SS
The course was good and the videos explained the topic very well and the content was indeed very nice..thanks for providing such a good course

In this course, you will learn the Grammar of Graphics, a system for describing and building graphs, and how the ggplot2 data visualization package for R applies this concept to basic bar charts, histograms, pie charts, scatter plots, line plots, and box plots. You will also learn how to further customize your charts and plots using themes and other techniques. You will then learn how to use another data visualization package for R called Leaflet to create map plots, a unique way to plot data based on geolocation data. Finally, you will be introduced to creating interactive dashboards using the R Shiny package. You will learn how to create and customize Shiny apps, alter the appearance of the apps by adding HTML and image components, and deploy your interactive data apps on the web. You will practice what you learn and build hands-on experience by completing labs in each module and a final project at the end of the course. Watch the videos, work through the labs, and watch your data science skill grow. Good luck! NOTE: This course requires knowledge of working with R and data. If you do not have these skills, it is highly recommended that you first take the Introduction to R Programming for Data Science as well as the Data Analysis with R courses from IBM prior to starting this course. Note: The pre-requisite for this course is basic R programming skills.

SS
The course was good and the videos explained the topic very well and the content was indeed very nice..thanks for providing such a good course
SS
great i learned alot and practice many things in a different way,thanks coursera
JK
Good course skills training and application introduction, applied sciences.
AO
Great content. However, i think the labs should be more detailed
TS
high efficieny course which provide knowlegde about the course .
SK
It is an amazing course. But you should know the basics of the Rstudio and it's layout.
CW
The material is presented in "pieces" that are too large. There is a basic understanding of R that needs to be built prior to using the visualization tools.