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Learner Reviews & Feedback for Exploratory Data Analysis with Seaborn by Coursera Project Network

332 ratings
56 reviews

About the Course

Producing visualizations is an important first step in exploring and analyzing real-world data sets. As such, visualization is an indispensable method in any data scientist's toolbox. It is also a powerful tool to identify problems in analyses and for illustrating results.In this project-based course, we will employ the statistical data visualization library, Seaborn, to discover and explore the relationships in the Breast Cancer Wisconsin (Diagnostic) Data Set. We will cover key concepts in exploratory data analysis (EDA) using visualizations to identify and interpret inherent relationships in the data set, produce various chart types including histograms, violin plots, box plots, joint plots, pair grids, and heatmaps, customize plot aesthetics and apply faceting methods to visualize higher dimensional data. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Top reviews

Sep 7, 2020

This project is great for people go want to advances her career exploring new viz techniques. The instructor is great, clear and easy to follow. I will definitely recommend to take this project.

Oct 3, 2020

As a beginner, this was a very good insight into EDA for me. You will however, have to read the documentation and more articles to go in-depth. However, this is a very good introductory course.

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26 - 50 of 56 Reviews for Exploratory Data Analysis with Seaborn

By Shubham K K

Sep 17, 2020

Nice course telling the basic functionality of data visualization with python .

By Adolf Y M

Oct 10, 2020

all is explained very well so i can get a good understanding of EDA

By Minhaj A A

Jun 1, 2020

Good project to practice your visualisation skills using seaborn

By Marwa A E

Jun 13, 2020

More than perfect course, amazing and simple. Thank you :)


Jul 28, 2020

An easy to understand project with good explanation.

By c s s

Jun 8, 2020

this was a beautiful learning experience!

thank you !

By Cheikh B

Jul 14, 2020

very helpfull project to learn easier seaborn

By Dr. A B

Sep 19, 2020

Good instructions for absolute beginners

By Serafeim L

Oct 1, 2020

Great overview of EDA with Seaborn

By Hitesh J

Jul 19, 2020

optimal course for beginner


May 30, 2020

Hands on was very useful

By Gangone R

Jun 28, 2020

very useful course

By Asha N

Jun 28, 2020

It was helpful


Jun 2, 2020

Very Helpful !

By Sachin

Oct 26, 2020


By Jitin S

Sep 8, 2020


By Deepak K

Nov 1, 2020

Thank You


May 24, 2020

Good one

By tale p

Jun 17, 2020


By Abhishek P G

Jun 14, 2020


By Gilsiley D

Aug 3, 2020

A basic course. For me show a good idea about exploratory data analysis and some important insights about using some graphics like violin, swarm and heatmap. I felt absence a conclusion, like show a final features can be selected.

By Divya R

Jun 30, 2020

I find this project a way better means to explore data analysis than the month long courses. This was a good quick refresher for me. Beautiful project, i hope to see many such more projects from the Mentor!

By Rui L

May 19, 2020

A good tutorial for starters in Data Science. All knowledge taught in it is some basic.

By Vishnu N S

Dec 9, 2020

GOOD start.. more api could be added

By Anil S

May 30, 2020

Good Course with clear instructions