This is a very enjoyable course, even though I was familiar with most of the tools, I still got to learn a few new tricks. If you are not familiar with programming, you might find the final assignment a bit challenging. Therefore, I strongly recommend that you take the course labs very seriously.

Course is really good to learn all the fundamentals of data visualization along with the advance techniques to master it. Assignments and practices are designed very well by the instructors and you would have to put all your efforts to understand and master all the course. Kudos to the IBM team

Best course so far in the series. The labs are great, they make you really apply what you've learned.

The final assignment is a true test of your skill. You can't repeat what you've done in the labs or what you've seen in the videos. Perfect test of skill. I've learned a lot.

Thanks Alex Aklson.

The final assignment is excellent! It is not just straightforward but requires us to think and research, go beyond the basics learnt in this course. Amazing course! Just the right amount of videos, simple labs, and challenging yet effective assignment, I learnt a lot! Thank you Alex Aklson <3

This course consist of most of plotting types with python, it's not only about matplotlib, but addtional tools and methods to create maps. It gives you a fabulous understanding about visualization using python. Completing this course, you will be able to demonstrate the data in ways you want.

Liked how it covered a vast amount of topic related to data virtualization. The notebooks are really useful for taking help in future works. I did like too see more details explanation and practice problems related to the libraries used in the notebook exercises. Overall loved this course.

Though the videos were short and running fast the labs were well designed, the peer graded assignment is well prepared too. I feel more accomplished than before. Honestly, this course should've been suggested to be taken at least before 2 other courses that I already finished to get here.

It was very good and interesting how to create different kinds of maps for different purposes, specially I liked the maps that you can embed in an image like the wordcloud using a mask from Alice in Wonderland, I will try to do something similar with another topic. Thank you very much.

Course is very good. I have advice for learner to pay attention to each week videos,, especially Week 5. Final exam is tricky exam. Otherwise course is well design. Only complain, lab is availability is unreliable. I had to switch to local jupyter notebook. Otherwise good luck to all

I appreciate the way the Instructor always (always!) refer back to previous lessons, so that the transition to the next lesson becomes seamless. The lab also reviews past exercises so you are not at a lost (especially if you have not gone through the course for a while).

Content wise, the best course in IBM Data Science Professional Certificate, as the quiz, lab and assignment modules really tests your knowledge. It made me learn a lot apart from course content to earn the course completion. Kudos to the content creators Jay and Alex.

As I have no coding experience, it is hard for me to follow the course material. To finish the assignment, one have to repeat the exercises in the labs until one has everything understood and remembered. Not a easy course but it gave me a sense of fulfillments.

Excellent, this is a great course introducing and teaching visualization !

PS : You might read about people telling that some of the materials in the assignment is not in the course. It's false it's in the lab. These people should take notes while working.

Excellent Course. I would recommend that the first week of this course be included in the introductory courses in Panda analysis. It will allow the student to really see the value of Pandas over an Excel and provide more of a boost to learn quickly.

a great course, data visualization is one of the topics that draws many people into the field of Data Science. I found it to be a very interesting course, one whose lessons I will return to often as I continue to build my knowledge and experience

The first 4 weeks were very easy and then during week 5 things gets really heavy and you need to dig deep into the subject matter. Nevertheless is was a great learning experience and now I feel enabled having transformed my R skills into Python.

This course gives a clear and deep understanding of different plots as well as different sub-modules in Matplotlib and folium. In addition to jupyter notebook, one can explore to cloud IDE to create interactive dashboards. Really worth for cost.

This course is very rich in knowledges about data treatment and data visualization. All the steps are clear for intermediary students on python language. I recommend for everyone who wants a essential skill for the future demands of technology.

This is really great course. It covered all the contents related to data visualization with python. Now, I can say that I have a good amount of knowledge in creating data visualizations. A very thanks to the IBM community to make this course.

At first I thought this course was the easiest among the 4 courses in this specialization. Turned out this course was the hardest but also worth spending time on because I have learned lots of applicable knowledge. Thank you Coursera and IBM!

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

What an outstanding way to learn such crucial skills from the world's best platform of Coursera.

I am feeling really proud to complete the course.

IBM Skills network labs are just speechless.

Jupyter notebook is just an amazing tool.

It was one of the better courses in this data science professional certificate. I like that the datasets didn't come prepared in advance in the lab exercises and I had to do some work on the on the data before creating the charts.

I felt this was hard. I realized this particular course forced me to review on how I needed to develop the mind set to become a data analyst and software developer. This class force me to learn more and keep going forward. Thanks

For the lab that used the jupyter_dash library, it would be really helpful if you include a video that shows us how to fix or bypass the bug. Many are still confused about how to do it and just keep restarting their lab kernel.