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Learner Reviews & Feedback for Data Visualization with Python by IBM

4.5
stars
11,896 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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1126 - 1150 of 1,872 Reviews for Data Visualization with Python

By joydeep g

Apr 25, 2022

good

By Mandadi S G

Jan 20, 2022

good

By Gang H

Dec 23, 2021

good

By 이재곤

Dec 18, 2021

good

By Dao X H

Jun 24, 2021

good

By Palatip J

Jun 16, 2020

test

By Golla M

Jun 3, 2020

good

By Naveen S P

May 5, 2020

Best

By gomesh n

May 3, 2020

good

By ARIJIT K

Apr 28, 2020

good

By Haowen W

Jan 31, 2020

Good

By Yu M C

Dec 9, 2019

good

By Manea S I

Sep 14, 2019

nice

By Prabhu M

Sep 6, 2019

good

By Nay L

Jul 13, 2019

good

By Aditya J

May 22, 2019

None

By Piotr M

Oct 28, 2018

Nice

By Precious B

Nov 13, 2024

👍

By John R

Jul 9, 2020

o

k

By Talha A

Sep 16, 2019

<3

By Ali C B

Dec 21, 2020

.

By Magic Y

Jul 25, 2019

I

By Manivannan D

Feb 20, 2019

V

By banan A

Jan 11, 2019

H

By Lena G

May 5, 2023

I found a lot of the information given in the course very helpful. It covers basic data visualization techniques and tools, so, as a newbie, I thoroughly enjoyed most of it. One thing that I wasn't particularly happy about is that toward the end of the course it is starting to get quite difficult and therefore takes up a lot more of your time than declared because some things that I (as a beginner) am unfamiliar with are treated as absolutely obvious, like HTML components. You are explained how to use them in Dash, but first you have to find out what they are in the first place by yourself if you are not familiar with HTML at all.

Another thing that bothers me a lot is the final assignment. I believe, the whole point of data analyst's job in data visualization is to provide other people with understandable, ready-to-use information. Yet you find yourself gluing screenshots together and converting them to pdf for a solid half hour in order to present your peers with the info you need them to assess, while you actually already have that necessary dashboard coded and ready. And I am left wondering where I should learn the required skills and what software I should actually use in order to present people with the dashboard I've just learnt to code.

Perhaps it is another level that would allow us to present the dashboard in its actual form and not its screenshot snippets, but it would be nice if the course taught you how to do that and gave you the tools to practice it.