ok

Let's start with the good: The activities. These are great reviews of what we have learned in other IBM courses, with some new stuff thrown in. I learned a lot. So why only 3 stars? The course has several basic problems that caused me to waste a LOT of time. 1) Unintelligible instructions/materials. There are so many grammar spelling errors, things copy/pasted into the wrong place, etc that it can be quite hard to follow. This is common in IBM courses but in this one I really felt it. 2) Technical issues. Labs crashed several times for me. In the Dash lab, it was particularly annoying, as the work cannot be saved in the lab itself, and so I lost all progress every time there was a crash. To make things worse, the staff moved several of my labs to different locations, forcing me to redo several hours of work (hopefully this is just a once-off problem though). 3) Some strange activities. For example, how does finding everything that starts with 'CCA' help us to answer the research question? Yes, it might be good practice in it's own right, but why can't we get practice by working towards the stated goal instead of by doing random time-filler activities?

The assignments were interesting especially when we had to think of our own problems to solve. It would've been really helpful if the course was regularly updated, specifically when it comes to the first assignment where a lot of students experienced challenges with their machines and the course was designed with old operating machines in mind. the discussion forums would help a lot if instructors actually answered the questions and not directed students to links that were of no assistance at all. The course material could really do with an upgrade.

The curriculum and project work was fine. Notebooks to complete were OK, although not flawless. The final presentation format was... bad. A written report in the form of a 50 slide PowerPoint presentation is *not* a good habit to be teaching future data science professionals. Plus the instructions regarding what was expected were either ambiguous, confusing, or absent. The curriculum is great and I learned something. The testing procedure was extremely tedious and poorly thought out and in dire need of a major overhaul.

Very prescriptive and guided. Everything I have come to expect from Coursera. Little room for critical thought or original content. Designed for begineers. I am surprised this is an IBM course beyond building the user base for its tools. The marking Rubik's are too prescribed to provide accurate marks which matters little given the way in which they are applied. The final powerpoint assignment should be replaced with a report and a ten slide deck.

The github guide was very helpful and informative. I wished there would have been more explanations how to interprete the results of evaluated models and about machine models in general, when to use which model for example. Also some details were missing like how to balance imbalanced data, should the data be balanced and then visualized or vice versa? Fitting a model is easily done, but it's the details that make the difference.

I went through many problems to complete the Plotly Dash labs which puts up a small HTTP server on a non-standard PORT. I had to setup an entire environment in my personal computer to work around them. Also, due to the lengthy labs of this course, many of my colleagues reported problems running out of CUH in IBM Watson environemnt. I believe 50% more CUH would suffice for this course.

The course gives the learners a perfect platform to practice the concepts learnt throughout the Data Science specialization. Final assignment is unique and interesting and the course makes sure you practice enough before taking it up. A good experience, but issues with Foursquare now and then makes it a little hectic to get done with the course.

A nice course though. Liked it!

The journey was very informative but at the end of the course and submitting all of my assignments before the deadline , i got my course certificate with no instructor signature . A very disappointing fact as I worked very hard to complete the specialization within my 7 day free trial which is till 8 pm today I.S.T

Never expected such kind of irresponsibility

The capstone content needs to be thoroughly edited for clarity, especially in the instructions on what exactly the instructors are looking for in the final deliverables. Some of the peer-reviewers seem to be confused, and I'll admit I was a little confused myself reading through the instructions the first time.

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.

This course leaves a lot to be desired, the IBM user interface for me is not beginner friendly and the SQL part is to me problematic. the DB2 is not a freeware and some student have to use the altaernatives such as MS Server, which is rather a hassle.

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 !!

It was a great course. I have learn a lot of things. Though, Some module was hard to understand particularly machine learning with python. Besically i was beginner of data science field that's why I feel so hard in machine learning module.

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.

To use the Watson platform is a headache, the account starts to ask for a credit card and I am just paying once.

It would be very good to start using a jupyter notebook from scratch.

The rest is fine.

Spent a lot of time getting the used IBM Cloud system components up and running. Partially redundant content (due to course overlap). The effort-to-benefit ratio of this course is questionable.

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.

The final project is way too over the top for this type of course. I've been asked to do less work in graduate level courses.