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Learner Reviews & Feedback for Developing Data Products by Johns Hopkins University

4.6
1,866 ratings
349 reviews

About the Course

A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience....

Top reviews

SS

Mar 04, 2016

This is a great introduction to some of the many ways to present your data. It's probably the easiest course in the specialisation but shows off an impressive array of widgets and gadgets.

RS

Nov 19, 2018

This course was amazing, it could definetly be more deep in each of the subjects, but gives you so much practice in tools that are very useful in the day by day of a data scientist

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76 - 100 of 348 Reviews for Developing Data Products

By FARZAD R

Jul 23, 2017

Very practical and useful course

By Juan A J R

Feb 18, 2016

The course not only instroduce me to great resources it also pointed me in the right direction to further develop the skills needed to create data products.

By Jean P L

Jun 21, 2018

One of the best

By Corey B

Dec 05, 2016

The final project was very cool!

By ooi s m

Jun 11, 2017

interesting course covering plotly, r markdown and shiny. love it

By Evgeniy Z

Apr 12, 2016

Nice introduction which allows to start using some tools to present results of the analysis.

By René S K

Apr 16, 2017

Thanks to these courses, I program production planning and control software for the company I work for.

By David P

Dec 18, 2015

The new platform is very versatile and easy to navigate. The page layout is much more clear. It is easy to navigate from course material to discussion boards.

I like the Quiz format, including expanding the number of choices for the multiple choice selections, but the grading was confusing. For Quiz 3, some questions came back with multiple "Well Done" comments, even when I had not selected the answer for which I was being praised. I also was told I made errors on the same question.... and this was after I answered the question (Question 2, on R generic functions) the exact same as I had answered it when I took the course earlier this year.

I was not a fan of not having to take a picture to submit work, so I am pleased that is no longer a requirement. I hope the typing pattern match is sufficient to affirm identity.

I have one comment on content specific to this class. Week 3 content lacks relevancy to the project and data products in general. I agree that knowledge of R packages, classes, and methods is an important part of understanding R. I am not sure where that fits in the Data Science curriculum as a whole, though. Maybe expanding the curriculum to include a second, more advanced R class, with a project to write our own methods, build an R package, or do something with yhat. That would assign relevant work to reinforce the lectures.

I would be happy to do further beta testing.

DCP

By Lee Y L R

Apr 10, 2018

Interesting! Learn to make interactive apps and slides!

By Romain F

Apr 19, 2017

Great practical course !

By Pablo A

Apr 06, 2017

Excellent, relevant, and updated content and guidance through videos and assignments. If you work hard and use material from previous courses in the specialization you can start to feel how you are getting somewhere. With the technology we learned in this course I feel I can now provide usable products that provide interactivity and promote better understanding of complex data sets.

By Anang H M A

May 03, 2018

Great course!

By Nirav D

Apr 03, 2016

This is a very useful course in the Data Science Specialization that teaches us how to present the results of our data analysis using Shiny, Slidify and other R based data presentation tools. It also introduces open source charting APIs that we could use in our data analysis applications.

By Jair G

Jan 20, 2017

Top 3 course of this specialization.

By Arnav D

Feb 02, 2017

Best coursera course I've taken so far!

By Reinaldo d O M

Jun 05, 2017

Awesome

By Niharika J S

Jan 03, 2017

Great Course

By Christian

Jun 14, 2018

Help

By Telvis C

May 31, 2016

It was a fun course. The final project allows more practice with Shiny.

By Mani K

Mar 17, 2016

Awesome course really enjoyed doing the project.

By Sanjay F

Jul 08, 2017

This was an exceptional course. The assignments and projects were thought provoking. Can we get some assignments/projects linked to this course so that we could apply our learning and earn some money as well?

By Venkatesh

Jul 08, 2017

Interesting ways to use R

By Roberto D

Jun 20, 2017

Great open source tools for conveying results, without a lot of coding.

By Raju G

Dec 11, 2017

Nice to learn making presentations & applications and hosting them on websites to share with the world

By Lei S

Jan 04, 2018

Very interesting course. I spent me a lot of time because I always want to try new things.