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Learner Reviews & Feedback for Data Visualization with Python by IBM

4.5
stars
11,512 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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1301 - 1325 of 1,797 Reviews for Data Visualization with Python

By Brijesh O

May 10, 2020

Need more methodic explanations on the key functions and parameters , kwarg

By Gustavo P F d X

Mar 23, 2020

There are some problems with the labs according to installation required.

By Prashant S

Apr 4, 2019

The last section of advance Visualization lab could have been more better

By LAURA T G

Feb 17, 2020

Mmany mistakes that make the studentsd work and stress more tan required

By ARCHANENDRA S

Dec 6, 2019

Excellent study material and brief description of visualization concepts

By Apurv T

Jul 30, 2020

the spatial analysis is new to me and want more detailed study chapters

By Diego A P

Dec 6, 2020

A broad range of visualizations explained fast and straightforward.

By Alvaro F

Mar 18, 2019

It would be good to make another section only for seaborn or bokeh

By anish k

Aug 20, 2020

Good enough to learn basic skills of data visualization library.

By Carlos A

May 6, 2020

Felt like there could be more information in the last week lab.

By Kang R K

Nov 5, 2019

short course but learn useful python package Folium efficiently

By Sai Y

Jan 23, 2023

Overall Best Course to learn . Needed in more indepth concepts

By Mohit S C

Mar 10, 2022

This course is so much benifical for me to visualize the data.

By William O

Apr 28, 2020

Thanks for the content of this course. I really learned a lot.

By Nicolás G S I

Jul 31, 2019

The final assignment is not too clear.Question 2 specifically.

By Serdar M

Nov 25, 2018

more explanation on functions' and methods' parameters needed

By kolluru s

May 4, 2023

Fantastic course ! still there is delay in receiving a badge

By Frank H

Feb 6, 2020

Some new packages i've never seen. Map one was really cool.

By Hong W

May 13, 2020

Good course to learn basic knowledge of data visualization

By Kevin D

Sep 26, 2019

first of the courses where things weren't spoonfed to you.

By Greg G

Jul 6, 2019

An interesting course with a number of practical examples

By Nath S

Apr 15, 2022

Really helped me to understand diferent types of graphs.

By Ahmad S

Jul 30, 2020

Very good course but need more examples and explanations

By aloke d G

Sep 24, 2019

Good insights into various plotting methods and library.

By Ankit K S

Feb 13, 2020

Very wisely chosen content of ungraded lab assignments