This course had several issues. First it was too much information for someone who has no background knowledge and therefore difficult to understand all the terms used without any examples to relate. Second, there were several audio related issues that were not resolved. I wasnt able to access IBM Watson Studio and even though I reported the issue I ended up losing marks on an assignment that required IBM Watson Studio which was no fault of mine. There were unclear instructions, graded assignments included content not taught the lab work (it wasn't mandatory to study the cheat sheet). Overall, disappointed.

There are some very helpful parts of this course, such as those on using GitHub that helped me tremendously and were very easy to understand. That being said, there is so much of an emphasis on pushing IBM's products that it seriously hamstrings the course. Conditioning a point of your final grade on submitting through IBM Watson is a very silly thing when data science is such an open field with a multiplicity of tools. I understand this is an IBM course, but it's a cheap and slimy thing to make so much of the course basically an advertisement for IBM products. Our time is scarce; please respect it.

The first course in the IBM Data Science Professional track was excellent. This one is not.

This particular course is dry compared to the previous one. It’s difficult to pay attention when many of the videos are a boring presentation of dozens of data science tools. Week two is less dry but is poorly organized and needs more explanation and refinement (poor audio quality, lacking descriptions). There are also videos which are essentially repeats (cover the same information) of the previous course but of worse quality. Overall, this course lacks refinement and organization, and is not worth paying for.

The content is a good intro into the tools that you are gonna use in a data career. However, I did have two major issues here where:

1) As IBM moved to Watson Studio from Data Science Experience, this did create some of the visuals and knowledge a bit outdated.

2) There was a massive disconnect when you have issues working Watson; especially with signing up and logging in. I see that this was a huge issue since then (judging by reading the discussion sections of the course) and this (along with my first point0 should definitely be discussed if you want this content to still provided.

It is a very quickly course, the week of the open source tools it's seen really quick, you can barely understand anything and they put three different tools in one week, if you really want to learn them search another course; it is also a big propaganda for de IBM tools, and they put so much more effort on selling you the idea that their products are really necessary that in actually introduce you to the tools that a data scientist use, and its so hard to understand if you don't speak english as your mother language, hope that with time they can fix it.

This course is not good. It has taken me several times the amount of time specified due to the outdated videos that no longer represent the tool as provided. Struggling to get simple markdown commands to work in the notebook, but I successfully executed them in the previous toolset. Several back and forth's between the actual work and the videos is very aggravating. It would be nice if you at least provided some printable instructions. I feel that I have gotten off track and may not be able to find my way back to a normalized starting point.

Very patchy. Some of the videos were quite informative but the practical exercises were a real problem. Often the instructions were impossible to follow as the software must be a newer version than that shown in the instructions. I had to Google for the latest instructions. Also the practical exercises rarely told you *why* you were learning anything; it said "type in this code" but you didn't understand the code. I was able to finish the course but only through sheer perseverance (and Googling for instructions) - it was not enjoyable.

This course at one time would have been great. However, for myself and many others (based on numerous discussion posts during my time taking the course), there was a multitude of technical errors and outdated training. Zeppelin Notebooks was not a working functionality in the IBM Skills Network, and most of the walkthrough guides were unhelpful due to updates in the tools being showcased. The course is in need of some serious updating to catch up on many changes that have impacted the tools covered in this course.

Material in this course looked like part of something else. It's a beginner's course but suddently I'm faced with a lot of technical jargon with no explanation. I supposed to experiment with software and code I've never seen or know how to interpret and I'm just suppose to run it to see what happens. I have no idea what I was supposed to learn from it. Week 2 was demotivating and added nothing to my knowledge. This week was an absolute loss of time. I still learned something from week 1 and 3

give one plus star with benefits of the doubt. If the course gets better in next courses but this is a shame. I can deal you promote IBM services and products, no matter with that, but you only give ALL the tools existing in the data science world and meanings, but with no knowledge is a none sense. Hope you improve, Basic stuff for analytics, statical or regression models, clustering I have no clue what they are. But well the name is tools for data science. No how to use them or what for.

The course needs to be updated. Especially the IBM Watson Studio section is something which needs to be worked on again. The site they refer to has hanged completely. IBM site was not user friendly and caused a lot of confusion. It took a lot of time to figure it out. This problem is not isolated and there have been a lot of users who are struggling to figure out how to solve it. This causes additional problems as the final assignment depends on getting started with the IBM website.

A lot of contents are not accurate since IBM website has been changed . And the final exam was terrible. For example, one answer was like Both A and B and there were no indication for A and B. Another question:What type of model would you use if you wanted to find the relationship between dependent and independent variables? If you choose regression model, it's wrong. If you choose Classification model, wrong again. Do I suppose to choose the wrong answer to get 100% grade?

A very fast-paced course with a lot of non-sense material for beginners. There is redundancy in final exam instructions; it is difficult to know which one to follow. Some videos have poor audio quality. There are too many links here and there that don't make sense. Many of the instructions for lab work are based on the older version of IBM studio, making it difficult to locate the buttons or tabs referenced in the videos and texts. IBM! You've already let me down!

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.