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Learner Reviews & Feedback for Data Visualization with Python by IBM

9,493 ratings
1,420 reviews

About the Course

"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data. One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions. The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

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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951 - 975 of 1,417 Reviews for Data Visualization with Python

By Jakhongir K

May 31, 2020

Overall really good. However, would be better if a few videos added about object-oriented visualization. Also some links and methods used should be updated to the latest ones.

By Michael J L

Mar 25, 2020

Best of the 5 IBM Data Science Courses I've taken so far. Some problems connecting with the labs, but you can bypass these by downloading the ipynb's from

By Govardhana

Jul 30, 2019

It was very nice and brief course but it could have been better. Some other topics must be included and some more exploration of different properties needed to be addressed

By Michael L

Jun 15, 2019

This course, although useful was difficult to follow at times. It did not get that into the Artist Layer of Matplotlib but the final project requires the student to use it.

By Elyass S

May 23, 2021

It's an informative course, it even tested a student's perseverance and creativity in solving/bypassing various bugs. The final assignment was definitely an eye opener.

By Venkata S S G

Jan 30, 2020

final assignment is tough. Everything else was decent and intuitive. Good jupyter notebooks and labs for practice were provided. Do practice all ungraded lab sessions.

By Christopher L

Aug 2, 2019

Would've enjoyed the course more, if it got into the nitty gritty of annotations, but a comprehensive and decently delivered course nonetheless. Kudos to the IBM team.

By In W C

Oct 3, 2019

Just like the few previous Python courses by IBM - errors and typos have yet to be fixed. But other than that, it is a really good introduction into using Matplotlib.

By Tichaona M

Sep 10, 2020

This is a very fascinating and demanding course when one follows all the Skills Network Lab exercises. The advanced visualization tools are worth the trouble!

By Neelam S

Jan 3, 2020

Examples contained less python codes as compared to asked in final assignment. More python codes for visualization are to be conveyed.

Queries are not solved.

By Seymur D

Jul 23, 2019

The course content was good, but final assignment needed more clarity in the what was demanded from the question. Lots of interpretation left for the student.

By Alexej Z

Nov 1, 2018

Some tests are not comprehensible in their entirety and can only be carried out with a great deal of effort. Otherwise very good content. I could learn a lot.

By Rohan B

Jun 20, 2019

Course is really helpful for indulging someone into data visualization but sometimes in the lab some stuff is just present for you to figure out yourself.

By Magnus B

Mar 11, 2019

The information provided was straightforward and easy to understand. However, the final lab requires extended knowledge that is not covered in the videos.

By Niladri B P

Jun 7, 2019

Excellent lab material. However, I feel the video lectures were a bit too brief and could have tried to explain the technical concepts a little bit more.

By Varun V

Jan 1, 2019

Nice course. But Seaborn examples could have been more helpful. Also, please use Python 3 for examples. Thanks for the video and more better class labs.

By Makinde M D F

Sep 17, 2020

The Course is an interesting and practical Course. Alex Aklson, the lecturer is a good teacher too.

Many thanks to IBM and all the teachers on Coursera.


Oct 11, 2019

The Course materials are brief and Short and understandable. No need to learn junk topic only relevant areas are learn in this course. Thanks to IBM .

By S B A

Sep 16, 2020

The course was good, syllabus was okay, I think that seaborn could have also been added in this, though waffle chart and map was very new for me...

By Tenin M L K

Aug 19, 2019

Good condense course. One thing is a the recall of the data set and the lab at the beginning or at the end of each lecture which are very annoying.

By Nicklas N

Jan 29, 2019

A good overview of different visualization methods in Python. The final assignment is a little tricky and requires a diverse set of Python skills.

By Sai S D

Sep 11, 2019

Its a great course to learn all Data Visualization libraries in python and thier constructs. It helps me alot to learn Data Science using Python.

By Pradeep M

Jan 9, 2020

Good course. However, the instructor should add a slide mentioning what kind of errors can occur in python programming and how to correct them.

By Andrew R

Oct 23, 2019

Some instructions could have been clearer. The final project required code that wasn't covered in the lessons. Had to research the internet.

By Daniel E

Mar 12, 2020

Not all code examples were explained thoroughly enough within the labs, definitely not within the videos. Generally a good overview though.