Chevron Left
Back to Developing Data Products

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

4.6
stars
2,136 ratings
397 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 3, 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 18, 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

Filter by:

76 - 100 of 397 Reviews for Developing Data Products

By Leandro M

Jan 29, 2017

the course i enjoyed most in this specialization. Learning to use plotly, leaflet and other tools was great

By Benjamin S

Nov 28, 2016

Love this course. Many interesting features (Shiny App, Maps, etc.) that I will definitely use for my job.

By Partha S G

May 7, 2017

I was a good exposure to data products building. Would be great to have something advanced on the topics.

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 Lauren B

Mar 3, 2016

I loved learning how to build a Shiny application. I know this skill will serve me well moving forward.

By Raju G

Dec 10, 2017

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

By Karthik R

Aug 7, 2017

Excellent Introductory course that provides good understanding of how to go about developing products.

By Srikumar G

Dec 25, 2016

very good course to understand on how to present your work in a very structured and repeatable manner.

By Francisco G

Jan 7, 2018

I would dedicate more time to shiny and reduce the time of number of lessons devoted to RMarkdown.

By Jared P

Jun 24, 2017

Loved this course. Would recommend it. I particularly enjoyed learning Leaflet and Shiny Apps.

By Vincent C

Oct 20, 2017

Good course on Data Products, I learned a lot about R Packages, shiny and the leaflet library.

By William R

Jun 12, 2017

Had issues with RStudio and the TA/coursera was great to work with and troubleshoot the issue.

By Giovanni V

Apr 10, 2016

I greatly enjoyed this course. It helped me to improve my skills in the field of data science.

By Avinash K

May 27, 2020

I feel well equipped for presenting statistical results after taking this course. Thank you!

By Evgeniy Z

Apr 12, 2016

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

By Lei S

Jan 3, 2018

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

By Eric S

Jul 23, 2020

Great course. Covers a large range of topics, but is well-paced and easy to follow along.

By Raunak S

Nov 25, 2018

a very good beginner level course for those learning how to develop Data Products in R.

By Laro N P

Aug 15, 2018

Awesome course, maybe more complex examples, but is fine as an introductory program.

By Wei W

Nov 15, 2017

This is by far my favorite course among the 9 courses I took in this specialization.

By Rose G

Mar 31, 2020

All of the content was in the first two weeks, but really interesting nonetheless.

By Saah N T G

Dec 29, 2018

Awesome Lessons!

I learned how to build shiny application and today I'm very happy!

By Henri A

Aug 27, 2020

I enjoyed the course and especially the interaction of the results with Internet.

By Ignacio O

Mar 30, 2020

Its a very nice course to learn the basics on how to prepare an data science app.

By Glener D M

Jun 15, 2019

Indispensable for anyone who wants to make a career in data science. I recommend.