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Learner Reviews & Feedback for Data Visualization with Python by IBM Skills Network

10,785 ratings

About the Course

One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualizing data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualize both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights. This course will teach you to work with many Data Visualization tools and techniques. You will learn to create various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more! You will also create interactive dashboards that allow even those without any Data Science experience to better understand data, and make more effective and informed decisions. You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE. You will use several data visualization libraries in Python, including Matplotlib, Seaborn, Folium, Plotly & Dash....

Top reviews


Aug 13, 2020

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!!!


Nov 20, 2019

It's a really great course with proper hands on time and the assignments are great too. i got enough opportunity to explore the things which were taught in the course. Really Satisfied. Thanks :)

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1326 - 1350 of 1,658 Reviews for Data Visualization with Python

By Ryan H

Feb 6, 2020

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.

By Vyacheslav I

Nov 25, 2019

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.

By Lyle W

Mar 28, 2021

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.

By Brendan H

Apr 30, 2020

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.


May 26, 2020

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.

By Awab A

Aug 30, 2019

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.

By Lucas Y

Aug 19, 2022

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.

By William Z

Mar 20, 2019

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.

By Marnilo C

May 4, 2019

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.

By Steven T

Oct 27, 2018

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.)

By Hizniye I B

Aug 27, 2021

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!

By Carmen R

Jul 26, 2020

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.

By Arvont H

Mar 29, 2021

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.

By Colin O

Mar 29, 2023

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.

By Forest K

Mar 25, 2023

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.

By Sara J H

Mar 6, 2023

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.

By Tharaka G

Feb 27, 2023

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.

By Tammara S

Aug 26, 2021

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.

By Hanru L

Mar 28, 2021

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.

By The B

Jul 16, 2022

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 .

By James P

Apr 10, 2021

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.

By Bryan B

Dec 19, 2019

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.

By Martha C

Feb 26, 2021

The first part of the course was good as I learned about creating visualizations for EDA. Unfortunately, the section on dashboards was not done well, in my opinion, and the final assignment was quite frustrating. I kept getting errors with my code but did not have enough knowledge from the course to understand how to fix them.

By James Q M

Jun 27, 2021

I learned from this course, however, of the nine courses in the professional certificate, I would say this is the worst. There are errors in the instructions of the labs, including being incomplete. Jupyterlab doesn't work (though they do say that it is optional.) I believe they need to reevaluate the content of this course,

By Tanya S

Nov 19, 2020

I felt that the course was a bit disorganized. The actual code bits that were used in labs were hard to follow and material covered in final assignment required a LOT of independent googling of pandas libraries. Overall, it was a good overview but this course fell short compared to the other courses in this specialization.