub in more detail before covering other tools. The job aids for doing the labs were outdated which complicated following them and also impacted what it took to do the final assignment. This course needs a massive update and overhaul.

The course was ill-prepared - the videos were annoyingly long while not being too informative; big part of the course was simply an IBM marketing content. To conclude the course, the student has to sign up for an IBM service however the instructions are unclear and the sign-up path proposed by the course instructors is faulty, resulting in not being able to fulfil the assessment.

These courses are good, but still in the realm of the "memorize and regurgitate" type of class. As an adult who wants to learn concepts and dive into practice of those concepts, this course is a bit inhibitive with all of the chosen questions for quizzes. These prevent you from really grasping a concept, and have to focus more on nit-picky details of each lecture/video.

As a total and complete beginner when it comes to most things data science, computers, coding, programming, etc., this course was very challenging. It felt unorganized, overwhelming, and filled with jargon. I eventually started putting things together by the end of the course, but it took me a lot longer and a lot more effort (and stress) than I would have liked.

The tools and website is sometimes hard to connect, and has maintenance/update very often and it made it extra difficult for us new comers to follow up without step by step guide to the new features, which prolonged the course and it wasn't very necessary.

But I did learn a lot from this course hopefully the tools and guides get better for the future students.

If you are going to create a class, please DOUBLE CHECK everything periodically. We have found most of what you are telling us is wrong and are having to learn by trial and error. I feel sorry for those who do not have a background in computers or speak english. They have to be very frustrated by your outdated instructions that do not work. I know I am.

The Skills Network Lab never once worked for me while I was enrolled in this course. While I have Jupyter Notebooks and RStudio available to me via an Anaconda installation, and could therefore follow along to most of the lessons, installing Zeppelin locally proved to be too difficult for me, and thus I have no hands-on experience with Zeppelin thus far.

This course came too early. I was overwhelmed with the number of tools covered as part of this which was not required especially the functionality part of each tool. This was the time I was about to quit as it was getting too much. It is better to focus on one tool and once you grasp the concepts of data science, it is easy to replicate across tools

+ Online environments for most tasks - Quite a few strangely worded questions, including double or triple negatives. - For the online RStudio demo a GGally dependency was missing. - Requires you to create a repository on your private GitHub and share it. - Annoying requirement to take screenshots of your Jupyter notebook for peer grading.

Too much content that was not accurate, (i.e. time to actually re-record the videos vs just having all those notes that say they're the same - the navigation on the IBM site is different now, so it's not just a title - time to rerecord). Also, found that a decent amount of it was a rehash of things in the first class in the certification.

The course says suitable for beginners but by Week 2, it becomes apparent that this is not actually the case. I was able to finish the course, but with great difficulty and a lot of research outside of the modules to understand this. There should have been a bit more of an introduction to the skills that would have been needed further on.