I spent more time trying to fix "localhost refused to connect" and other errors from the end of course management, while submitting my final assignment, than on doing the actual course or assignment - it's not a very efficient way to test a newbie like me who isn't familiar with these various environments.

Also, when there's no instructor speaking to you and it's just robotic voice and text, it doesn't feel much like an educational course and is off-putting. The lectures were also way too short and flew through concepts too quickly. The only mitigating factor was the labs which were decent and the only thing that actually aided my learning rather than being a hindrance. I hope you don't take this the wrong way, but I'm unsubscribing from this course. Thanks anyway.

This course touches some very interesting topics and tries to cover many aspects of Data Visualization. That said the videos do not explain anything in depth, most of them are just 3 minutes presentations of the same code that will be explained in the labs wasting another 2 minutes just to do THE SAME dataset formatting IN EACH VIDEO! The labs are interesting however you have to read and understand a lot ON YOUR OWN, most parameters are not explained (of course you can just copy paste the examples to pass the labs) and if you really want to learn you have to study most of the material on the websites and tutorials of the various tools that are used in the course e.g. matplotlib, Plotly, Dash etc. So I don't really understand what you need this course for.

El curso esta descripto como nivel intermedio, sin embargo, las primeras dos semanas se tratan plots basicos (ej. boxplot, pie chart, scatter, etc) pero no se profundiza muchos sobre las opciones de parametros a ajustar ni como mejorar la parte estetica, y la practica solo da un pantallasmo muy general. Yo en mi caso buscaba conocimientos algo mas avanzados sobre estos graficos.

La seccion de dash, si bien yo no la conocia y estuvo interesante, fue poco clara la explicacion, una practica completa pero como que me falto mas base y explicacion de los diferentes modulos para poder llevarla a cabo. Al final no me quedo muy claro como se deberia armar el archivo para dashnoard ni que rol cumple cada parte.

I would give 2 stars for the materials taught prior to 5th week's final project. It goes downhill from there. The final project is atrocious. The assignment does not run in the suggested platform (e.g., Jupyter notebook, Watson, or Skills Network - the latter has been malfunctioning for couple of weeks now). I had to run the project in Google Colab to get the output. Most of the students are facing the same problem. Ans yet, neither the instructors nor IBM staff provide any workable solution. Furthermore, the instructions given does not match with the output generated in the lab (e.g., only one upload 'space' for uploading multiple plots). Terrible experience for most participants.

This was a horrible course culminating in the two assignments. The coding experience was mostly debugging as the skeleton code has problems on its own. The assignments for graphs (part 1 and dash) were not clear for some of the graphs. And people must have been confused like hell as the peer review of my code did not bring me 100 percent of the points, though it was quite stable (unlike the skeleton). And worst of all, I spent most of the time debugging code in an unfriendly environment--right, even if this was the intention, the intention was bad. Never again. The positive part is of course the cheatsheets. But, frankly, this was the worst module I've done with IBM.

Overall, the course has been interesting and pretty useful to learn the basics of Data Visualization and how to implement interesting graphs in Python. Unfortunately, the final assignment is a complete mess and a waste of time. The tasks themselves took about half an hour to complete, but the provided code is full of typos and small errors that required days of troubleshooting, only to figure out that my code wasn't working because of a couple of misplaced spaces in a code that was meant to be only copied and pasted. In addition, a basic understanding of HTML is required to complete the final weeks of the course.

The topic was interesting and visual feedback is gratifying.

The instructor videos were almost totally worthless. The first video should explain how the course will be conducted (information presentation, additional reading required, overall approach to homework, etc.) with subsequent videos explaining important concepts.

The included sample code files at least presented a progression to learn some concepts and provide a basis for experimentation.

The final homework required extensive internet searches rather defeating the point of a "lecture course".

By far the worst Coursera course I have taken.

The instructions and rubrics for the final assignment part 2 are unclear. It would be beneficial if the instructors could explicitly specify whether they want students to take screenshots of the code or the graphs. The phrase 'take a screenshot representing' can be interpreted differently by individuals, leading to varying submissions. Consequently, I received different grades for identical submissions and a zero for accurate code. Resubmitting solely due to a lack of standardized grading requirements is both time-consuming and energy-draining.

I think the materials are good, and give a very broad overview of what visualization packages are available.

However, having the assignment based on Plotly Dash is very painful as it is not a straightforward setup, and some individuals might face challenges even executing the codes.

I would suggest sticking with matplotlib, as I presume the main objective is to know how to storytell, and not on how fanciful your storytelling can be. We can probably leave that in other courses like Tableau, D3.js or a focused visualisation course.

One of the main packages used has been deprecated. Final was confusing to many. The decision to use a different tool to run the python code should be changed to use the same software that is typical to the program. Should consider not focusing on the dashboarding elements of python. The final would have been better if it had been in the typical environment either through IBM or coursera and required just submissions of code and visualizations from a jupyter notebook. There were also technical difficulties with the final project.

I was really enjoying the classes in this certification until this one came along. There were so many errors and issues and it was an incredibly frustrating experience. The only reason that I am even giving it two stars is that I feel like I did learn a little in the beginning of the course. I really hoped to learn more and now feel anxious about what the next course in this certification will be like. Very disappointing and discouraging experience and such an unexpected turn after so many great courses.

The plotting aspect was fine cause it is meant to be straightforward, but the dashboard lessons taught me nothing. I spent a lot of time self-learning dashboard. Also, I see no point in introducing students directly to plotly dash, instead of using the jupyter-dashboard first.

Finally, using a sandbox environment is extremely dangerous, you should be more careful about these things. I took this course as part of the Data Science Professional Certificate Programme, and this has been the worst, by a margin.

The course material is well presented and interesting, but the final assignment is totally out of line. It contains questions with items that are not in the course or prior courses and I for one could not find on the internet. It took much longer and was much more difficult than final assignments in any of the prior courses. The professor needs to change this assignment, in particular question 2. Other people have struggled with the assignment and complained about the course and nobody seems to care.

This course is great, the material is well organized and easy enough to understand and learn however the final assignment is a royal pain due to formatting issues. More time was spent trying to figure out my formatting so I could run my application than learning the material itself. It would be nice if the code for the final assignment could be submitted so partial marks could be awarded. I spun my wheels for 2-3 weeks on this before I could get my dashboard to successfully run.

Thanks, Colin R

This course is POORLY maintained. The instructions are unclear and often confusing. There are errors throughout the modules but especially in the final assignment. The code given by the instructions to download the required libraries was out of date and wouldn't work multiple times. There are also numerous errors in the instructions, misspellings, and an overall total lack of attention to detail which confuses students.

Do yourself a favor and take the Google version of this course!

the videos were short and lacking content. The quzies were sometime not based on the videos, for example, one of the modules were a short 1 minute clip doing a wiki definition of the application or whatever. The assignments were semi okay but virtually all the heavy lifting was already done for the final assignment and the other assignments. I had to look everything up myself for the most part the videos were close to useless. Zero in depth knowledge on anything in this section.

At the end of the course we introduce the tutorial part on an Integrated Development Environment (IDE) based on Theia (an open source IDE platform similar to VS Code) to develop and run Python code. This system is extremely impractical and does not allow to save the exercises on file. In fact, for the final exam, a series of reports are required that are not at all simple and paratic in performing in such an environment and with the few notions explained during the course.

The lessons were great! Super informative and I truly learned a lot. The final assignment was extremely frustrating though as minimal instructions/links were provided and some of the links were broken. The concepts in the final assignment were somewhat related with the course material, but much more advanced (ex: using the artist layer of MatplotLib with looping to create patches was NOT covered in the material). This made what I did learn very frustrating to apply.

Matplotlib, Seaborn, and Plotly are basic visualisation tools with a monotonous narrative and an emphasis on code explanation. The Dash part is not well-organized. The directions are not clear and understandable. As a result, during the project stage, there is a process that is incompatible with the educational goals and will consume needless time. The curriculum and section weight should be reassessed, and more specific criteria should be set.

Often found bugs and errors in the code supplied by the labs. The staff seemed to ignore most of the posts on the forum when other students were looking for help / solutions. The course also fell under the unfortunate category that most online courses fall under - the course starts off basic and understandable and then makes leaps in information and expects students to keep up. Loved the start of the course, hated it by the end.

The final assignment has quite a few issues. I understood the Dashboard design is more for us to have some basic ideas of how it's generated. But it was way more complicated and I ended up spending 2 hours working on it. After finishing it I don't think I learned anything useful in particular. All I was doing was to fix bugs here and there and referring discussion in the course and github. It doesn't make any sense.

The biggest challenge of this course was getting the workshops to work to begin with, and not what the course is supposed to be about. I can't say I learned a whole lot about creating dashboards or visualising data, but I certainly learned more about troubleshooting. Most of the time I spent on this course was trying to get the workshops to work as they were poorly made and contained errors or had other problems.

Very interesting topic with poor materials. Apparently not only I had problems with the final assignment, but earlier materials also were not very precisely explained. It forced me to look for support and solutions outside the Coursera, which is good, but I would imagine that everything is prepared, explained with references to external sources. Sorry, for me this module - great disappointment.

Not good. The quizzes were pointless and the final assignment deal minimal modifications (that have nothing to do with analyzing the data ) that are not covered in the course. Of course you can do these minimal adjustments if you search the documentation for the plotting libraries, however is this was the goal of the course why not teach it? if not, why make us bother with it?

Some useful information but overall this course needs upgrading. Pretty much all of the information was given in the labs which made the videos feel a bit pointless. Final graded assignment required so much outside research not covered in the actual course that it took far longer than expected. Quite surprising as the previous 6 modules were all really well thought through.