2018년 11월 27일
The course with the IBM Lab is a very good way to learn and practice. The tools we've learned in this module can supply a good material to enrich all data work that need to be presented in a nice way.
2020년 8월 13일
Great course, one of the best course to get hands-on learning for Data Visualization with Python. Particularly the lap exercise, it will make you think on every line of code you write. Excellent!!!
교육 기관: Atfy I Z•
2020년 4월 21일
A great course for you to further understand the mechanics of data visualisation as well as providing a space for you to familiarise and test your understanding on the subject matter.
교육 기관: umair•
2019년 4월 11일
this course should come before data analysis with python
교육 기관: Rodolpho P•
2020년 9월 29일
Although I understand that learning doesn't take place at only one place, this course seemed very weak in terms of providing enough examples necessary to solve the problems in the final assignment.
All videos had a same part that was repeated, and no information was agregated by this repetition.
The contents of the labs are quite good, but a more detailed explanation could exist.
Some updates are needed: one of the labs uses MapBoxBright, which gives us a clean figure with no map because this is not available anymore.
The final assignment required us to look for solutions that were not present in the course, and in my opinion, they should be. The student should go to outside sources when it feels a need to understand something deeply or if the way presented by the instructors was not the best for the student to understand what's going on.
There's a lot of room for improvement: the videos should not be repetitive; the contents should be updated, anything that is required in the assignment should be presented throughout the course, if it's not in the labs it should at least be in the videos; the final assignment could provide a notebook with the requirements as the other courses in the specialization offer (in my case, I took it as part of Data Science Professional Certificate by IBM); if this is not the case, the student should be prompted to create a notebook with the questions and answers, which would estimulate even more the creativity around data visualization.
교육 기관: Baher•
2020년 8월 23일
In the final assignment, I had to explore the internet to get some codes to display the bar graph or the map. These codes were not covered in the class. The course needs to get improved by giving the keys of how to do things . For instance, the method .patches was never covered in the course. I do not know how to use it. It may be a part of panda library, but the method was critical to do the assignment. There are many other examples. I spent almost a night to finish the assignment because I took a long time to self learn these tasks. It is good at one side, but the course should help me.
교육 기관: BISHAL C•
2021년 11월 19일
The course content is great but the way it is being taught is not up to the mark..
the labs are good but that's not the way everyone can learn things..
Something can be done like some instructor should be there who will be teaching us about those libraries. In the videos, the instructors are just giving a brief idea about the libraries and asking us to go through the labs for better understanding.. How about giving more ideas where someone will guide us through the labs too. I hope you can understand..
교육 기관: Vimal O•
2021년 11월 9일
On overall IBM data science professional certificate track: Pros: Content is just good enough, instructors are good. Cons: IBM watson and the platform given to practise on is awful and has terrible performance and reliability issues, most often doesnt work and had an impact on my test deliverables. I personally overcame those issues to some extent with kaggle's and google colab jupyter notebook environments.
교육 기관: Bob D•
2021년 12월 16일
Some good material, but some was pretty niche and therefore less useful. The lessons were okay, but as usual the whole thing was riddled with typos and technical issues. Not good enough for a major organisation like IBM.
교육 기관: Sarah s•
2019년 1월 14일
This course was nice but there were extra stressors that weren't included in the course.
교육 기관: Frank A I•
2021년 3월 21일
Unfortunately, this has to be to worst Coursera course that I have taken. I only give it 2 stars for the first few weeks, otherwise this is more of a 0/5 star
While the beginning was a descent course, the final project was very much a left field task. While it did have some of the material from the course, there were several aspects that were not explained in depth or not at all. It also didnt help that there were some errors in the base code that were not explained and it took the students to resolve them.
Many people pinged the instructors for assistance, including myself, but aside from a few comments here and there, all their responses were basically "Review this thread that says to run the code a gain and give it time to load". When I asked for more detailed instruction beyond that thread, I never heard back from the instructors. With so many students opening threads and asking the same question, the instructors should take that as a hint that something is wrong and that they should take a more active roll to resolve the issue (a new lecture or assignment to help explains the errors rather than a thread provided).
The best part was that when I mentioned I had issues with this at work, a coworker of mine who had 20 years experience, at least 10 of which is with Python, offered to look over the code with me. He was confused with what the instructor was attempting to have us learn with the final assignment.
In short, I rate this course low because of the final assignment not being properly explained before or during it and that fact that there is little to no instructor support beyond repeating themselves and telling students to "toggle the dropdowns and wait"/ "rerun the code"
교육 기관: Hani H•
2022년 4월 3일
This course started out good but quickly went downhill. The first two weeks focused on matplotlib, and while I did learn something useful, I did not need a dataset recap on every single video. its a waste of time.
Week three is where things quickly go off the rail. Waffle charts were introduced, and we were told that there is no quick way to do a waffle chart in python. That's fine, I'll learn how to do it the old school way. That was time consuming but time well spent right? WRONG. When you take the module quiz you are asked if pyWaffle is the best way to create a waffle chart. You answer no because you actually watched the videos and did the lab training, but you get a wrong answer. You check online and what do you know, you can actually do a waffle chart with 2 lines of code. IBM knew this (hense the question in the quiz) but nobody bothered to update the lab or the videos
The video on word clouds introduces the concept and you were supposed to learn in in the lab, but then you get to the lab and you are told to skip this section. I have no words for this
The part on dashboards takes the cakes. IBM basically provides you with external links and leaves it at that, there isnt even an attempt to teach you these concepts. And you know what the best part is? the course project requires you to build a dashboard. Yep, the thing they didnt even attempt to teach you.
Anyway this review is too long and I doubt anyone reads it, but hey, if you do, just be prepared to read a ton of external resources because you are not getting what you are promised
교육 기관: Gina A•
2021년 12월 15일
The first few weeks of content was actually really useful for someone interested in data science, but the last 2 weeks were a bit of a trainwreck. It was clear that the assignments related to dash weren't well conceived--there were many issues, instructors were slow to address these issues in the forums in a concrete way, and honestly it felt more like a programming lesson than something practical in data visualization.
The final assignment grading also wasn't well conceived. The way the guidelines/questions were asked were very unclear, so sometimes you didn't see what you actually needed to upload until you had already taken the screenshot or submitted the assignment. This carried over into the grading--there were times the directions said to remove points if certain things weren't present on a student's answer, but then as a grader you actually didn't have the ability to remove points for that reason.
These types of mistakes are, I feel, pretty sloppy and shouldn't exist in a course that's part of an IBM-backed certification that people pay money for.
교육 기관: Thierry C•
2021년 7월 31일
This course is the most disorganized I ever followed to date on Coursera. Up to the step where we learn about the Dashboards, the course is pretty well presented and the labs are working with good guidance but then, when reaching the dashboards, the guidances disappear, none of the dashboard lab work in JupyterLab. The final exam is a torture with a peer review submission so messy that you will have to spend more time assembling screenshots together than producing the dashboards themselves, and after so much struggle, you will have to answer sneaky questions with some answer that do not even make any sense in English. Be prepared for a lot of frustration and even though, they say that knowledge of HTML language is not required... well... most of the dashboard labs are actually based on HTML language. I wish the course was better prepared and that all labs were working, I have learned less than I could due to those broken labs.
교육 기관: Alasdair T•
2020년 6월 22일
Course could benefit from a refresh - for instance, support for Mapbox Bright tiles has been dropped from Folium for 1+ year, but the course still tries to demonstrate their use. There are several posts from confused students wondering why this doesn't work. Surely it'd be better to just remove/update this section of the course rather than have to deal with so many bug reports in the forum?
Also the videos for this course are extremely repetitive and barely of any relevance, e.g. 1-2 mins of several of the videos is just the same footage of the data being imported to Pandas and cleaned. Once you've seen this once, you've more or less got the point. Add to this that the Final Assignment required knowledge of matplotlib which was *not* covered in the course, and had to be researched elsewhere, and it seems obvious that the quality and relevance of the video content could be improved significantly.
교육 기관: Carina D•
2021년 4월 20일
Although the course was informative, the course components related to Dash applications need to be reworked or removed. For a course that should only require the use of a course-provided cloud-based Jupyter notebook (JupyterLab via IBM Skills Network Labs), the labs and final assignment should work via that service. The final assignment also should be reworked into a new assignment because of its incompatibility with the course-provided Jupyter notebook. A final assignment should not be debugged extensively and require the use of outside applications (one of them being an application that requires computer installation) to be completed. The course should explicitly state what resources are needed for the final assignment if it requires outside resources, and the debugging instructions should be listed in the final assignment instructions, not in a thread in a discussion board.
교육 기관: Ricardo S•
2021년 3월 12일
I'm disappointed. I believe data visualization is a very important skill, but this course didn't teach the most valuable skills.
The videos feel like someone is merely reading the documentation. There is a difference between showing something and teaching something, and very little was thought in this course.
In the labs, the visualizations (1) Do not tell a message (2) Are not compelling (3) Do not teach you how to generalize the idea behind the chart.
The worst part: the course creators apparently know this. Some of the labs don't even have exercises, because clearly these "classes" are not enough to teach you how to do it on your own. And the final assignment has multiple posts explaining how to fix the many oversights in it.
This has honestly impacted my opinion on IBM (is this what you offer to your clients?) and Coursera (is this the average quality of a course?)
교육 기관: João R d C•
2020년 2월 4일
Out of all the courses in the IBM Data Science Professional Certificate, this was the one I had the highest expectation for and unfortunately I was a bit disappointed. The course materials are lacking in information and the final assignment asks for customisations that weren't covered in the course materials, which leads to question: are these important things to know and the materials are lacking in information ? Or are these irrelevant and should be a part of the final assignment? Because if they're just there to make sure no one gets a 100% grade, then that's just sad.
교육 기관: Anoosh G•
2021년 2월 6일
Final assignment was frustrating, its was difficult, It took more than a month to get my assignment reviewed. At the beginning i waited for a week, I did not get any peers to review, then soon after a week when i logged in, my assignment was gone and 4th week videos and new assignment were reset. I completed again all modules and new assignment finally and again waited for a week to get it done. I've spent more time in this course in the entire Data Science Professional certificate, I don't know whether this is a problem from the creator or coursera itself.
교육 기관: James H•
2020년 5월 5일
This class could have been one of the best based on my interest, but it wasnt explained very well and I had to use outside sources to figure out what was going on in the labs and sections... Also some of the final project material wasnt covered in the class itself... It was more difficult than it needed to be... Once I used Google to find answers, the stuff I actually learned were useful...
교육 기관: Mehmood S•
2020년 4월 29일
Much of what was tested, was not taught in the course. Therefore, the course requires individuals to do their own research online to answer the final assignment questions.
The purpose of paying for the course is to quickly learn fundamentals from the course, NOT to spend hours looking online for the right answers and waste time with trial and error experimentation.
교육 기관: Mark S•
2020년 8월 19일
Very poor. As the course carries IBM's name, I expected a premium product, but I was disappointed. The training videos were brief and didn't go into the material in any great detail, and certainly didn't prepare the student for the lab sessions or the final assignment. I learnt more from Stack Overflow than I did from from the training videos.
교육 기관: Ana C T M•
2020년 1월 21일
Links did not work for classes hands-on exercises, repetitive video explanations, and final project required content that was not explained in classes. Overall, it was a bad experience on a subject that should have received more thought and caring from instructors on lesson plans and class materials given its importance.
교육 기관: Sean H•
2020년 8월 14일
Labs and lessons did not adequately prepare me for the peer review lab. A lot of information went through quickly or was hard to reread on account of the sheer volume of charts created. Minor gripe but when learning pie charts the videos mention pie charts being awful without properly explaining why they are awful.
교육 기관: Jeff S•
2021년 1월 8일
-Many videos repeated just over 1 minute of the exact same content reviewing the dataset.
-Videos were very brief and then exercises would be beyond concepts taught.
-lab contained thick code to prepare graphs but not explained.
-Enjoyed creating the maps & learning about other visualisations.
교육 기관: Steve K•
2019년 10월 20일
Almost all videos included the same bit about getting and reframing the data. This was a significant portion of the videos as well.
There seemed to be more confusion around the final assignment judging by the amount of questions in the forum. The assignment needs to be rewritten or made more clear.
교육 기관: Juan C C•
2020년 3월 23일
Content was solid, but videos mostly said "go do the labs" vs offer meaningful tips for the final an beyond. Worst of all, the tech is outdated. I spent an entire weekend working on the final assignment due to technology issues. An embarrassment for Coursera and IBM that they let this happen.