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Dr. Aihua Li
In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp. DSCI 605 Data visualization serves as the foundation for understanding principles, concepts, techniques, and tools used to visualize information in large, intricate data sets. It also provides hands-on experience in visualizing big data using the open-source software R. Through the course, students will learn to evaluate the effectiveness of visualization designs and think critically about decisions, such as color choice and visual encoding. Additionally, students will create their own data visualizations and become proficient in using R.
Read more
In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp. DSCI 605 Data visualization serves as the foundation for understanding principles, concepts, techniques, and tools used to visualize information in large, intricate data sets. It also provides hands-on experience in visualizing big data using the open-source software R. Through the course, students will learn to evaluate the effectiveness of visualization designs and think critically about decisions, such as color choice and visual encoding. Additionally, students will create their own data visualizations and become proficient in using R.
Read more
In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp. DSCI 605 Data visualization serves as the foundation for understanding principles, concepts, techniques, and tools used to visualize information in large, intricate data sets. It also provides hands-on experience in visualizing big data using the open-source software R. Through the course, students will learn to evaluate the effectiveness of visualization designs and think critically about decisions, such as color choice and visual encoding. Additionally, students will create their own data visualizations and become proficient in using R.
The course comprises four sections. The first section caters to learners with minimal or no experience in R, establishing the groundwork for data visualization with R. The second section introduces preliminary data visualization techniques, allowing students to gain hands-on experience with common visualization practices for Exploratory Data Analysis (EDA) using ggplot2. This section emphasizes data exploration before delving into advanced data mining. The third section builds upon existing data visualization skills by delving into advanced data visualization topics, including interactive data visualization, time series plotting, and spatial mapping.
The primary objective of the first three sections is to equip students with a well-developed set of skills, enabling them to create a wide range of visualizations in R. The final section focuses on completing a final project, where students apply the skills, theory, and experiences gained from the previous sections. The project entails developing a data visualization that effectively communicates a compelling story to the audience and readers.
Register for this course and see more details by visiting:
OpenCourser.com/course/08uarv/data
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What's inside
Syllabus
Introduction to Data Visualization and Getting Started with R
In the first module, we will learn what is data visualization, why data visualization is necessary in data science field, what data visualization will do and what skills data visualization need. We will first get started with R by learning R basic and R Markdown to prepare the data visualization in the course.
Read more
Syllabus
Introduction to Data Visualization and Getting Started with R
In the first module, we will learn what is data visualization, why data visualization is necessary in data science field, what data visualization will do and what skills data visualization need. We will first get started with R by learning R basic and R Markdown to prepare the data visualization in the course.
Read more
Graphics Components for Data Visualization
Understanding the elements and components of data visualization is essential for data visualization because it provides a systematic framework for creating effective and meaningful visual representations of data.In this module, we will explore the grammar of graphics, explain some rational, and introduce principles in data visualization, as well as describe the common Exploratory Data Analysis (EDA) idioms' features and applications.
ggplot2
Let's get our hands wet with real data visualization-producing a graph. In this module, we will explore the powerful data visualization package ggplot2. In this module, you will learn basic usages of ggplot() function, the fill and color aesthetics, and learn to create a histogram using ggplot() and setting suitable bin numbers or bin width.
Embed Images and Tables in R Markdown Files
Now you have conducted the basic data wrangling, documented your work in R Markdown, and created your first data visualization in previous modules. In this module, you will learn to embed, create and refer to images and tables in R Markdown. In addition, you will learn to produce scatter plots, which further enrich your visualization experience and enhance your visualization skills.
Boxplot and Multiple-view Layout
This module will continue for one of the common EDA idioms-box plots to enrich your data visualization experience and will explore new technique-layout multiple plots on one page. In this module, you will learn to produce boxplots using ggplot(), interpret boxplots and arrange multiple plots on one page.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a foundational understanding of data visualization in the age of big data
Utilizes the open-source software R for hands-on experience in visualizing big data
Focuses on evaluating and critically interpreting data visualizations
Suitable for learners with minimal or no experience in R
Provides a comprehensive overview of data visualization principles, concepts, techniques, and tools
Culminates in a final project where students apply their skills to create a compelling data visualization
Save this course
Save Data Visualization to your list so you can find it easily later:
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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 Data Visualization with these
activities:
Review the basics of R
Show steps
Familiarize yourself with the R programming language, which is essential for data visualization in this course.
Browse courses on
R
Show steps
-
Review basic R syntax and data structures
-
Practice loading, manipulating, and summarizing data in R
-
Create basic plots using the plot() function
Review past course materials on data visualization principles
Show steps
Solidify your understanding of data visualization fundamentals.
Browse courses on
Data Visualization
Show steps
-
Review lecture notes and course materials
-
Complete practice exercises or quizzes
Review basic R programming concepts
Show steps
Refresh your understanding of essential R programming skills for data analysis.
Browse courses on
R Programming
Show steps
-
Review the RStudio interface and basic syntax
-
Practice data import, cleaning, and transformation techniques
16 other activities
Expand to see all activities and additional details
Show all 19 activities
Create a boxplot using ggplot2
Show steps
Develop proficiency in using ggplot2 to visualize data effectively.
Browse courses on
Data Visualization
Show steps
-
Load a dataset into R
-
Use the ggplot() function to create a boxplot
-
Add labels, title, and axes to the plot
Explore the ggplot2 package
Show steps
Gain hands-on experience with ggplot2, a powerful R package for creating visually appealing and informative data visualizations.
Browse courses on
Ggplot2
Show steps
-
Follow tutorials on ggplot2's grammar of graphics
-
Create different types of plots using ggplot2, such as histograms, scatterplots, and bar charts
-
Customize and enhance ggplot2 visualizations
Participate in a peer discussion group
Show steps
Participate in a peer discussion group to share your knowledge, learn from others, and get feedback on your data visualizations.
Browse courses on
Data Visualization
Show steps
-
Join a peer discussion group focused on data visualization.
-
Participate regularly in discussions and share your insights.
-
Provide feedback and critique to other group members.
Read 'Data Science for Business'
Show steps
Gain foundational knowledge of data science concepts and their application in business contexts.
View
Data Science for Business
on Amazon
Show steps
-
Read chapters 1-3 to understand the basics of data science
-
Complete the exercises in chapter 2 to practice data manipulation
-
Read chapter 4 to learn about data visualization techniques
Present and discuss data visualizations with peers
Show steps
Engage in peer-to-peer learning by presenting and discussing your data visualizations, gaining valuable feedback and insights from others.
Browse courses on
Data Visualization
Show steps
-
Prepare a brief presentation on your data visualization
-
Present your visualization to a group of peers
-
Lead a discussion on the visualization's effectiveness and potential improvements
Practice creating data visualizations in R
Show steps
Practice creating data visualizations in R to reinforce your understanding of the techniques and tools covered in the course.
Browse courses on
Data Visualization
Show steps
-
Load a dataset into R.
-
Create a scatter plot of two variables.
-
Create a bar chart of a categorical variable.
-
Create a histogram of a continuous variable.
Create a scatter plot using ggplot2
Show steps
Strengthen your data visualization skills by practicing with a specific technique.
Browse courses on
Data Visualization
Show steps
-
Load a dataset into R
-
Use the ggplot() function to create a scatter plot
-
Add labels, title, and axes to the plot
Follow a tutorial on advanced data visualization techniques
Show steps
Follow a tutorial on advanced data visualization techniques to expand your knowledge and skills beyond the basics covered in the course.
Browse courses on
Data Visualization
Show steps
-
Find a tutorial on a specific advanced data visualization technique.
-
Follow the steps in the tutorial to create a data visualization.
-
Interpret and analyze the data visualization.
Attend a workshop on data visualization
Show steps
Gain hands-on experience and learn best practices from industry experts.
Browse courses on
Data Visualization
Show steps
-
Identify and register for a relevant workshop
-
Attend the workshop and actively participate in discussions
-
Apply the techniques learned to your own projects
Participate in a data visualization competition
Show steps
Challenge yourself to solve real-world data visualization problems and showcase your skills.
Browse courses on
Data Visualization
Show steps
-
Identify and register for a suitable competition
-
Gather and explore the provided dataset
-
Develop and refine your data visualization solutions
-
Submit your visualizations and compete with others
Create data visualizations for real-world datasets
Show steps
Apply your skills to create meaningful visualizations for real-world datasets, helping you solidify your understanding and develop practical expertise.
Browse courses on
Data Visualization
Show steps
-
Find interesting datasets online or use provided datasets
-
Explore and analyze the data to identify key insights
-
Design and create data visualizations to communicate these insights
Contribute to an open-source data visualization project
Show steps
Contribute to an open-source data visualization project to gain experience working on real-world data visualization projects and to give back to the community.
Browse courses on
Data Visualization
Show steps
-
Find an open-source data visualization project to contribute to.
-
Identify a bug or feature to work on.
-
Implement your fix or feature and submit a pull request.
Create a data visualization dashboard
Show steps
Create a data visualization dashboard to demonstrate your ability to communicate insights from data effectively.
Browse courses on
Data Visualization
Show steps
-
Identify a dataset and a set of questions to answer.
-
Create a storyboard for your dashboard.
-
Develop and refine your data visualizations.
-
Assemble your dashboard and write a narrative.
Develop a data visualization dashboard for a business scenario
Show steps
Apply your data visualization skills to create a practical tool for business decision-making.
Browse courses on
Data Visualization
Show steps
-
Define the business use case and data requirements
-
Design the dashboard layout and select appropriate visualizations
-
Implement the dashboard using R and ggplot2
-
Validate the dashboard with stakeholders and gather feedback
Develop a data visualization dashboard
Show steps
Create a comprehensive data visualization dashboard that effectively communicates key insights from a dataset, showcasing your ability to present data in an engaging and informative way.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and identify the key insights you want to communicate
-
Design the layout and structure of the dashboard
-
Develop interactive visualizations using ggplot2 and R Shiny
-
Test and refine the dashboard for usability and effectiveness
Participate as a mentor in a data science community
Show steps
Reinforce your understanding by helping others learn and apply data science concepts.
Browse courses on
Mentoring
Show steps
-
Join a data science community or forum
-
Offer to help others with questions or challenges
-
Share your knowledge and experiences to support their learning
Review the basics of R
Show steps
Familiarize yourself with the R programming language, which is essential for data visualization in this course.
Browse courses on
R
Show steps
Show steps
Show steps
- Review basic R syntax and data structures
- Practice loading, manipulating, and summarizing data in R
- Create basic plots using the plot() function
Review past course materials on data visualization principles
Show steps
Solidify your understanding of data visualization fundamentals.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Review lecture notes and course materials
- Complete practice exercises or quizzes
Review basic R programming concepts
Show steps
Refresh your understanding of essential R programming skills for data analysis.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Review the RStudio interface and basic syntax
- Practice data import, cleaning, and transformation techniques
16 other activities
Expand to see all activities and additional details
Show all 19 activities
Create a boxplot using ggplot2
Show steps
Develop proficiency in using ggplot2 to visualize data effectively.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Load a dataset into R
- Use the ggplot() function to create a boxplot
- Add labels, title, and axes to the plot
Explore the ggplot2 package
Show steps
Gain hands-on experience with ggplot2, a powerful R package for creating visually appealing and informative data visualizations.
Browse courses on
Ggplot2
Show steps
Show steps
Show steps
- Follow tutorials on ggplot2's grammar of graphics
- Create different types of plots using ggplot2, such as histograms, scatterplots, and bar charts
- Customize and enhance ggplot2 visualizations
Participate in a peer discussion group
Show steps
Participate in a peer discussion group to share your knowledge, learn from others, and get feedback on your data visualizations.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Join a peer discussion group focused on data visualization.
- Participate regularly in discussions and share your insights.
- Provide feedback and critique to other group members.
Read 'Data Science for Business'
Show steps
Gain foundational knowledge of data science concepts and their application in business contexts.
View
Data Science for Business
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 to understand the basics of data science
- Complete the exercises in chapter 2 to practice data manipulation
- Read chapter 4 to learn about data visualization techniques
Present and discuss data visualizations with peers
Show steps
Engage in peer-to-peer learning by presenting and discussing your data visualizations, gaining valuable feedback and insights from others.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Prepare a brief presentation on your data visualization
- Present your visualization to a group of peers
- Lead a discussion on the visualization's effectiveness and potential improvements
Practice creating data visualizations in R
Show steps
Practice creating data visualizations in R to reinforce your understanding of the techniques and tools covered in the course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Load a dataset into R.
- Create a scatter plot of two variables.
- Create a bar chart of a categorical variable.
- Create a histogram of a continuous variable.
Create a scatter plot using ggplot2
Show steps
Strengthen your data visualization skills by practicing with a specific technique.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Load a dataset into R
- Use the ggplot() function to create a scatter plot
- Add labels, title, and axes to the plot
Follow a tutorial on advanced data visualization techniques
Show steps
Follow a tutorial on advanced data visualization techniques to expand your knowledge and skills beyond the basics covered in the course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find a tutorial on a specific advanced data visualization technique.
- Follow the steps in the tutorial to create a data visualization.
- Interpret and analyze the data visualization.
Attend a workshop on data visualization
Show steps
Gain hands-on experience and learn best practices from industry experts.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify and register for a relevant workshop
- Attend the workshop and actively participate in discussions
- Apply the techniques learned to your own projects
Participate in a data visualization competition
Show steps
Challenge yourself to solve real-world data visualization problems and showcase your skills.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify and register for a suitable competition
- Gather and explore the provided dataset
- Develop and refine your data visualization solutions
- Submit your visualizations and compete with others
Create data visualizations for real-world datasets
Show steps
Apply your skills to create meaningful visualizations for real-world datasets, helping you solidify your understanding and develop practical expertise.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find interesting datasets online or use provided datasets
- Explore and analyze the data to identify key insights
- Design and create data visualizations to communicate these insights
Contribute to an open-source data visualization project
Show steps
Contribute to an open-source data visualization project to gain experience working on real-world data visualization projects and to give back to the community.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find an open-source data visualization project to contribute to.
- Identify a bug or feature to work on.
- Implement your fix or feature and submit a pull request.
Create a data visualization dashboard
Show steps
Create a data visualization dashboard to demonstrate your ability to communicate insights from data effectively.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify a dataset and a set of questions to answer.
- Create a storyboard for your dashboard.
- Develop and refine your data visualizations.
- Assemble your dashboard and write a narrative.
Develop a data visualization dashboard for a business scenario
Show steps
Apply your data visualization skills to create a practical tool for business decision-making.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Define the business use case and data requirements
- Design the dashboard layout and select appropriate visualizations
- Implement the dashboard using R and ggplot2
- Validate the dashboard with stakeholders and gather feedback
Develop a data visualization dashboard
Show steps
Create a comprehensive data visualization dashboard that effectively communicates key insights from a dataset, showcasing your ability to present data in an engaging and informative way.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and identify the key insights you want to communicate
- Design the layout and structure of the dashboard
- Develop interactive visualizations using ggplot2 and R Shiny
- Test and refine the dashboard for usability and effectiveness
Participate as a mentor in a data science community
Show steps
Reinforce your understanding by helping others learn and apply data science concepts.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Join a data science community or forum
- Offer to help others with questions or challenges
- Share your knowledge and experiences to support their learning
Career center
Learners who complete Data Visualization will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use data to solve problems and make informed decisions. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Data Analyst.
Data Scientist
Data Scientist
Data Scientists use their knowledge of data analysis and visualization to extract meaningful insights from large datasets. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Data Scientist.
Business Analyst
Business Analyst
Business Analysts use data to improve the efficiency and effectiveness of businesses. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Business Analyst.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Statistician.
Research Analyst
Research Analyst
Research Analysts use data to identify trends and make predictions. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Research Analyst.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze the financial performance of companies and make investment recommendations. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Financial Analyst.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency and effectiveness of business operations. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as an Operations Research Analyst.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand consumer behavior and develop marketing campaigns. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Marketing Analyst.
Interaction Designer
Interaction Designer
Interaction Designers create user interfaces for websites and other digital products. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as an Interaction Designer.
User Experience Researcher
User Experience Researcher
User Experience Researchers use data to understand how users interact with products and services. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a User Experience Researcher.
Information Architect
Information Architect
Information Architects design and organize websites and other digital products. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as an Information Architect.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visual representations of data. They work in a variety of industries, including technology, finance, healthcare, and retail. This course would be a great way to learn the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course will be essential for success as a Data Visualization Specialist.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work in a variety of industries, including technology, finance, healthcare, and retail. This course may be useful for learning the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course may be helpful for success as a Software Engineer.
Web Developer
Web Developer
Web Developers create and maintain websites. They work in a variety of industries, including technology, finance, healthcare, and retail. This course may be useful for learning the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course may be helpful for success as a Web Developer.
Graphic designer
Graphic designer
Graphic Designers create visual content for websites, print, and other media. They work in a variety of industries, including technology, finance, healthcare, and retail. This course may be useful for learning the basics of data visualization and how to use the R programming language to analyze data. The skills you learn in this course may be helpful for success as a Graphic Designer.
For more career information including salaries, visit:
OpenCourser.com/course/08uarv/data
Reading list
We've selected 18 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Visualization.
Save
This classic book on data visualization provides a comprehensive overview of the principles and techniques of effective data visualization. It must-read for anyone who wants to learn how to create clear and informative visualizations.
Comprehensive guide to the ggplot2 package, which is one of the most popular data visualization libraries in R. It provides a step-by-step guide to creating a wide variety of visualizations, from simple plots to complex dashboards.
Provides a comprehensive overview of the field of information visualization. It covers the different theories and techniques used to create effective visualizations, as well as how to evaluate the effectiveness of visualizations.
Save
Provides a comprehensive overview of the design principles and best practices for data visualization.
Provides a comprehensive guide to the design and development of data science projects, including a chapter on data visualization.
Provides a comprehensive guide to creating interactive data visualizations for the web. It covers the different types of interactive visualizations, as well as how to use them effectively to engage users.
Save
Provides a collection of essays and examples that illustrate the power of data visualization in storytelling and decision-making.
This practical guide focuses on creating effective data visualizations using common software such as Excel, PowerPoint, and Tableau.
Save
Provides a comprehensive overview of the principles of data visualization. It covers the different types of charts and graphs, as well as how to use them effectively to communicate data.
Save
Provides a comprehensive introduction to R, a programming language that is widely used for data science. It covers the basics of R, as well as more advanced topics such as data visualization, machine learning, and statistical modeling.
Provides a comprehensive overview of the principles of visual communication. It covers the different elements of visual design, as well as how to use them effectively to create clear and informative visualizations.
Save
Provides a comprehensive overview of the field of data visualization. It covers the different theories and techniques used to create effective visualizations, as well as how to evaluate the effectiveness of visualizations.
Save
While not specifically about data visualization, this book provides valuable insights into the art of presenting information effectively.
Save
Provides a collection of essays on data visualization. It covers a wide range of topics, from the history of data visualization to the latest trends in the field.
Save
Provides practical guidance on how to create effective data visualizations. It covers the different types of charts and graphs, as well as how to use them effectively to communicate data.
Provides practical guidance on how to use data visualization to tell stories and communicate data effectively. It covers the different types of data visualizations, as well as how to use them effectively to engage audiences.
Provides practical guidance on how to choose the right chart for every data story. It covers the different types of charts and graphs, as well as how to use them effectively to communicate data.
This beginner-friendly book provides a gentle introduction to data visualization concepts and techniques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/08uarv/data
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Mastering Data Visualization with R
Level
Intermediate
Via
Coursera
Institution
Ball State University
Instructor
Dr. Aihua Li
Language
English
Good to know
Provides a foundational understanding of data visualization in the age of big data
Utilizes the open-source software R for hands-on experience in visualizing big data
Focuses on evaluating and critically interpreting data visualizations
Suitable for learners with minimal or no experience in R
Provides a comprehensive overview of data visualization principles, concepts, techniques, and tools
Culminates in a final project where students apply their skills to create a compelling data visualization
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