This was the most complicated to understand out of all of them, at least the final project was.

The final assignment was not straightforward. It doesn't check the visualization capabilities.

Needs better and more elaborate explanation. It's too tough to understand and execute.Thanks!

Some of the questions on the final assignment questions were not covered on this course.

There was no course material teaching us how to do one of the tasks for final assignment

A lot of material is not explained verbally, videos are half-useless and repeating.

Final assignment confusing. Some code questions of the tests were poorly formatted

The tutorial videos needed to have more content and explanation and not the labs.

Please have more explanation in Videos. The content is not covered enough in labs

Solid lectures, but final project and labs had errors. Fix these problems soon.

Code was not taught nearly as well as the other modules in the certificate.

Not Fully explained. The final agriment tasks not match with course content

No Instructors helping out. Little is learned... Not worth taking.

The lab stopped working and we didn't get any support.

Questions in the peer graded are little out of scope.

need to adjust material very bad labs and tutorials

Poor examples / labs! Labs very often not working.

lack of adequate instruction for some assignments

Poor study material compared to the assignment

The Skillshare network is not working. :>

opening a tool takes too long

i didnt get my badge

Need to be clearer

not very clear

This is definitely the worst IBM course I have taken. Truly awful. The good: It introduces you to multiple visualization packages, albeit briefly. The instructor responses to most of my questions were detailed and helpful, though many responses I saw to other questions were unhelpful or even inaccurate. The bad: Where to begin? The course suffers from very poorly written/designed instructional materials. For example, students are often tasked with creating visualizations that don’t make much sense or are not optimal for the situation. The final project material is particularly awful. The dataset students are given is a synthesized dataset that is very poorly designed. Even the instructors are not sure exactly what the rows and some of the variables represent. Of course, creating a visualization using a dataset with a nonsensical structure is likely to produce a nonsensical result, but sometimes even the visualization prompts themselves are nonsense. Why were we asked to create a bar chart with two continuous variables and one categorical variable? Why were we asked to create a line chart for data that has multiple observations for specific x-axis values? Students complained about this, and the staff said they would fix it months ago but have not, which is another issue. You might often find yourself thinking “what abomination of a graph did I just create? Is this right?” then checking the solution code and seeing that you are correct, it is just a nonsense plot. I would be embarrassed to show somebody the work I created in this course, even though I did it correctly. Many of the quiz/exam questions and/or answers are either vague, nonsensical, or not very educational. As an example, a question on the final exam (which I will not write here) asked a question akin to asking “What feature of a car is helpful for buying a car?” What kind of a question is that? Students complained and the staff said they would remove it months ago but have not. Another question was like asking “What kind of animal is a dog?” and giving the answer choices: A) A furry animal B) An animal that hisses C) A lizard D) A dead animal What is that supposed to teach us? What do you mean by “kind”? The course materials are also full of typos. Did nobody proofread the course content and think critically about it? Some responses I saw from instructors also contained many serious typos. Also, as previously mentioned twice, errors and egregiously badly written course material are slow to get fixed (if at all?). I wasted so much time wondering if I was doing something right, if something was a typo, or what a vague prompt or question meant. The course materials also use deprecated functions, sending me on a hunt to find and learn the current functions. None of this is helped by the script-reading robot voice that often lacks subtle but important intonation and sentence pacing. Another, more foundational issue with the course is that it doesn’t really teach you that much about each visualization package. This is especially true for the dashboarding section. There is no way I would feel confident building a real dashboard for an organization with just the knowledge learned in this course. The lack of depth is also exacerbated by the fact that the visualizations being created are not well suited to the problem at hand or are based on nonsense data. If this course is meant to teach us useful skills, shouldn’t we be creating realistic visualizations that are representative of how a data analyst would visualize real-world problems? I could say more, but the bottom line is that I do not recommend this course for learning data visualization with Python. I seriously hope IBM overhauls this course.