Chevron Left
Zurück zu Developing Data Products

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

4.5
1,783 Bewertungen
338 Bewertungen

Über den Kurs

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-Bewertungen

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

Filtern nach:

251 - 275 of 337 Reviews for Developing Data Products

von Stefan K

Mar 21, 2017

I think this one is the best from the Specialization as it is the most Practical one (more than Practical Machine Learning).

Can be taken without the others if you have basic experience in R and want to learn about cool R applications.

The reason I don't give full rating is for not having practical assignment every week. So there wasn't enough effort put into the course. Of course, we can do optional homework and make more applications, but assignments like these should be mandatory. There is no package building and no swirl course building - So why do we have week 3 and 4 at all? The quizzes are also laughable - no knowledge testing at all.

So although I liked this course from the Specialization the most, I still can't give full rating because of the mentioned issues.

von Lucas

Jun 22, 2016

A very straightforward course on how to build fast and useful applications fora broader audience.

von VenusW

Jan 18, 2017

Really Interesting class, interactive app/plot is so much fun. Great to be able to make creative stuff myself.

von Kristian G W

Feb 02, 2017

I really like the new version of this. It mixes a lot of tools, but most are useful. It was fun doing the assignments.

von David E L B

Jun 05, 2017

Really useful and practical curse.

von Gerrit V

Jul 31, 2017

Great course, I just missed some material on distributing data products as files or objects. Data Science environments are getting connected to traditional BI-environments more and more, now that organisations are getting more used to DS. So it is starting to be important to also deliver data products as files to the e.g. data warehouses, ArcGIS, or open data platforms. I know this is mentioned in Getting and Cleaning Data. But some further elaboration would be nice.

von 朱荣荣

May 08, 2016

The lecture is not so fluent taught than other coursers in the specialization

von PowLook

Dec 03, 2015

This course gives a good introduction on how to develop an application.

It gives all the available tools in the field out for us to try and use them.

The course is enjoyable and not stressful. I find the assignment as meant to get us to do the project and not really there to fail us. It is difficult to fail to course as only the minimum is required.

von Simon

Nov 20, 2017

The course is simple yet useful. With very little knowledge about web development you learn to do some cool stuff.

Well done!

von Ramy H

Jan 28, 2018

Interesting topic, touching on many field. I believe it was quite informative as it applies on the previous modules knowledge into this one. However it didn't touch deeper on each topic.

von Yuriy V

Mar 10, 2016

I liked the course and found it informative, but wish there were more stuff on Shiny Widgets and Input/Output/Render topic. R Shiny tutorial is pretty good, but I was hoping more relevant info about those topics from this course.

von Sreeja R

Feb 14, 2018

This course lacked required information of help to get started. Now thanks to some posts by mentors i was able to successfully complete the Capstone project. Overall a very good experience!

von Angel S

Jan 07, 2016

Interesting course

von Paul A

Nov 13, 2016

Great course, just like the others in the certification.

von Andrew V

May 31, 2017

Good course, but I felt it was a bit easy to get good marks on the assignments with a minimum effort assignment. Some of the ones I marked were very little to do with data-science.

von Fernando M

Sep 04, 2017

Quite hard for a non-specialist but very useful

von Chinmoy D

Jan 02, 2018

good and quite interactive

von Jason M C

May 05, 2016

Compared to the other classes in the JHU Data Science specialization, this one is pretty laid back. It's useful information, and teaches a few nice tricks on how to present data analysis results.

von Robert W S

Dec 16, 2016

Great introduction to interactive plotting, mapping, and shiny. Deeper examples would be helpful.

von MD A

Jun 05, 2017

Would be nice to add some optional references, reading materials or videos covering "Creating Data Products with Python and Python stacks"

von Tushar K

Feb 10, 2017

Excellent course. Got to learn Shiny Application in this.

von Erika G

Aug 22, 2016

I enjoyed the class, but was frustrated when it came time to get my Slidify to work on GitHub (since RPubs wasn't publishing them correctly.) I had to convert it to RPres (which was easy, thankfully) in order to get my project submitted in time.

von Md F A

Oct 09, 2017

Good learning experience. I'd love to see little more detail work assignments.

von Rishabh J

Aug 23, 2017

This was just a quick overview of different technologies out there to help creating various types of interactive graphics in R. But I would have preferred if at least one of those technologies were explored in more detail.

von Fernando S e S

Aug 22, 2016

The skills taught in this course are fantastic and I'm sure using them will blow my colleagues' minds away. However, I must say that the lectures on Rcharts and other interactive plot builders sound kinda sloppy, poorly prepared. I know the documentation for those packages is bad and it takes effort to figure out what they do, but that is precisely why a well-prepared lecture would be so useful. I would also talk about license, since we have been dealing with packages that are completely open for use, but these have some restrictions.