this curious course teaches about tools and techniques for communication with audiences on data science. some tools are very interesting and deserve a deep research from the learner, this course is mostly informative about the potential of such tools.

Tough to get the assignments and everything up and published but a good practical course. I started this course a while ago but life got busy and I had to pull out. There have been changes to the course since then and it has made the course better.

One of the finest courses and specializations on Data Science, It lays the foundations of creating new apps,, doing their documentation and making presentations. Some useful projects will keep you engrossed, and enhance the learning experience.

This course taught me very exciting things and I am looking forward to making shiny apps for my portfolio. It may have been way too easy and quick to finish, though. I barely needed a week. A bigger assignment with leaflet would have been nice.

In terms of practical data science in R, this is the most usefull course in the specialization. Here you can learn a lot about very important R packages such as shiny, MarkDown, leaflet,... Highly recommendable and very, very important.

A very good coverage on creating interactive charts using various facilities such as plotly, google vis, and the shiny app framework. The knowledge is very practical to be used immediately for my day-to-day work.

This was an exceptional course. The assignments and projects were thought provoking. Can we get some assignments/projects linked to this course so that we could apply our learning and earn some money as well?

This course is packed with rich content that draws on all of the data science concepts in the other 8 courses. The best part is leaning how to use Shinyio so it is easy to share R analysis and visualizations.

This is very useful course and I using most of the items especially shiny and slidify, and other tools, I have recommended this course of all my colleages. Now I'm writting my reports with RStudio.

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

A course where you can show everything learned in the R language, especially in visualizations.

I hope and in the future there are courses focused only on visualization with R

Although it is an easy course to pass, it is very important in content. It teaches the finishing moves, the ones you'll need after all your hard work. 5-star without doubt.

Brian Caffo is the best! No one could explain better than him. Congratulations for this excellent course, you are my inspiration to become a better data scientist.

There are some concepts that should be disclosed as pre-requisites for this course. I had to re-sit this course not for the content but for the pre-requisites.

The course not only instroduce me to great resources it also pointed me in the right direction to further develop the skills needed to create data products.

This course helped to get the knowledge how to create shiny apps and r packages. Very usefull, thank you every lecturer and masters how create this course.

Excellent course, well delivered and adapted that help to build a structured output from a statistical analysis. I would recommend this course to anyone.

All that I learned on this course it's totally helpful. I loved this course because I feel that learn a lot of new useful tools that I can use in my work.

It is a very good course. There's quite some work, but the content isn't hard. Make sure you update your RStudio for all the features to work correctly

Out of the other 8 modules, I personally liked this one the most. Here is where you put into practice what you've have learned so far. Great job guys!

It is a good course provide neccessary stuffs for data science.

You can skip week 4 as it is done previously in other courses . Small and good course.

I appreciated the wholistic approach of presenting the information via GIT, R shiney server and making the slides.... all very useful going forward.

It another great lecture in this specialization course. Simplified, understandable, and highly impactful. You'd learn A-Z of shiny app development.

The content is good and exposes to various tools and formats for building data products. Exercises for week 2 and week 3 were very simple though.