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

4.6
stars
1,988 ratings
380 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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351 - 375 of 379 Reviews for Developing Data Products

By Guilherme B D J

Oct 13, 2016

Although I really liked the content of this course, the videos seemed to be have been done with rush. Many of the explanations were started but not finished and the presenter had many breaks during his speech to think or to go back with a better explanation.

By Marco S C

May 23, 2016

This module is not the same level as the previous ones, giving a superficial view of several package but not on any deepens. The application development was the positive part of the module.

By Kevin

Jul 06, 2016

Nice course, but the discussion forum are not the same as in the old format. I also think that the shiny videos from Rstudio are better than the instructional videos in this course.

By Aaron W

Aug 29, 2018

The course is a great survey of tools for sharing data analyses with R. Unfortunately, the content is already a little out-of-date because the technology is always developing.

By Léa F

Feb 19, 2018

This course is clearly not the most interesting of the specialization regarding math/theoretical knowledge, but it helps you get to know a nice way of presenting your results.

By Vaibhav S

Nov 13, 2016

A bit fast paced as they teach so many things in a single week. But the stuff they teach is surely great and makes you appreciate the beauty of R

By Jesse K

Dec 27, 2018

The concept itself was great, but there were numerous issues with the peer review exams, especially around the requirements.

By Shreyas G M

May 03, 2016

This course isn't as clearly outlined or carefully prepared as the others in the Data Visualization specialization.

By Alvaro B C

Jan 18, 2016

I have not received yet my certificated and I can't see it in the list. Is there something wrong?

By Tai C M

Oct 07, 2017

Not bad. But I feel that this topic is more for those who likes to develop web products.

By chris

Oct 19, 2017

Good range of topics - updates to content would be useful --> eg http://jupyter.org

By Vitalii S

Sep 02, 2017

This course can be updated:

1) add swirl lessons.

2) add more video materials

By Aleksey K

Feb 26, 2016

The course is OK, but I'd rather learned app development with Python or Java.

By Diego T B

Nov 07, 2018

Interesting but I had to learn most of the things here by my own

By Michael K

Feb 13, 2016

Lots of material in a short amount of time.

By Martin S

Feb 26, 2016

Updated and entertaining!!

By Vijay B

Feb 08, 2019

Review took too long

By Paul R

Mar 14, 2019

A disappointing end to the pre-capstone lectures, taking the foot off the machine learning gas from course 8 with a detour back to tools and yet another Rmarkdown lecture. This basically covers building shiny apps (needed for the capstone), leaflet (maps), making presentations in RStudio - then gets lost in R Packages and Swirlify which are not very useful here. Some of this is needed in the capstone, but this course can be compressed and combined with earlier courses and make room here for something more substantial at this late stage in the specialization.

By Lucicleyton H d F

Feb 06, 2019

The syllabus is very unbalanced through the weeks. For example the week 01 could be split into two weeks . The week 04, in my view, is unnecessary.

By Stefaan D

Oct 28, 2016

I am a developer and know how to create advanced websites. This course has less use for me as in my day job i create sophisticated websites

By Chuxing C

Apr 07, 2016

Would like to use the time to learn more machine learning/predictive technique, etc.

By Lazar K

Feb 14, 2017

I didn't learn many data science concepts in this class

By Brian F

Aug 20, 2017

This was a fun course, but not particularly useful.

By Seth D

May 23, 2016

seemed like a filler, nit are why this was included

By Chan W Y J

Jan 17, 2018

peer reviewers are spastic mouth breathing idiots.