This course felt less well organized and structured as compared to the other courses in the IBM Data Science track. The videos were sparse on detail, and while the labs did have a lot of good information, they were missing crucial material that was necessary for the final assignment. The final assignment also didn't include a Jupyter notebook template / starter code, which combined with the missing information from the labs made the assignment much more frustrating than those for the other courses in this series.

Almost good. But not much explanation given, quick brief on basic functionality. Most of the videos are 3-4 minutes long, where 30 seconds is logo + ending and additionally one minute in almost every video - explanation of the data. In almost every video. So, total explanation of particular functionality is close to 1:30 to 2 minutes. Plus, lecturer is soooooo bored with what he is explaining, that you want to go to sleep in 5 minutes. Final assignment was quite good. That is why it's 3 stars instead of 2.

The course staff was terrible. They don't answer me what I am asking about. They have a lot of good materials, but lack of insructions and explanations. Also, I think they need to update Dash instruction such as creating a new files. I saw many people asking same questions and lab staff had to spend their time to answer these questions that they shouldn't have to. Thus they lack their time to spend more for advanced questions and their answer, for many times, didn't make any sense.

I was glad to learn the tools and techniques taught in this class, but the typos and grammatical errors throughout the curriculum caused confusion and distracted from the learning process. Some of the videos are helpful, but others present concepts without context and seem to be aimed at an audience that has already mastered the material. Overall, I think the coursework was appropriately challenging and the final project gives you good hands-on experience to build on in the future.

The labs were very informative, but the videos didn't add much of anything to my knowledge. The final assignment was incredibly difficult, and the course was all but useless for completing it. Almost everything for the final assignment had to be looked up elsewhere. When a final assignment tests over material never covered in the course, what purpose does it serve? There are many other reviews that have the same complaint. Something needs to be done to rectify this problem.

That`s a good course. I realised the Instructor efforts and his great skill and capabillity wich Python visualization. The final assignment pointed to activities that couldn't be deployed in another (or resident) Jupyter notebook, just only in an IBM cloud notebook.I expensed too much time trying to discover it. Some instructions should be better explained during the course. This is an important subject to be dealing in just tree weeks. Thank you.

The part of using the artist layer is a little ambiguous. Now after I finished the course I don't feel that I know clearly the difference between using the artist layer or using the scripting layer. In both cases we use plot function of a dataframe.

I think dedicating a week or more to discuss the actual functions and the way of using the matplotlib library may be better than previewing more visualization options like waffle chart and word cloud.

The course material itself is interesting, and the design, e.g. course video, quiz, hands on labs has the potential to be a good framework for learning. The execution is incredibly poor, with labs that are frequently vague about requirements, poorly written and constructed, and on more than one occasion have the answer to a question already in place. I know this is relatively introductory level but the lack of proofing is pretty problematic.

Good course overall, but I found the learning pace quite odd. The first part, on more basic visualization techniques, feels very slow, but when it comes to more advanced stuff and dashboards it feels rushed. I feel like this course could have spent more time explaining dashboards, I'm not sure I would feel very confident to implement a dashboard myself. The exams were very copy/paste so you don't get to do a lot by yourself.

The scope of this course is very praise worthy. But knowledge delivery, keeping in mind that even beginners(with no to low coding knwledge) are taking, seems very short sighted, ill formulated & pre formulated coding in the notebook files are having a lot of errors! The same applies for some other courses also. Its a request please share sufficient knowledge through video modules, they describe the content the best.

Sorry to say but this course is actually worse than the others in have learned before.

I understand it may be hard to teach only the different tools for visualization such as folium, bar/pie chart. However, the speaker in this course speaks the same "WORDS", just like replacing the variable names when coding under instructions.

I did learn something in this course but just don't like the way we been given.

This course had several areas where it could be improved: (1) The Final Project was made much more difficult by requiring the students to use skills which were not taught in the course. This seems to defeat the purpose of testing, which is to test what was learned. (2) The course should have contained content which explains when it is more appropriate to use the specific types of visualizations.

Overall a good course, especially the final assignment is well done. However, there is too much focus on the class labs and practically no effort put into the videos. Within the class labs there are only comments as reference to how and why something is done which often lacks proper explanation (e.g. what the called methods in a chart mean, how loops are used to fit data etc.)

I have nothing to criticise except that all these tools could also be taught without being dependent on the IBM platform. It's not a bad platform, it's just that you heavily rely on the internet to complete assignments. That's a bit frustrating if you want to complete an assignment while you're on the road or just have a bad connection in general. Except for that: flawless!

I felt this class was not bad.... I do think that the quizzes are a bit too easy with the assignment being a serious step up. The assignment also required you to Google some how-to's, use some patches and reference prior courses which I feel asked a lot of learners. The info is good, the skill learned is pretty cool. Not the best class, with definite room for improvement.

The material we learned will be useful. But, the Week 5 assignment had to much busy work concerning making screenshots. I got some tips on the forum though that allowed me to make the submissions while minimizing the number of screenshots I took. Hint: create the app with mode equal to 'external' instead of 'inline' and print save the resulting browser tab as a PDF.

I Enjoyed this course, but I feel that it went in too many directions. It spent a little time 4 or 5 different visualization tools. I think it would be much more effective if it just went more in depth with 1 or 2 tools. Because of how many tools this course taught, I had to use a lot of outside material, and I do not feel as if I learned as much as I should have.

The material was okay, but the presentation and teaching methods were flat. We are looking for a progression here, not just a list of things to do with visualization. No narrative = bad recall. Also, the online programming environment is buggy - I got it working eventually. Plenty of trial and error that could have been avoided with 5 minutes of documentation.

Much more difficult than the previous courses in the data science certificate curriculum. Especially the final peer-graded assignment. There are a million things that could go wrong to prevent the code from successfully running, and if you so much as miss a comma you have to wait for the instructors to respond to your questions and tell you what to do.

Great tools introduced in the course but in the final assignment, dash is graded. Its a useless tool for enterprise applications. I dont see why anyone would want to use this over other tools like power BI or Tableu. Even building a simple dashboard with JS and bridging it with a Flask backend is easier than using the cumbersome syntax of dash.

It was a good course. I really enjoyed it when the labs worked. The labs did not work most of the time. It was frustrating and degraded the learning experience. I spent hours combing the forum and the Internet to find solutions. I was desperately afraid that I would not be able to complete the final assignment. I am glad I was able to finish.

I thought the final assignment shall be focus on Matplotlib and seaborn, but found it was only about "dash". And it is too complicated and exhausting with many bugs. I don't think python has advantage to build a dashboard since it is much easier to use Tableau and Power BI to build it. The final assignment should be restructured and improved.

Many things could have been explained little easily. There is good detail but I think there is some communication gap between the student and the teacher . I think this course should have a visible instructor alongside the content to create better human understanding. Otherwise the course is good overall. Just a bit difficult for newbies .

This is a crucial course however does very little in the way of teaching. The final assessment is also rather buggy. I could not get the dashboard to display in the provided online notebook, so I had to complete the tasks locally. You could argue that this serves better as a teaching aid, however the videos and lessons do not cover enough.

Although the idea of this course is good, it didn't have the same flow as the other IBM courses in the IBM Data Science Professional Certificate. There were no quizes during the videos, and the final project had concepts and code that weren't in any labs or videos. Even the hints from the professors in the discussion were misleading.