Brief Introduction
Learn about the ggplot2 data visualization package for R, creating map plots with geolocation data using Leaflet, and interactive dashboards to display your work on the web using the R Shiny package!
Description
In this course, you will learn about 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 R data visualization package called Leaflet to create map plots, a unique way to plot data based on geolocation data. Finally, you will learn about 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. Enroll in the course, watch the videos, work through the labs, and then watch your data science skills grow!
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.
Knowledge
- Create basic bar charts, histograms, pie charts, scatter plots, line plots, box plots, and maps using R and related packages, such as ggplot2.
- Customize charts and plots using themes and faceting.
- Create maps using the Leaflet package for R.
- Create interactive dashboards using the Shiny package for R.
Data Visualization Techniques
- 3.3
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Gain hands-on experience in creating effective visualizations This course will focus on building a variety of data visualizations using multiple tools and...
Designing, Running, and Analyzing Experiments
- 3.6
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You may never be sure whether you have an effective user experience until you have tested it with users. Basic Experiment Design Concepts...
Linear Regression and Modeling
- 4.7
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This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable....
Explore Core Data Concepts in Microsoft Azure
- 4.8
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You will identify and describe core data concepts such as relational, non-relational, big data, and analytics, and explore how this technology is implemented with Microsoft Azure....
