Not everything that was needed in the final project was covered well enough (or at all) in the videos and lectures

Very theoretical, Quiz questions were made over complicated. this make loose interest in completing the course

I am happy with what I learned but I think it is not as good as the rest in the series.

Terrible IT support. Labs do not work. Never recommend IBM courses to anyone.

Hi,

I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".

Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)

Course 1: approximately 9 hours to complete

Course 2: approximately 16 hours to complete

Course 3: approximately 9 hours to complete

Course 4: approximately 22 hours to complete

Course 5: approximately 14 hours to complete

Course 6: approximately 16 hours to complete

Course 7: approximately 16 hours to complete

Course 8: approximately 20 hours to complete

Course 9: approximately 47 hours to complete

This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.

(*): https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_content=10-IBM-Data-Science-US&adgroupid=70740725700&device=c&keyword=ibm%20data%20science%20professional%20certificate%20coursera&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=347453133242&hide_mobile_promo&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpWPrZDik6-Ne30To7vg20jGReHOKi4AbvstRfSbFxqA-6ZMrPn1gDAaAiMGEALw_wcB

I felt that the curriculum was not structured in a manner conducive to learn the material. Too much of the training and lab work was to execute already prepared commands without an explanation as to why we were doing using these commands. In addition, the training material could have used more detailed explanations and then lab work allowing the student to apply this knowledge. Instead, you watch a lot of abbreviated videos and then do a single lab exercise that has the student try out certain aspects of what was covered.

For the final exercise, there was so much that wasn't covered in the course material. This took many extra hours searching for how to do things. While this type of searching might have been helpful in preparing for use of Python/Data Science outside of the course, none of the course material to date trained us on how to interpret the reference material. The final lab should be challenging, but not to the extent where the material presented doesn't provide the method for solving these problems. The curriculum designer should take this into account when building these classes.

Lastly, the tooling used for the course did not work for over a month. This added hours to my training. It also meant that I was never able to complete some of the lab exercises, or use the completed material as a reference for the final exam work. The Coursera help desk was not at all helpful in informing students of the issue and when it would be resolved, and only gave advice to try to recreate the same exercises (without the supporting code) in other environments. This added many hours to the time that I needed to complete the exercise.

While the data visualization tools outlined here are valuable, the final assignment for this course does a very poor job of assessing the things that were actually taught.

Early on, you are assured that the course will emphasize the scripting layer of matplotlib, rather than the more complex artist layer. In the final assignment, however, you are instructed to use the artist layer, and configure many parameters that were never covered in any of the labs or videos.

Likewise, utilizing geojson files for choropleth maps was covered in the most cursory manner - you are never requried to open a geojson file, or understand how it is configured. You just load it in and carry on with the assignment. However, without understanding the setup of a geojson file, no student is going to understand how to properly configure the key_on parameter when making their own choropleth map for the final assignment.

The ability to actually create a graph from a set of data is perhaps the smallest part of the final assessment. Everything else is fussing with irritating details, often details that we were never taught about in class.

This was not a course. This was a "go get them tiger": the labs are there, go do them and come back for the assignment. And then, in the assignment there were features that we had to include in a chart that were not even hinted - let alone explained - anywhere in the course. If we the idea is that we must search for everything on the web, then the course should at least include references to websites where we can find relevant information. Back in my student days we called that "suggested reading". Some of the Multiple Choice questions were really annoying: do we really have to remember the first name of the creator of Matlab to become data scientists? Great Material, but a very frustrating overall experience since there was no teaching.

This is by far the least helpful course in the IBM Data Science Professional Certificate series. The videos contain mostly repeated info, so you really only learn much of anything from the labs. But even the labs are very basic compared to what you are expected to do for the final project. If I am paying for a course to teach me something, I shouldn't be teaching myself with help from Google. I can do that on my own, for free. If the "help" offered by the teaching assistant in the forum is code that doesn't look even vaguely familiar right after going through the course, doing all the labs, and getting a 100% on every quiz, then there is a big problem. I would absolutely not recommend this course

The video lessons just tell you that do some things are possible, but just in theory they would explain how to do it on labs, but the labs aren't so clear. There are days that I try to download the files for final assignment and the link doesn't work and the mentores don't answer. I didn't want to give one star to the course, because all of the other courses from IBM Data Science certification are so good, but unfortunately this course definitively doesn't scores higher than that, because I had to study on matplotlib and other libraries documentations in order to do the exercises.

by far the worst course of the whole certification program. Carelessly prepared content. Full of typo and mistakes. Quiz results are not even consistent. Different answers for the same question is considered wrong. If a question has two possible answers as multiple-choice, the answer should be one of those, right? Many of the videos are repeating each other. Very little information. Waste of time and money. If there was another way to get this certificate without taking this visualization course, I would pick that way.

The course was not well organized. The instructor focused on providing very advanced content rather than simplifying the conpects in order to make it easy for the student to digest, and follow. In many times i had to search online to understand the content. Even in the final assignemt, it was asked to use many functions that was not itroduced before, and the attached files that were needed to answer the questions came with errors, and i had to search in stockoverflow to solve the attachments problems.

In my opinion, it's a terrible course. The labs seem to belong to an advanced course, whereas the videos are elementary and for absolute beginners. The labs take several hours and and even days to complete and understand, whereas it's claimed only an hour is required. None of the links/path at the final assignment worked! zero to none customer support, which is an absolute shame. The final assignments are way beyond the scope of a beginner course. Waste of money!!!

Arguably the worst course in IBM certification. There were problems everywhere. The code boxes weren't loading in quizzes. The overall peer guided assignment was a nightmare since they were demanding the part which was not even taught. To sum it all up, peers checked my assignment incorrectly. The assignment grade calumniation took so long than usual. Keep in mind I've done previous courses in this IBM professional certification.

Worse course ever!

Don't waste your time - this course is just repetition of the same video "data cleaning" which is half of the whole course.

BTW they use outdated (unsupported) version of Python - Python 2. Not a big deal, but shows that the course itself is outdated. Other libraries used in the course are outdated as well - if you use latest versions you'll find some warnings or error because library has been moved forward.

Короткие лекции по 1-2 минуте вызывают удивление - неужто в IBM настолько разленились, что им языком лень ворочать?

В видео показывают и говорят одно, а в контрольных заданиях совсем другое, такое впечатлении, что готовит лекции один человек, а задания к ней совершенно другой и при этом они между собой не общаются.

Куча потерянного времени, раздражения и неудовлетворения, практических знаний - около 5% всего, в места 100%.

The videos are chopped together and the end-of-section quizzes are full of "gotcha" true/false questions and incomplete questions that will cause you to fail and wait the 8 hours until your next try.

The content is lackluster, the videos are cut together with differing audio quality, and the presenter couldn't sound more bored.

Not a good course. I just want to get through it to finish the specialization.

The course was shallow in content. I wish it explored pros/cons of advanced visualization techniques & how to go about implementing them in python with several real-world examples. The videos were extremely short & repetitive explaining the same dataset in each video. Bulk of the learning happens in optional labs & peer reviewed final assignment. Most of the insights are easily available online.

This is worst course in the specialization. None of the videos give any defined explanation about the parameters or keywords that are discussed in the labs. In the labs too there are no clear explanations as to why certain parameters are used. This is the worst course. I would recommend replacing the videos with videos that actually contain clear explanations. This is not for beginners.

This course should really just be the three lab sessions. The videos could be more helpful if they reinforced the labs, instead they gave very rudimentary descriptions of the charts. Aside from the geotagging lesson, the detail of the videos and even some of the lab content doesn't adequately prepare you for the course assignment.

By far the worst module of the IBM Certificate. The videos do not explain anything just repeat the same things over and over again and the things needed for the final assignment are not in the videos or the labs. It will take you forever to do the assignment in the end simply because you need to do lots of research on your own

The instructor skipped many things on the lectures expecting that the students will learn from the lab. The lab experience was good until I used the last lab on the last module. I couldn't run some functions. In the final graded assignment, the lack of proper tutorial on how to use JSON file, I felt like a failure.

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I think, you really should change this course in a way that one is not dependent on labs.cognitiveclass.ai

It simply does not work. I have manually to upload everything to my light version of the Watson Studio.

The overall level of the cause is way too low compared to the request made in the tests. Furthermore mistakes and inaccuracies are present all'over the course material. Please review the course material and integrate information needed to perform the tests

Seems like a Pandas course instead of a Data Visualization Course. The videos are very redundant and don't really give explanation on many items. The assignment is extremely hard in relation of the quality of the materials covered in the course.