This is a very useful capstone project in which you can apply all the learning you have done throughout the course, the more practice you do the more you learn. I like this course from coursera and recommend it for data science aspirants.

Thank You!

It's a great course to get a comprehensive background on Data Science (including ML) and lays the foundation for more advanced courses. It touches on all the areas that are required for data science.

The IBM Data Science Professional Certificate is a very good course. lam glad to have covered the course with the help of Coursera. I will put to use all concepts learnt in this Data Science series.

This Program was well structured, it was a great combination of learning and problem solving. You also got a great chance to see how useful data can be and how easy it is to make it work for you

A must take capstone project. Enroll for it and you will be moved by the project... Very interesting !

Good, but the last peer assignment, the report slides, that's so weary to do. It took me a week to do that boring task, I think they could make it more interesting with another way.

A good level of challenge, didn't need the 50 slide PP.

My review after around 11 or 12 months of studying all ten courses is: the IBM Data Science Professional Certificate contains general information and process on data science, but does not go into great detail. After joining the course, I was able to further think and ask at work how data collection would affect our product and indicate how the envisioned data may provide misleading information. However, the courses' duration is much longer than indicated on Coursera and apart from the time spent on completing the course contents, I have spent a lot of time trying to get Watson Studio or the hands-on lab operational, and the hands-on lab could be down for a week or more. From my perspective, this is counterintuitive and inefficient, and I did not expect this from IBM's products. Looking at some of the reviews for this course, I think it is fair to warn others who are looking to join that the courses are generic and some - if not most of the - time requires the learner to Google answers for any confusion and code tutorial or read books; this does not bother me as it has been my approach for a long time. As I am writing this review I am awaiting my classmate to review my peer assignment for the second time because I got less than the required pass grade, which perhaps my classmates may have experienced once or twice throughout these ten courses due to incorrectly marked assignments. Although I admit I did not perfectly complete the capstone project's slides, based on the guide I would have received a higher score than what I had; for example, I got zero points instead of two points for having my GitHub link and PDF file attached. However, I understand the importance of reading your peer's assignments because some of the assignments I read inspired me, but the peer-review system is flawed because the course expects a constant number of students studying at the same period and the minimum number of assignments required the students to review would cover the whole cohort for that period; evidently, sometimes this system does not operate as expected because there are usually threads asking for help to review the assignment on the week's discussion forum. Consequently, from my perspective, this course would be more efficient if an automated correction system was also available, similar to "Machine Learning by Andrew Ng".

Very challenging course, much more challenging than the previous IBM Data Science courses. Although all of the topics that become relevant in the Capstone project have been addressed in previous courses it almost feels as if you have learned nothing before. So you HAVE to go back to the old courses. More often than not you realize that before you had only a superficial understanding of the concepts and the details. On the other hand, it also shows that some of the previous courses just were not good enough to have a lasting impact. This is especially true for the "Data Visualisation" course (and here in particular the Dashboard topic).

So while in the end it was a good learning experience to go through the pain of going back and forth between the project and old courses (or other sources), I would have wished that there is a more seamless flow within the whole IBM Data Science course.

Creating a 50 page final Report is quite a challenge but it certainly helped to tie everything together. In the end, it was worth it and I am actually somewhat proud that I worked my way through it.

With all the critical points I mentioned I don't want to miss the opportunity to thank all instructors for setting up this course. I can imagine that this itself is a Herculean task, with all the technical hurdles that needed to be overcome. While there were a few hiccups that were only addressed in the discussion forum, from a technical perspective, I think this course actually worked quite well.

So thanks again - keep up the good work.

The topic is so far away from what we normally face in the business world that I found it irrelevant. Also, the whole course material (entire Data Science Professional Cert program) needs to be ''audited" for correctness, for example some quiz answers are wrong (therefore when you click the right answer, you get marked wrong), then there are instances of lack of guidance or misguidance in certain lab assignments, leading to hours of wasted time until you figure it out. Anyway it facilitates learning, albeit in a time-intensive way. Lastly, in case you need to quickly contact some instructor to point out anything, it's totally hopeless. Just give up. They make sure you cannot get in touch with a human being live. On the other hand, the course is organized well in terms of topic by topic development; a lot of effort has gone into creating the videos etc. I learned a lot and am happy with what I learned.

I can say overall it's a good program. However by reviewing the first few courses, you will get a headache, but the rest courses are very useful. Some parts are really useless for a data scientist and are more useful for programmers, which I recommend you do not put a lot of time on them and skip them as much as you can.

Apart from the material, I think this certificate is really useful for you to get a job. But, if you just want to learn new concepts in data science and do not need a certificate, I recommend you to take other courses other than IBM. There are very good courses on @linkedin Learning.

In this program, IBM pushes you to work only on its platforms which is really annoying and I think this a considerable drawback of this program.

If you spend at least 4-5 hours a day, you'll be able to complete it in 2 months. The subscription is monthly and it's around $50 CAD and you can unsubscribe whenever you want.

A stunningly miserable end to a relatively solid program. There are just so many questions I have. Why 40+ slides? Why link each previous project individually, and then collectively? Why have a link in a slideshow? Who on earth thought 40+ slides was at all realistic? That's roughly 4x longer than what would be considered a max number of slides in any professional context!

The amount of redundancy, busywork, and general disrespect toward the individual's time is absolutely attrocious. The several different "activities" that tell you how to make a POWERPOINT are downright insulting.

The actual data gathering, analysis, and prediction training are really cool! The way in which they're all brought together in the end is simply and infuriating waste of time.

The course is actually very very hard, I made it through all the Data Science courses for Proffesional Certificate, however, when I came to this final course, I kind of got lost when working on assignments that would lead me to create a project of the desired outcome. As it's been some time since I took other Data Science courses and tried to complete this one, I came back now, after around a year, to see if anything got fixed as I believe other participants of the course had problems creating their projects as well, yet however, I see that nothing has changed. Tried creating the project again, yet got stuck at the assignment for week 3. Maybe Coursera or IBM Teaching staff should really look into this issue that not only I am experiencing.

This course appears to be all but abandoned by IBM. Many components of the Applied Data Science Capstone are outdated, Pythons scripts won't load, with errors plaguing almost every assignment. The only assistance you'll find is two to three year old forum posts, unanswered, from students who had to overcome the same errors with strange workarounds. Not to mention, the instructions are abysmal. It's almost as if the creators of this course have never actually had a homework assignment, and simply don't know how to compose a homework assignment, or they didn't take the time to actually do it themselves. Again, lackluster data science course from IBM, that they themselves don't care about.

While I rate highly the first 4 classes of the course, the 5th which is the final project is a joke.

There, you have to gather the info and make the predicition. Yet, you have a sample of, warning, 90 records and using ML models for that is a WASTE!

Also, the 5th does not treat crucial parts of DS jobs like feature engineering, picking right models or smply fitting the data correctly. In some cases it is not even there.

I do am sorry to grade it as 1/5 but the gem course class should be done better, way better.

Worst learning exeperience on Couresera!

Very steep learning curve for beginners. A lot of coding skills were not taught in previous course and I had to do a lot of googling.

It's not that I hating doing my own research, but for a professional training course, I don't expect so many DIYs! There's a difference between being lazy and lack-of- design course and a well-constructed, thinking-encouraging courses.

NOT RECOMMENDED!

Utterly frustrating. Materials / deliverables change regularly so you I've ended up needing to restart twice. Course is poorly curated, basically just leaving you to debug code rather than really teaching you about data science.

Moderators ignore you (or simply don't exist?)

I regret being on this course for such a long time and wasting so much money. There are much better courses out there. This doesn't deserve the IBM brand.

There are a lot of things wrong with this course: The labs need to be updated, we are asking to do something that didn't work in the labs. We are also ask to submit links, and the submission box does not allow clickable links. The Quizzes that doesn't show the question, the all or nothing peer reviewers, all of this is in the discussion forums, but there is not enough support staff.

One star for the fact that the Lab notebooks were flooded with errors, you would need more time fixing the errors rather than going through them,

Also, in peer graded assignments, some of the links submitted aren't processed as hyperlinks and cannot be copy pasted either, so there's no way to view them.

Very bad experience on this one.

This obscene deadlines are impossible to say the least. If you wanted us to pay you the two months immediately you could have just stated it on the terms... I would rather pay all the three months worth of tuition immediately than wait almost to months to finish this course.

This was the most frustrating course I have taken on Coursera. The foursqure api is not up to date and I had to waste hours of my life fixing the bugs.

Unnecessairily complicated. Here to learn Python..not how to connect files from here and there

It is a teribbly structured course. Avoid.

peer reviewing is worst

Worst and Very hard