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Enrico Bertini
and
Cristian Felix
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on information visualization and to design and develop advanced applications for visual data analysis.
This course aims at...
Read more
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on information visualization and to design and develop advanced applications for visual data analysis.
This course aims at...
Read more
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on information visualization and to design and develop advanced applications for visual data analysis.
This course aims at introducing fundamental knowledge for information visualization. The main goal is to provide the students with the necessary “vocabulary” to describe visualizations in a way that helps them reason about what designs are appropriate for a given problem. This module also gives a broad overview of the field of visualization, introducing its goals, methods and applications.
A learner with some or no previous knowledge in Information Visualization will get a sense of what visualization is, what it is for and in how many different situations it can be applied; will practice to describe data in a way that is useful for visualization design; will familiarize with fundamental charts to talk about the concept of visual encoding and decoding.
Register for this course and see more details by visiting:
OpenCourser.com/course/gk17gz/information
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Develops fundamental knowledge necessary to describe, understand, and implement information visualization methods, which are core skills in data analysis
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Reviews summary
Data visualization foundation
This is a comprehensive introductory course on the fundamentals of information visualization, designed to provide learners with the knowledge to describe and create visualizations for various situations. It covers the fundamental concepts of visual encoding and decoding, the process behind creating effective visualizations, and the practical applications of information visualization. Students with little to no prior knowledge in this field will benefit the most from this course.
Concepts are explained with clarity.
"Very well structured course, with clear and understandable teaching."
"Prof. Enrico explains in a clear and entertaining way."
"The course materials are generally useful. the videos are reasonably well explained so that is positive."
Provides valuable and insightful information.
"Informative, yet highly academic in the first two modules."
"Overall an enjoyable course with an enthusiastic trainer."
"The course is with clear explanation."
Teaches best practices in the field of visualization.
"I learned a lot with it, now my knowledge about Information Visualization as well as the best practices will help build better representations for my projects."
Balances theoretical knowledge with practical applications.
"Covers both theoretical aspects and their practical applications."
"It'll give you a conceptual understanding of some common practices already found in your practice and help you build a vocabulary to talk about visualization in a more precise way."
"Weeks 3 and 4 were the best ones, with a more practical focus."
Builds necessary vocabulary to effectively describe visualizations.
"The main goal is to provide the students with the necessary “vocabulary” to describe visualizations in a way that helps them reason about what designs are appropriate for a given problem."
Occasional technical issues or assignment ambiguities.
"The only thing I would suggest to improve is giving more instructions for the final project as it was a bit unclear the extent to which we were being asked to research the graph on our own."
"There were a few problems with the assignments, such as questions referencing data elements that didn't exist."
"I noticed minor issues in the in-video quizes which I reported when I could, but I saw similar comments in the forums also."
Peer review assignments may have subjective grading.
"My primary issue and why I won't give 5 stars is that the week 3 assignment grading was very subjective and had low margin for error."
"Students read the questions differently and some graded in a very judgy manner."
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 Information Visualization: Foundations with these
activities:
Review prerequisite topics on data visualization
Show steps
Reinforces the core building blocks of data visualization that are necessary for understanding more advanced concepts.
Show steps
-
Review fundamentals of probability and statistics
-
Revisit concepts of visual perception and human cognition
-
Practice creating basic charts and graphs
Review fundamental concepts of data visualization
Show steps
Refresh your understanding of the foundational concepts and principles of data visualization to strengthen your comprehension of more advanced topics.
Show steps
-
Review textbooks or online resources on data visualization.
-
Attend a workshop or webinar on visualization fundamentals.
Visualize a personal dataset
Show steps
Apply your knowledge and skills to a real-world scenario by visualizing a dataset that is personally relevant or meaningful to you.
Show steps
-
Gather or create a dataset based on your interests or experiences.
-
Explore and analyze the dataset to identify insights and patterns.
-
Design and create visualizations that effectively communicate the insights.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore interactive tutorials on visualization techniques
Show steps
Provides practical demonstrations and step-by-step guidance on implementing effective visualization techniques.
Show steps
-
Identify online tutorials or workshops
-
Follow the instructions and practice creating visualizations
-
Experiment with different visualization tools and libraries
Explore data visualization libraries
Show steps
Familiarize yourself with popular data visualization libraries to expand your technical skills and enhance your ability to create effective visualizations.
Browse courses on
Visualization Tools
Show steps
-
Identify different data visualization libraries (e.g., D3.js, Tableau, Python's Matplotlib).
-
Follow tutorials or documentation to learn the basics of using these libraries.
-
Experiment with the libraries by creating simple visualizations.
Practice visual encoding and decoding
Show steps
Practice translating data into visual representations and interpreting visual representations back into data to strengthen understanding of encoding and decoding principles.
Show steps
-
Identify different visual encodings (e.g., color, size, shape) in provided visualizations.
-
Decode the meaning of visual representations by extracting data values from visualizations.
-
Create visualizations by encoding data into visual elements (e.g., bar charts, scatter plots).
Analyze and critique visualizations
Show steps
Enhance your critical thinking skills by examining visualizations, identifying their strengths and weaknesses, and providing constructive feedback to improve their effectiveness.
Show steps
-
Review different types of visualizations and their intended purposes.
-
Analyze visualizations for their clarity, accuracy, and effectiveness.
-
Provide constructive feedback on visualizations, suggesting improvements for design and data representation.
Create a visual data story
Show steps
Develop your ability to communicate insights effectively by crafting a visual narrative that conveys a clear and engaging data-driven story.
Browse courses on
Data Storytelling
Show steps
-
Choose a dataset and identify a compelling story to tell.
-
Design visualizations that effectively convey the story's key points.
-
Create an interactive or static visual presentation.
-
Share your story with others and gather feedback.
Develop a visualization dashboard
Show steps
Gain practical experience in designing and developing interactive dashboards that enable users to explore and analyze data effectively.
Browse courses on
Dashboard Design
Show steps
-
Identify the purpose and target audience for the dashboard.
-
Design the dashboard layout and select appropriate visualizations.
-
Develop the dashboard using a suitable data visualization tool.
-
Test and iterate on the dashboard based on user feedback.
Review prerequisite topics on data visualization
Show steps
Reinforces the core building blocks of data visualization that are necessary for understanding more advanced concepts.
Show steps
Show steps
Show steps
- Review fundamentals of probability and statistics
- Revisit concepts of visual perception and human cognition
- Practice creating basic charts and graphs
Review fundamental concepts of data visualization
Show steps
Refresh your understanding of the foundational concepts and principles of data visualization to strengthen your comprehension of more advanced topics.
Show steps
Show steps
Show steps
- Review textbooks or online resources on data visualization.
- Attend a workshop or webinar on visualization fundamentals.
Visualize a personal dataset
Show steps
Apply your knowledge and skills to a real-world scenario by visualizing a dataset that is personally relevant or meaningful to you.
Show steps
Show steps
Show steps
- Gather or create a dataset based on your interests or experiences.
- Explore and analyze the dataset to identify insights and patterns.
- Design and create visualizations that effectively communicate the insights.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore interactive tutorials on visualization techniques
Show steps
Provides practical demonstrations and step-by-step guidance on implementing effective visualization techniques.
Show steps
Show steps
Show steps
- Identify online tutorials or workshops
- Follow the instructions and practice creating visualizations
- Experiment with different visualization tools and libraries
Explore data visualization libraries
Show steps
Familiarize yourself with popular data visualization libraries to expand your technical skills and enhance your ability to create effective visualizations.
Browse courses on
Visualization Tools
Show steps
Show steps
Show steps
- Identify different data visualization libraries (e.g., D3.js, Tableau, Python's Matplotlib).
- Follow tutorials or documentation to learn the basics of using these libraries.
- Experiment with the libraries by creating simple visualizations.
Practice visual encoding and decoding
Show steps
Practice translating data into visual representations and interpreting visual representations back into data to strengthen understanding of encoding and decoding principles.
Show steps
Show steps
Show steps
- Identify different visual encodings (e.g., color, size, shape) in provided visualizations.
- Decode the meaning of visual representations by extracting data values from visualizations.
- Create visualizations by encoding data into visual elements (e.g., bar charts, scatter plots).
Analyze and critique visualizations
Show steps
Enhance your critical thinking skills by examining visualizations, identifying their strengths and weaknesses, and providing constructive feedback to improve their effectiveness.
Show steps
Show steps
Show steps
- Review different types of visualizations and their intended purposes.
- Analyze visualizations for their clarity, accuracy, and effectiveness.
- Provide constructive feedback on visualizations, suggesting improvements for design and data representation.
Create a visual data story
Show steps
Develop your ability to communicate insights effectively by crafting a visual narrative that conveys a clear and engaging data-driven story.
Browse courses on
Data Storytelling
Show steps
Show steps
Show steps
- Choose a dataset and identify a compelling story to tell.
- Design visualizations that effectively convey the story's key points.
- Create an interactive or static visual presentation.
- Share your story with others and gather feedback.
Develop a visualization dashboard
Show steps
Gain practical experience in designing and developing interactive dashboards that enable users to explore and analyze data effectively.
Browse courses on
Dashboard Design
Show steps
Show steps
Show steps
- Identify the purpose and target audience for the dashboard.
- Design the dashboard layout and select appropriate visualizations.
- Develop the dashboard using a suitable data visualization tool.
- Test and iterate on the dashboard based on user feedback.
Career center
Learners who complete Information Visualization: Foundations will develop knowledge and skills
that may be useful to these careers:
Data Visualization Architect
Data Visualization Architect
A Data Visualization Architect conceives and oversees the development of an organization's data visualization strategy. They work with data scientists and business stakeholders to understand the organization's data and information needs and to design and develop data visualizations that effectively communicate insights. This course introduces fundamental knowledge for information visualization and provides the necessary vocabulary to describe visualizations in a way that helps reason about what designs are appropriate for a given problem. This foundational knowledge is critical for a Data Visualization Architect to effectively design and develop data visualizations that meet the needs of the organization.
Data Visualization Engineer
Data Visualization Engineer
A Data Visualization Engineer designs, builds, and maintains data visualization applications and dashboards. They work with data scientists and business stakeholders to understand the organization's data and information needs and to create data visualizations that effectively communicate insights. This course provides a strong foundation for data visualization engineering by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Data Visualization Engineer to effectively design and develop data visualizations that meet the needs of the organization.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to make predictions. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for statistics by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Statistician to effectively communicate their findings to stakeholders.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for software engineering by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Software Engineer to effectively communicate their findings to stakeholders.
Data Analyst
Data Analyst
A Data Analyst collects, cleans, and analyzes data to identify trends and patterns. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for data analysis by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Data Analyst to effectively communicate their findings to stakeholders.
Marketing Analyst
Marketing Analyst
A Marketing Analyst collects, analyzes, and interprets data to help businesses make marketing decisions. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for marketing analysis by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Marketing Analyst to effectively communicate their findings to stakeholders.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for product management by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Product Manager to effectively communicate their findings to stakeholders.
Data Scientist
Data Scientist
A Data Scientist uses mathematical and statistical models to analyze data and make predictions. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for data science by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Data Scientist to effectively communicate their findings to stakeholders.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst helps businesses make better decisions by providing them with data and insights. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for business intelligence analysis by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Business Intelligence Analyst to effectively communicate their findings to stakeholders.
User Experience Designer
User Experience Designer
A User Experience Designer designs and evaluates the user experience of websites, intranets, and other digital products. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for user experience design by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a User Experience Designer to effectively communicate their findings to stakeholders.
Interaction Designer
Interaction Designer
An Interaction Designer designs and evaluates the user experience of websites, intranets, and other digital products. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for interaction design by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for an Interaction Designer to effectively communicate their findings to stakeholders.
Information Architect
Information Architect
An Information Architect designs and organizes the structure and content of websites, intranets, and other digital products. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for information architecture by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for an Information Architect to effectively communicate their findings to stakeholders.
Visual Designer
Visual Designer
A Visual Designer creates visual content for websites, intranets, and other digital products. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for visual design by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Visual Designer to effectively communicate their findings to stakeholders.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze data and make predictions. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for quantitative analysis by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Quantitative Analyst to effectively communicate their findings to stakeholders.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs and develops machine learning models. They use data visualization to communicate their findings to stakeholders. This course provides a strong foundation for machine learning engineering by introducing fundamental knowledge for information visualization and providing the necessary vocabulary to describe visualizations. This knowledge is critical for a Machine Learning Engineer to effectively communicate their findings to stakeholders.
For more career information including salaries, visit:
OpenCourser.com/course/gk17gz/information
Reading list
We've selected ten 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
Information Visualization: Foundations.
Is helpful in providing background or prerequisite knowledge and is commonly used as a textbook at academic institutions.
Save
Is commonly used as a textbook at academic institutions and by industry professionals.
Save
Is more valuable as a reference tool than it is as a current textbook.
Is more geared towards advanced learners and researchers.
Save
Is an excellent resource for those interested in the storytelling and communication aspects of data visualization.
Save
Is focused on the practical aspects of data visualization and valuable resource for beginners and practitioners.
Focuses on the design of dashboards and valuable resource for those interested in creating effective and informative data visualizations for decision-making.
Is geared towards business professionals and valuable resource for those interested in communicating data effectively to non-technical audiences.
Features a collection of essays from experts in the field of data visualization and valuable resource for those interested in learning from the experiences and insights of leading practitioners.
Provides a quick and easy-to-understand overview of data visualization and valuable resource for beginners.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/gk17gz/information
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Time
20 hours
Via
Coursera
Institutions
New York University Tandon School of Engineering
New York University
Instructors
Enrico Bertini
Cristian Felix
This course belongs to a
collection
called
Information Visualization . It's comprised of four courses:
- Information Visualization: Advanced Techniques
- Information Visualization: Foundations (viewing)
- Information Visualization: Programming with D3.js
- Information Visualization: Applied Perception
Good to know
Develops fundamental knowledge necessary to describe, understand, and implement information visualization methods, which are core skills in data analysis
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