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Learner Reviews & Feedback for Data Visualization with Python by IBM

4.5
stars
11,830 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

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.

CJ

Apr 22, 2023

Learnt a lot from this visualization course. The one I found most interesting was making the dashboard. Although sometime the code and indentation are tedious, but this might be useful in the future.

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1426 - 1450 of 1,861 Reviews for Data Visualization with Python

By Sergey Z

•

Apr 25, 2020

Very small course

By Nick V

•

Jul 28, 2023

Great course!!!

By Raj K

•

Jul 9, 2018

Great course :)

By Mohammed A A A

•

May 29, 2022

greate cource

By tanmoy p

•

Dec 16, 2020

good content.

By Ernesto C M P

•

Jan 15, 2022

good course

By Nandivada P E

•

Jun 11, 2020

nice course

By Shailesh Y

•

Aug 13, 2022

excelleant

By nico

•

Nov 18, 2020

Very nice!

By Alex A

•

Oct 14, 2020

Great Job!

By Kausar A

•

Nov 13, 2022

Excellent

By Omer. K

•

Sep 14, 2021

excellent

By Marcin

•

Jul 21, 2020

Too easy

By Jacob J

•

Aug 12, 2019

good job

By Ashutosh S

•

Dec 24, 2022

good

By Venkata T

•

Jun 29, 2020

Good

By SRINIVASULU B

•

Jun 12, 2020

GOOD

By DEVARAMPATI M S A

•

May 27, 2020

good

By Vishal A

•

Apr 20, 2020

good

By KVD S

•

Feb 28, 2020

good

By Veronica S

•

Apr 28, 2019

Good

By Franco M V

•

May 16, 2020

.

By Louis

•

Jan 30, 2020

I have mixed feeling about this course. I think the purpose of this course (visualizing data) and the different ways of doing it is really motivating and awesome, specially when you realize all the things you can do (types of charts , maps etc...). This is actually awesome!

However, on the down sides:

-Each video repeats the steps on how the database used in each course has been "cleaned". I agree with the feedback from other people, reminding us one or two times is fine, but in each video... This is too much!

-I would have liked more practical exercises, specially to plot multiple linear regression models (and polynomial of different degrees, in particular), to display on a chart, and to make predictions. That would be great !

-Labs: they are of unequal difficulty: some are relatively easy to complete, some require more thinking/research and time, while some have no question at all or very little. Maybe it would be useful to re-organize the labs ?...

-Week 3: as everyone mentions, the "artist layer" method is only briefly covered in one of the lab. It would have be really useful to spend more time on it, and on all the things we do with it. Like others, I spent lot of time searching online, and it took me a full afternoon to complete that part of the final assignment !

To summarize: it's a very important and interesting course, but video lessons should be re-recorded with deleting all parts repeating the initial database processing, and adding more topics such as artist layers, etc. Also, maybe split each lab in 2 since there are few labs in this course, but if we follow them correctly, it requires quite few hours to spend on each lab (at least for "beginners" like us starting learning about this topic).

Thank You !

By Justin E

•

Mar 31, 2023

This is an alright course, I wouldn't consider it a bad course. I might be too harsh on the ranking there giving it 3 stars, but there are room for improvements, mainly on week 4.

One of which the lab instructions should be more clear on what to do, I've seen many people have complaints on the labs, primarily on the introduction to dash. This lab specifically has done a subpar job on explaining what to do in my opinion. The lab doesn't make it clear enough that you need to read the instructions before doing anything. If memory serves me right, it is there, but was emphasized enough if that makes any sense. Maybe it isn't that much of a big deal. Anyways, after you got through that one lab, you shouldn't have a hard time with this course.

For the forum replies to the problems that the learners were facing, I don't think it's been all that helpful, no offence to the staffs/mods, but the responses/replies seem rather too vague for confused learners which makes the learners to ask more questions, especially from the Dash introduction lab/Theia Lab in week 4.

I find the videos are great on explaining the tools for data visualization, the quizzes are also good as well.

Anyways, again not a bad course. If anything, it's a decent course.

By Vladimir M

•

Mar 14, 2024

The structure of the course, and topic choice, are great. I have learned a lot in this course. However, the course could benefit from a real person reading the info, or at least a more pleasant robot voice. The course uses a lot of new code that was not covered in previous courses (I'm doing Data Science specialisation, and usually the code builded on the previous knowledge). Moreover, the course is unbalanced, and there is not enough time to practice building dashboards before you try and build one yourself for the finals. And the thing with dashboards is that they work only if you execute the code perfectly with is hardly ever the case. I am extremely motivated, studying every day, always rewriting the code by hand into the textbook, and have received 100% grade for every one of previous 7 courses. And yet, when I was doing the final assignment, it took me five days of studying for 4 hours each, of coding and reading Dash documentation before everything worked as it should, and I wanted to quit many times. I later discovered that lots of other students struggle with this course too.