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.
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!!!
par 清基 英•
I was so upset for the last project because knowledge of I have learned from this course was not enough as all for completing all the questions. I really wish to get more advice or tips for the project.
par Stephen V•
Doing the IBM Data Science Certificate and this is probably the worse course. The content is relevant but the directions and labs are poor compared to the others. The explanations aren't as clearn.
par Tara S•
A lot of problems opening the labs. The final assignment required us to do things that were not discussed in the course and it was unclear where to get the relevant information to complete it.
par Federico T•
Video lessons are poor in explanation of matplotlib syntax as well labs. Differences between pyplot and artist layer are not clear: a lot of work has left to selftaught. Kind regards, FT
par Ermek A•
Some exercises throughout the course aren't explained neither in the video, nor in the labs.
It is hard to understand the Authors data visualization functions explanations in the course.
par Sarthak S•
The Dashboard week is a mess, nothing is explained enough and the final assignment is awful broken code wreck that maybe works for only about half the people.
This Course wasn't that good like the previous ones, the Videos were quite short and the labs weren't very explicit and made to be understood by everyone.
par Andrew S•
Not everything that was needed in the final project was covered well enough (or at all) in the videos and lectures
par vijay v•
Very theoretical, Quiz questions were made over complicated. this make loose interest in completing the course
par Eduardo F V•
I am happy with what I learned but I think it is not as good as the rest in the series.
par Sobhan A•
Terrible IT support. Labs do not work. Never recommend IBM courses to anyone.
par Anita L•
more examples in the lab for the most popular chart types is appreciated.
par Hakki K•
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.
par Yifan J•
Honestly, this is the WORST course I have ever taken on Coursera. And Alex Aklson is the worst instructor. As a course on data visualization, it should focus primarily on how to VISUALIZE the data. In other words, when we have the processed and formated data, how can we turn it into plots. But in the videos, especially week 2, the instructor over and over again repeated the data processing for Canadian immigration. After watching the videos, what I remember most clearly is not how to make the plots but the total number of immigrants to Canada from each country. And for the most important part, that is, the details of how to generate the plots as well as applying various features, the instructor just spent very little time in the videos. Yes, a lot of them are covered in the lab, but remember that for a course, the lab should just be supplementary of the lecture. The instructor should teach those skills systematically in the VIDEOS, and the lab should only be used to reinforce our understanding of those skills. In particular, as has been mentioned in many comments, the final assessment requires using the artist layer which was only introduced a little bit in the lecture but NEVER taught in detail. This is not responsible behavior. Overall, I am very disappointed. And I hope that IBM can ask another instructor other than Alex Aklson to create a new version of this course.
par omotoke o•
The Data Visualization with Python course needs a serious review by the instructors. With the growing demand for Data Analysis skills across almost all industries, I decided to take all the courses on the IBM Professional Data Science certificate platform. I had taken 6 out of 9 courses when I took the Data Visualization course. It was the only course out of all of them that gave me a serious headache. The course honestly disappointed me and ruined my day, cos I could not figure out the Peer graded assignment. Data Visualization is one of the backbones of Data Analysis because it is a tool that is used to communicate with the world. I was excited to take the course and all was going smoothly till I took the final peer graded assignment. The scope was not covered in the course and it took me forever to figure out. Please, the instructors of this course should kindly review it and make the necessary adjustments for the sake of future individuals interested in the course.
par Carlo P•
Very disappointing. Unfortunately, one of the worst course of the IBM Data Science professional certificate. It does not have the typical quality standards of an IBM course:
- Most of the videos are very short and do not go in the detail of the topic
- Videos have bad quality audio
- Labs are not laboratories where you use what you have learned, but the real lessons (without a deep explanation of what is done and why).
- Labs are also unbelievably full of typos.
- Most of the final assignment requires things that are not explained.
- The course also lacks consistency: they explain something and request totally something else regarding Data Visualisation (that you have to search on google).
- It should be a longer course, with longer videos that explain in detail how to make the various diagrams
I hope IBM will make a massive restyle of this course.
Do not attend the course if you are not obliged (you are studying for the IBM data science certificate).
par Inês B•
Now that I've finished this course, I can honestly say it was the worst from the IBM Data Analyst curriculum.
It was full of mistakes (spelling and syntax wise) and although there were some new things, this course seems almost irrelevant.
The cherry on the top was to make a dashboard with information only given in two short videos that required previous knowledge of HTML and C+ (things that we do not approach on this course!)
The final assignment is way way too complex considering the students are entry level users.
I would really recommend IBM to do a complete makeover of this course!
par Reinaldo O•
If I could give this course zero star, I would! Please IBM and Coursera, fix this course! It's the worst course so far in the specialization. The videos are poorly made. The labs are full of bugs. I had no prior experience in data visualization and it was extremely hard for me to follow the labs and assignments. This course it's not for everybody, but for people with an acceptable knowledge of Python and HTML. I wish all the courses in this specialization were like the SQL course. That course was beautiful. You should check that.
par Sergii G•
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%.
par Soumik B•
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.
par Ramiro G•
In the final assignment you lose lot of time troubleshooting or dealing with the errors in the provided skeleton code. You can see this yourself by reading just a few consultations in the disscusion forum.
The rest of the final assignment its just basically copy/paste on the empty slots, so not really learning more than what you can already learn by watching a youtube video.
par Dmitry N•
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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.
par christos a•
Course feels extremely rushed and the final assignment requires knowledge not taught in classes. I DONT recommend this certificate. If i wanted to google everything i would just kept my mony and wouldnt spend it on garbage moneygrabs.
par Elena G•
The class itself is very high level (and super repetitive on unimportant information) , but the final assignment asks for things that were never covered in the class. Anything I learned from this I taught myself. Very frustrating!
This course is a disaster. Nothing works. It is impossible to propperly prepare the tasks because not one single lab is working. I am paying for this and I feel cheated. I am truly considering dropping from coursera.