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.
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
By Geovanni H M•
Oct 13, 2016
Good course but I think it can be better.
By 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.
Jun 22, 2016
A very straightforward course on how to build fast and useful applications fora broader audience.
Jan 18, 2017
Really Interesting class, interactive app/plot is so much fun. Great to be able to make creative stuff myself.
By 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.
By David E L B•
Jun 05, 2017
Really useful and practical curse.
By 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.
May 08, 2016
The lecture is not so fluent taught than other coursers in the specialization
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.
Nov 20, 2017
The course is simple yet useful. With very little knowledge about web development you learn to do some cool stuff.
By 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.
By 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.
By 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!
By Angel S•
Jan 07, 2016
By Paul A•
Nov 13, 2016
Great course, just like the others in the certification.
By 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.
By Fernando M•
Sep 04, 2017
Quite hard for a non-specialist but very useful
By Chinmoy D•
Jan 02, 2018
good and quite interactive
By 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.
By Robert W S•
Dec 16, 2016
Great introduction to interactive plotting, mapping, and shiny. Deeper examples would be helpful.
By 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"
By Tushar K•
Feb 10, 2017
Excellent course. Got to learn Shiny Application in this.
By 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.
By Md F A•
Oct 09, 2017
Good learning experience. I'd love to see little more detail work assignments.
By 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.