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

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.

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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626 - 650 of 1,861 Reviews for Data Visualization with Python

By Nikhil B

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Sep 27, 2018

Really interesting and challenging for beginners, enjoyed it a lot

By kazim a

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Mar 30, 2021

very good and easy understandable course. Thank you coursera team

By Timothy-Ray H

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Nov 17, 2020

Very tough course but also very well worth the additional effort.

By Natalia M d l V

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Jun 25, 2020

one of the best courses so far in the IBM specialization. thanks!

By Mrinalini S

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Mar 19, 2020

It is a good for learning the basics of Visualization with Python

By Josh H

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Jan 10, 2020

Really informative course on visualization however very beginner!

By Amir K

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Dec 4, 2019

A good course on visualization. many important topics are covered

By hassan s

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Aug 19, 2019

Nice concepts. real need of this course for every data scientist.

By moid h

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Jan 31, 2019

Really Good Course, especially the labs for practicing exercises.

By Nicolas Y

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Dec 28, 2019

Excellent introductory course to data visualization using Python

By Akash V

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Sep 10, 2019

Such a productive and interesting course. Learned a lot from it.

By Vamsi K

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Oct 16, 2018

Some what hard but exciting course related to data visualization

By Aaron Z

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Jun 17, 2020

Great course with easy-to-understand contents from all the labs

By Waruna S

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Mar 8, 2020

Very good course and help apprentices to search web and learn.

By E L (

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Jul 28, 2019

One of the best courses on data visualisation I have ever taken

By Saptashwa B (

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Feb 10, 2019

Fantastic course with some great lab and very good assignment!!

By Vaseekaran V

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Jul 6, 2020

Great course to get introduced to visualizations using Python.

By Rivers L

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Jul 6, 2020

I learnt a lot about the data visualization skills! Thank you!

By Khandoker S I

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Mar 22, 2020

This course helped me a lot to improve my knowledge of python.

By Brett R

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Aug 27, 2019

Great hands on course. Really enjoyed! Big confidence builder.

By Andy L

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Dec 4, 2018

Very useful not only on data science filed, but also any filed

By Priyanka L

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Jul 13, 2018

Great exposure deep knowledge in Data science with simplicity.

By Vishal O

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Jun 26, 2020

Course was very good, wish to have more examples for annotate

By Michael Y

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Jun 22, 2020

The hands on programming exercises were very useful! Thanks.

By Kristin R

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Feb 5, 2020

i took a long break and still managed to come back and finish