Advanced Data Visualization with R from Coursera

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.

What's inside

Syllabus

Advanced Figures with ggplot2

In this module, we will work through making a number of different figures using ggplot2 and a few additional R packages. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

Spatial Data

In this module, we go through an introduction for making spatial figures (maps) in R. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

Plotly and gganimate

In this module, we will work on animating figures and making them interactive. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches data visualization, which is essential for nearly all jobs today

Builds a strong foundation in data visualization using ggplot2

Develops essential skills in R programming, which is an industry-standard tool

Extends data visualization capabilities by introducing advanced R packages

Prepares learners for advanced data visualization techniques

Lays the groundwork for interactive visualizations and data dashboards

Reviews summary

Advanced data visualization with r

Learners say this well-received course on advanced data visualization with R has engaging assignments and useful lectures. Students report an increase in their R skills thanks to helpful assignments and clear lectures. Those especially interested in GIS and maps may find this specialization especially valuable.

Emphasizes geographic data visualization.

"Excellent introdutiction to advanced data visualization, exceptional for R user without previous experience in GIS and Maps."

"This course is a bit different from others I have done on Coursera. In this instance, the instructor provides a general overview of the topic and then points the student to the broad array of online resources that are out there to assist the learner in developing their understanding of the subject."

"I think this was another excellent course in the specialisation. The emphasis in this course was on introducing a wide range of visualisations so there necessarily was less emphasis on the data wrangling aspects."

Provides clear instruction.

"Collin is great."

"He does a great job explaining and building knowledge in the videos, paired with very useful reading resources."

"I think the lectures are very clearly delivered and the R code provided has useful comments to explain each step."

Enhances R proficiencies.

"My skills have vastly improved in R with this specialization."

"I gain a lot of knowledge and nitty-gritty visualizing using R."

"I think after this course I could return to each of the visualisations introduced and would have a solid foundation to develop each one further for my own requirements."

Provides valuable learning experiences.

"Assignments are well designed."

"Course material was appropriate amount to learn the subject and the projects could be completed in a reasonable amount of time, using the material covered in the course."

"good introduction to some features of ggplot2 that i don't have much experience with, specifically plotly and a couple of mapping packages."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Advanced Data Visualization with R with these activities:

Connect with Experienced Data Visualizers

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Gain valuable insights and guidance by connecting with experienced data visualizers.

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Attend industry events or meetups related to data visualization.
Reach out to professionals in your field via LinkedIn or email.
Ask for advice on your career, projects, or specific data visualization challenges.

Review R programming Basics

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Refresh your R programming skills to ensure you have a strong foundation for this course.

Browse courses on R Programming

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Review the fundamentals of R, including data types, operators, and control flow.
Work through a few basic R programming exercises to refresh your memory.

Review 'ggplot2: Elegant Graphics for Data Analysis'

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Expand your knowledge of ggplot2 by reviewing this comprehensive book.

View Advanced R, Second Edition (Chapman & Hall/CRC... on Amazon

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Read through the first few chapters of the book to get an overview of ggplot2.
Work through the exercises in the book to practice using ggplot2.

Six other activities

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Show all nine activities

Participate in a Study Group with Classmates

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Enhance your understanding of course material and connect with classmates by participating in a study group.

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Find a few classmates who are also taking the course.
Meet up regularly to discuss the course material, work on assignments together, and quiz each other.
Share resources and tips with each other.

Practice Creating Basic Visualizations with ggplot2

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Gain proficiency in creating basic visualizations with ggplot2, which will be essential for this course.

Browse courses on Ggplot2

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Follow along with a tutorial on creating basic visualizations with ggplot2.
Create a few visualizations of your own using ggplot2.
Share your visualizations with a classmate for feedback.

Follow Tutorials on Advanced ggplot2 Techniques

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Enhance your ggplot2 skills by following tutorials on advanced techniques.

Browse courses on Ggplot2

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Find tutorials on advanced ggplot2 techniques, such as creating interactive visualizations or working with spatial data.
Follow along with the tutorials and practice the techniques.
Apply the techniques to your own data visualization projects.

Attend a Data Visualization Workshop

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Supplement your learning with hands-on practice and expert guidance at a data visualization workshop.

Browse courses on Data Visualization

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Research and find a data visualization workshop that aligns with your interests and skill level.
Register for the workshop and attend all sessions.
Actively participate in the exercises and discussions.

Create a Visual Summary of a Research Paper

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Demonstrate your understanding of data visualization by creating a visual summary of a research paper.

Browse courses on Data Visualization

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Choose a research paper that interests you.
Extract the key findings from the paper.
Create a visual representation of the key findings using ggplot2 or another data visualization tool.
Write a brief explanation of your visual summary.

Create an Interactive Data Visualization Dashboard

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Showcase your data visualization skills by creating an interactive dashboard.

Browse courses on Interactive Data Visualization

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Choose a dataset that you are interested in.
Design the layout of your dashboard.
Create the visualizations for your dashboard using Plotly or another tool.
Make your visualizations interactive by adding tooltips, filters, and other features.

Career center

Learners who complete Advanced Data Visualization with R will develop knowledge and skills that may be useful to these careers:

Statistician

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Data Analyst

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Quantitative Analyst

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Data Scientist

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Data Visualization Specialist

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Survey Researcher

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Business Analyst

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Operations Research Analyst

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Data Journalist

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User Experience Designer

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Information Architect

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Product Manager

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Sales Manager

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Marketing Manager

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