The final capstone felt like a mis-match with the previous 3 courses of the specialization. The capstone was also the final project for other specialization which would explain the mis-match.

Even though I learned a lot, it wasn't entirely clear what was actually required from me.

This course is ok. Not too challenging and not too easy. It definitely needs an update. Things have changed over the last couple of years and it appears that the course developers have not made an update since 2018. WIth a refresh this course will be a 5 star course for sure.

Labs could be improved verifying all the commands work well. Videos could be improved make them more informative as in other Data Science courses part of the Specialization. Many things are left to the labs without sufficient previous explanation.

The challenges presented have been really good however I'd reccomend that the prceding modules be evaluated for the changes that have come in over the years,maybe lay more emphasis on 'what is used more frequently' in a real life situation !!

This course was extremely difficult and it took me the longest. There were errors in the lab so I could not finish any of the labs, but I had asked for help and the response for help was very poor for the lab or for the assignment.

It is good because you get to know many tools to get data and it has very good examples of how a project should look, but i think this is a project that must not be reviewed by other students, so we get useful feedback.

Very challenging. A lot of the things you have to do in the final project are things you must figure out on your own, since they're not explained in any previous lessons.

A challenging Capstone project with many dimensions. The structure of the previous courses in the certification could have been improved to build up to this project.

This course is about applying what you learn on a free form project.. but you should use Foursquare API which it might be challenging little bit to deal with..

There are some errors in the instructions labs, in forums is the way you can get help, but it it necessary to modify the code in the examples.

Great capstone project. But forced to do the same project. It would be better to get more choices of projects.

I didn't like that we had to use Foursquare — I could not come up with anything interesting.

The difficulty could be increased and the scope of topics covered could be wider.

The instructor of the capstone saved this specialization for me.

I did not find the project relevant to the rest of the course

Broken links in samples and csv data files.

some lab codes cannot run smoothly

very vague with the information

It is good for beginners.

Hardness Level High

really difficult

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.

I enjoyed working on an open ended project, which was not the case in the remaining 8 courses in this specialisation. I was completely unprepared for some common challenges with a real life dataset and it took me a hard time to address them. On the other hand, it is hideous that only one person reviews your assignment and there are absolutely no requirements regarding the accuracy of the results. I mean who would accept a statistical model with the lowest possible accuracy in your new dream job? Anyhow, the only reason why I kept improving my project is just to show it to my potential future employer and not because of the requirements. The other funny thing is the cavalcade of "Please review my assignment" threads in the discussion forums, which makes it impossible to have a meaningful discussion there. In conclusion, I did other courses on Coursera, but this one had a far lower quality than those.

On one hand there is some encouragement to experiment and come up with an interesting problem and I actually took some time to come up with something non-trivial before starting. But practically, there is no need to -- you can just take the example notebook from one of the prior weeks and change the city. The evaluation doesn't really reward you for doing something original or extra.

Sadly, the certificate of the specialization as a whole is worthless.

I hoped this course would be more complex but it mostly consist of Foursquare API requests. I had to focus how to fit other datasets in addition to Foursquare data to find something interesting but instead of using fancy algorithms and testing them I had to focus on data and it was really time consuming, I spent 2x more time on each assignment. Whole IBM DS path was great but final course was a big disappointment.