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Exploratory Data Analysis with Seaborn に戻る

Coursera Project Network による Exploratory Data Analysis with Seaborn の受講者のレビューおよびフィードバック



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....




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.



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.


Exploratory Data Analysis with Seaborn: 51 - 66 / 66 レビュー

by Gilsiley D


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


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 Johan R


I think it would be nice if I could play the video while using jupyter on my computer, it was a bit annoying to use the virtual machine, since if it was not on the page the video stopped

by Rui L


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

by ajinkya a


Understanding Seaborn plots was helpful

by Vishnu N S


GOOD start.. more api could be added

by Anil S


Good Course with clear instructions

by Anirudha S


Thank you. It was great.

by Raj v


Explanations could have been more detailed. Parameters should be explained.

by Nikhil A


Should have used more plots only 5 were there,but it was good

by Andrea C


Good course for beginners, not for intermediate learners

by Amrendra P S


Didn't learn much in this course. Just write the same code as explained in the videos and also the Instructor was not explaining thing in deep. This course I found worthless. It will be better if I had done some other courses rather than devoting my time for this

by Linyu W


Not specific or even systematic. There're supposed to be more function in seaborn usefel for EDA

by Amay S K


No complementary course

by Alireza R


Very basic!

by Fuat A


Not worth the money.