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.

I ended up having to reset the course deadlines multiple times due to the final project. My final project was submitted end of february, and yet still beginning of April have still not received final grades for it, thus need to keep resetting deadlines. A little frustrating to keep paying a new fee for a course that has been completed.

Although the intent was clear, and IBM Watson Studio is helpful, this course needs to be rewritten. The week 3 content is a repeat of what was completed in the first course of this certification. Additionally, the content of needs to be updated to reflect the new format and functions of IBM Watson Studio over Data Science Experience.

Rather shallow course that tests you on trivial knowledge mentioned at some point in the videos/readings. More hands-on exercises/assignments will be more useful, instead of just testing on things that can be easily googled. Course does give a nice overview of data science tools, you one does not learn much more than an overview.

This one comes to soon in the path to get IBM professional certificate.

To many tools to get a handle off when you just start out. A bit overwhelming

As a stand alone course when you need these tools it is probably ok.

I would have prefered to just stay with skillabs and move on.

and then later maybe come back when absolutely needed.

A lot of errors, typos, and mismatched interfaces make this course frustrating. The order the material is presented in several lessons is wrong. The general purpose of the work is clear, and I took copious notes on a lot of it, but so many details are missing, hidden, or presented in the wrong order. This course needs updating!

The content of week 2 (module 2) was shockingly bad. Complete disregard for the level that this course is aimed at and extremely bad quality. Week 1 overall was decent compared to week 2, but was a complete data dump and quite a challenge to keep up. Week 3 and the assessment in week 4 were a pleasure and a delight to learn

the first week is really impossible to follow, too many inofrmations and given too quickly and there's no meaning in listing all those programs. Second week is the best one in my view, and very well organized. About the last 2 weeks: a course on tools cannot be focused 50% on IBM tools, which, by the way, nobody uses.

I was very disapointed in the 4th week's content. I understand that it is a course sponsored by IBM, hence, I was expecting way better content on their softwares and tools. On top of that, the interface shown in the videos is different from the current one which made it even harder to follow. IBM you can do better.

Incluyen conceptos dentro de conceptos que no están plenamente aclarados en el principio, lo cual retrasa mi estudio porque debo buscar en otras fuentes de información para poder entender los términos utilizados dentro de su contexto, ya que en primera instancia no poseo una formación académica relacionada al curso.

Dull presentation and the second half felt like I was paying for an advertisement of IBM's data science tools more than anything else. If I'm having to pay for each specialisation from IBM, it would be good to get some information on IBM's competitors to balance it out. Not just IBM's resources and the free ones.

IBM Watson section is totally out of date and no where is it mentioned that the information in the videos is not accurate and the steps are all wrong. very disappointined in the quality of this course will be canceling subscription if this is the type of instruction the other courses have. Totally unacceptable

This course just promotes the tools from IBM and it also needs you to make accounts into its products and although it says, the products are free trial, they want your credit card details. Most questions in the assignments are also all about their products. I am very annoyed and disappointed by this course.

The content is rich, but hard to follow along is you have some form of learning disability. I struggle with concentration, so only having to read works on a slide made it hard for me to follow along with the course content. I would advise you, preview and ensure that this content fits your learning needs.

The course is too dry and not contextualised, the only thing I was happy to have learnt is how to use Gibhut, that's quite hands on, however other parts are full of jargons that I am not even sure if they are relevant to me at all, and I can't remember most of them or understand how to apply them at all.

Material given in the course was not well stuctured. It took me 10 minutes to conspect some thesises in 7 minustes video, just because information provided in the following slides was chaotic. Finished this course in a few hours. But very well integrated ads of IBMs software, bonus star for it

While generally content was useful, video tutorials were created using outdated tools and with not much explanation or introduction to concepts. Some video tutorials were also used with a Mac, which leads to syntax variations. Week 3 felt like I was sitting through an IBM Watson advertisement.

Many of the videos are out of sync with the current IBM Cloud interface. Also some lessons start at a point but give no indication how to get to that same starting point.

I felt not much was gained from week 3. I learned more from IBM help docs and YouTube than from week three's materials.

Regarding Mod7: it doesn't match the current Watson, it doesn't address the myriad of details that one has to have lined up to make it go, and the at the end I got to make a fun little board - but there was no option to share it. Overall not a great time. Other Moduals were very educational.

I understand the purpose of this course, to showcase all the different tools a data scientist needs, but since this course is offered for beginner level, the vast majority of the concepts introduced in the lections serve no purpose in educating since we don't have the expertise to grasp it.

Confusing, curriculum not designed for beginners that don't have coding experience. You can get through it, get a certificate, and learn some stuff, but be prepared to Google a lot and watch other tutorial videos in order to pass the course quizzes, because the video lectures are terrible.

Well, that course is not that useless as the previous one in the specilization because now at least I got to know some tools. But still, most of the course is a waste of time, as all those tools could be described and linked as a part of some module in a more difficult and hands-on course.