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.
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 PL Y•
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.
By Greg A•
Analysis is useless if done for its own sake. Once you have found something interesting the challenge is finding engaging ways to share your insights. This course is a bit scattered since it covers so many different ways of publishing and presenting data, but it is a really nice survey of what is out there.
By Joana P•
I lost myself a little bit, because the materials were a little over the place, we did shiny in the first week lectures and only in the last week the project was about it.
Same with leaflet, I think ti could be structured differently.
But i find them very relevant so that is the reason why I rated it with 4.
By Kim K•
You will need to be familiar with the subject in order to keep up with the assignments or put in a large amount of time to learn. The forums are helpful and other students are great. Visit the shinyapps.io website for Shiny Apps and slidify research. Rigorous and rewarding when you put the work in.
By Raul M•
It is a nice class but many of the topic were already covered on previous class of the specialization. If this is the only class you will take, it is okay but it you are taking the whole specialization this is like doing few (not all) things again
By Matthew C•
Good course, but it was a little light on content. Probably the easiest month of the specialization aside from the first one. The assignments were too easy too pass. Good intro to some very interesting packages (leaflet, shiny, google vis) though.
By Erika G•
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 Yuriy V•
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 Rishabh J•
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.
By Daniel J R•
This class includes a lot of introductory content an a good measure of hands-on practice. It also provides a great amount of resources and reference material for the learners to expand their knowledge further.
By VIPULKUMAR P•
Nice course and good classmates. It's very focus oriented and gives very good idea of Shiny, Rmarkdown, plotly and how to publish documents on github, Rpubs and other online sites. I learnt power of R
By Jason M C•
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 Sreeja R•
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 Ramy H•
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 Jeffrey E T•
Good overview of available tools. Lack of practice exercises makes preparing for quizzes difficult. However, the course project does a good job to get your feet wet with Shiny Apps.
By Andrew V•
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 Iain L•
Interesting, practical course. Gives a broad overview of R Markdown, Shiny, interactive plots (Gvis/Plotly), incorporating maps via Leaflet and creating your own training courses.
By Luiz E B J•
The content is very interesting, brings a lot of knowledge to develop good presentation and analysis. Could me more focused in just one option to go further an deep. Recomend!
By Johnny C•
I have learned a lot. The course is simple and very useful. Maybe the assignments should improve because the directions are a bit vague, but in general I liked it.
By Julian J•
Although all coursera courses are same, the peer assessment is very useful for this course. It's very helpful to see products made by other people.
By MD A•
Would be nice to add some optional references, reading materials or videos covering "Creating Data Products with Python and Python stacks"
By Rafael M•
Excelente curso, 4 estrellas debido a que las instrucciones para revisión no son tan claras y los compañeros revisan de forma subjetiva.
By Johan J•
Awesome course. Overview of all the things you need to become part of the data science community in terms of contributing and sharing.
By Jorge L•
Excellent content. I was expecting more examples related to the industry, such as data products for data journals, telcos, etc.
By Federico G•
Really good course, but for the time invested I think they could have gone a bit deeper in some areas. I enjoyed it though :)