Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Data Visualization & Dashboarding with R Specialization [5 courses] (Johns Hopkins)

Specialization - 5 course series

Getting Started with Data Visualization in R

Course 111 hours4.7 (296 ratings)View course

What you'll learn

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.

To fill that need, this course is intended for learners who have little or no experience with R but who are looking for an introduction to this tool. By the end of this course, students will be able to import data into R, manipulate that data using tools from the popular tidyverse package, and make simple reports using R Markdown. The course is designed for students with good basic computing skills, but limited if any experience with programming.

Skills you'll gain

R Programming, Tidyverse (R Package), Data Manipulation, Data Wrangling, Data Import/Export, Histogram, Scatter Plots, Ggplot2, Statistical Visualization, Data Visualization, Data Visualization Software, Rmarkdown, and Statistical Reporting

Data Visualization in R with ggplot2

Course 212 hours4.9 (129 ratings)View course

What you'll learn

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.

This course is the second in a specialization in Data Visualization offered by Johns Hopkins. It is intended for learners who have either have some experience with R and data wrangling in the tidyverse or have taken the previous course in the specialization. The focus in this course learning to use ggplot2 to make a variety of visualizations and to polish those visualizations using tools within ggplot as well as vector graphics editing software. The course will not go into detail about how the data management works behind the scenes.

Skills you'll gain

Plot (Graphics), Data Visualization Software, Ggplot2, Heat Maps, R Programming, Scatter Plots, Graphics Software, Data Wrangling, Tidyverse (R Package), Data Visualization, and Graphical Tools

Advanced Data Visualization with R

Course 310 hours4.9 (79 ratings)View course

What you'll learn

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.

This course is the third in the Specialization "Data Visualization and Dashboarding in R." Learners come into this course with a foundation using R to make many basic kinds of visualization, primarily with the ggplot2 package. Accordingly, this course focuses on expanding the learners' inventory of data visualization options. Drawing on additional packages to supplement ggplot2, learners will made more variants of traditional figures, as well as venture into spatial data. The course ends make interactive and animated figures. To fill that need, this course is intended for learners who have little or no experience with R but who are looking for an introduction to this tool. By the end of this course, students will be able to import data into R, manipulate that data using tools from the popular tidyverse package, and make simple reports using R Markdown. The course is designed for students with good basic computing skills, but limited if any experience with programming.

Skills you'll gain

Plotly, Statistical Visualization, Scatter Plots, Tidyverse (R Package), Geospatial Information and Technology, Animations, Interactive Data Visualization, Rmarkdown, Spatial Data Analysis, Data Mapping, Ggplot2, R Programming, Data Manipulation, and Data Visualization Software

Publishing Visualizations in R with Shiny and flexdashboard

Course 411 hours4.9 (70 ratings)View course

What you'll learn

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.

Skills you'll gain

Data Presentation, User Interface (UI), UI Components, Interactive Data Visualization, Application Deployment, Dashboard, Shiny (R Package), Ggplot2, Data Visualization Software, Application Development, and Statistical Visualization

Data Visualization Capstone

Course 521 hours5.0 (34 ratings)View course

What you'll learn

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.

This is the final course in the Specialization "Data Visualization and Dashboarding in R." Learners in this course will enter with a well-developed set of skills making a wide variety of visualizations in R. The focus on this course will applying those skills to a unique project, drawing on publicly available data to tell a compelling story using the data visualization toolkit assembled in the previous courses.

Skills you'll gain

Statistical Visualization, Statistical Reporting, Graphing, Data Visualization, R Programming, Data Wrangling, Data Visualization Software, Rmarkdown, Data Transformation, Data Analysis, Data Manipulation, Data Import/Export, Data Storytelling, Data Cleansing, Tidyverse (R Package), Data Literacy, Storyboarding, and Ggplot2