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Learner Reviews & Feedback for Data Visualization with Python by IBM

4.5
stars
9,817 ratings
1,474 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

LS
Nov 27, 2018

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.

AM
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!!!

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1201 - 1225 of 1,469 Reviews for Data Visualization with Python

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.

By Toby C

Feb 6, 2020

This course was good but for too many of the final assignment questions I really had a to look up how to do it on the web.

A better explanation of the key_on parameter in choropleths would help - even though the entry in the json file is features - the key_on value is feature.properties.<key> not features.properties.<key>.

By Jovita A

Dec 19, 2020

Needs further improvement, examples: (1) discuss important features/syntax ... go over it, may need not be too detailed but simple instructions on what the parameters do, (2) dont repeat throughout the case because it is assumed that the students knew it from the start so that other topics can be discussed or included.

By Brian C

Apr 20, 2021

Course was very hit and miss, fine through to the final section on dash boarding which was all over the place. Complicating matters was the fact that the lab sessions wouldn't run on the suggested site, meaning that they needed to be downloaded and executed separately on something like VSCode or Google Colaboratory.

By Claudia R C

May 10, 2019

The course is nice, but there are several issues that could be easily solved:

Some of the notebooks on JupyterLab were not working (e.g. "exploratory...").

On the final assignment page there were some bugs regarding the upload (i.e. question 3)

The videos in week 5 were too condensed and resulted hard to follow.

By Joshy J

Oct 31, 2019

This course is a little disappointing for me. It is a 3 Week course and content you learn in this course are not even cover introductory sections. The Final Project is So hard, that it didn't cover the important sections. I don't suggest this course if you are really serious about Data Visualization.

By Kevin O

Apr 19, 2019

None of the labs data imports worked. The majority of the video content said to take the time to really learn the topics via the labs. The final assignment data sources worked, so at least that could be completed. Paid courses really need to have external dependencies reliably available or updated.

By Louis C C I

Mar 20, 2021

The content was really interesting and I learned a lot. I just wish the code was explained better because there were a lot of times where there were functions I had not seen before and were not explained. The final project was also a humongous pain to complete do to graphs not being displayed right.

By Mark H

Feb 10, 2019

Good content to know. Fair but not great in terms of presentation. Many videos repeated how to prep the data frame so you end up watching the same 2 minutes several times. Also a lot of the things you had to know you had to figure out on your own versus finding it in the material presented.

By Daniel A

Sep 10, 2020

Still good overall but not as well designed as previous courses in the IBM data science certificate track. The final assignment is MUCH more difficult than any content in the labs and harder than previous final assignments, which isn't necessarily bad but it's inconsistent and unexpected.

By Giselle

May 25, 2020

I didn't completely understood the labs and where some lines of code came from. Also, I felt that we don't get enough directions to complete the final assignment, not even which notebook to use. This has been by far the most difficult course of this training in my opinion.

By Yanis B

Nov 25, 2018

Great course except of the final assignment being based on a deprecated or soon to be deprecated version of Folium Choropleth implementation. Please review that part as it could be very confusing to students that do not use cognitive class as their development environment.

By Sean M

Jan 20, 2020

Since students weren't able to submit code, this made it extremely difficult to answer the final project (which I couldn't figure out how to finish). Getting feed back on how to correctly code the answers is more important than showing a screenshot of the final product.

By ADITYA D

Jan 12, 2020

Need more clarity and practice for this course. This course seems the toughest as it asks for memorizing artistic layer syntax which seems so difficult coupled with the humongous choropleth map!

A huge amount of practice is needed for this certificate even after labs!

By Antonio J R C

Aug 13, 2020

Good approach to basic concepts of Matplotlib and other tools to visualize data with Python, but the assignment and final evaluation require much more knowledge than those taught during the course and, eventually you spend more time googling concepts on websites.

By Collin C

Jan 8, 2020

The information was valuable and generally well explained. The final was a massive failure; the classes and examples prepare us for maybe half of the questions, but all the questions depend on building off each other. The only way to pass is to Google for hours.

By Pablo D B

Jul 19, 2019

I had many issues when people marked my final assingment. Maybe the indications should be clarified. For example some people didn't gave me the points for not showing the dataframe with the rows in the same order, although all the rows were respectively correct.

By Eunice C

Jan 9, 2020

not too practical over the course, a lot of theory based which is great as well. But I personally not a big fan of the Watson studio as it's not user friendly. I have to go through a lot of layer on their site before getting to the studio or the notebook.

By Pelin Ö

Aug 3, 2020

Not much on videos, I could find the info in the labs in other courses. It took me very long time to submit my assessment, I had to buy another course to get back on track here. I was demotivated. This course was the least satistfactory among all..

By Odontecete

Mar 14, 2021

THE FINAL ASSIGNMENT WILL NOT WORK. PERIOD. NOBODY ANSWERS ANYTHING IN THE DISCUSSIONS. THE CODE THAT IS GIVEN IS FULL OF SCRIPTING ERRORS. AND NOBODY CAN GET JUPYTER CONFIG TO FREAKING CONNECT.

PLEASE FIX THE FINAL ASSIGNMENT SO THAT IT WORKS!!!

By Jan M

Aug 1, 2020

Topics were interesting, but the amount of new code being explained dramatically decreased. Also the final assignment was nightmare-ish as I was often forced to make code that wasn’t discussed in the previous videos and labs.

Overall frustrating