Course Summary
Learn the principles of effective data visualization and design with this course. Explore different techniques and tools for creating compelling visualizations that effectively communicate data insights.Key Learning Points
- Learn the fundamentals of data visualization and design
- Discover different techniques and tools for creating effective visualizations
- Understand how to effectively communicate data insights through visualizations
Job Positions & Salaries of people who have taken this course might have
- USA: $75,000 - $110,000
- India: INR 6,00,000 - INR 12,00,000
- Spain: €30,000 - €50,000
- USA: $75,000 - $110,000
- India: INR 6,00,000 - INR 12,00,000
- Spain: €30,000 - €50,000
- USA: $60,000 - $90,000
- India: INR 4,00,000 - INR 8,00,000
- Spain: €24,000 - €40,000
- USA: $75,000 - $110,000
- India: INR 6,00,000 - INR 12,00,000
- Spain: €30,000 - €50,000
- USA: $60,000 - $90,000
- India: INR 4,00,000 - INR 8,00,000
- Spain: €24,000 - €40,000
- USA: $80,000 - $120,000
- India: INR 6,00,000 - INR 12,00,000
- Spain: €30,000 - €50,000
Related Topics for further study
Learning Outcomes
- Understand the principles of effective data visualization and design
- Learn how to use different techniques and tools to create compelling visualizations
- Effectively communicate data insights through visualizations
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of data analysis and visualization
- Access to data visualization tools
Course Difficulty Level
IntermediateCourse Format
- Online self-paced course
- Video lectures and quizzes
- Hands-on exercises and projects
Similar Courses
- Data Visualization with Tableau
- Data Visualization with Python
- Information Visualization: Foundations
Related Education Paths
Notable People in This Field
- Edward Tufte
- Alberto Cairo
- Nathan Yau
Related Books
Description
In this course, you will analyze and apply essential design principles to your Tableau visualizations. This course assumes you understand the tools within Tableau and have some knowledge of the fundamental concepts of data visualization. You will define and examine the similarities and differences of exploratory and explanatory analysis as well as begin to ask the right questions about what’s needed in a visualization. You will assess how data and design work together, including how to choose the appropriate visual representation for your data, and the difference between effective and ineffective visuals. You will apply effective best practice design principles to your data visualizations and be able to illustrate examples of strategic use of contrast to highlight important elements. You will evaluate pre-attentive attributes and why they are important in visualizations. You will exam the importance of using the "right" amount of color and in the right place and be able to apply design principles to de-clutter your data visualization.
Knowledge
- Examine and improve an ineffective visualization
- Examine and improve an ineffective visualization
- Apply visualization best practices
- Create and design visualizations that work best for the target audience
Outline
- Getting Started in Effective and Ineffective Visuals
- Course Introduction
- The Human Brain and Data Visualization
- Cognitive vs Perceptual Design Distinction
- Introduction of Effective and Ineffective Visuals
- Types of Visualizations
- Examples of the Types of Visualizations in Tableau
- Practicing Good Ethics in Data Visualization
- Ineffective Visuals and How to Improve Them
- Please Read: A Note from UC Davis
- Tableau Desktop vs. Tableau Public
- Module 1 Quiz
- Visual Perception and Cognitive Load
- Visual Perception and Cognitive Principles Introduction
- Cognitive Load and Clutter
- Principles of Visual Perception
- Strategic Use of Contrast
- Pre-Attentive Attributes of Visualizations
- Color as a Pre-Attentive Attribute
- De-Cluttering Exercise
- Module 2 Quiz
- Design Best Practices and Exploratory Analysis
- Design Best Practices Introduction
- Gestalt Principle: Proximity
- Leveraging Pre-Attentive Attributes
- Accessible Visualizations
- Aesthetics
- Design and Exploratory Analysis Introduction
- What is Exploratory and Explanatory Analysis?
- Case Study: Anscombe's Quartet
- Identifying Outliers
- Constructing a Control Chart
- Missed Opportunities and Graphical Fails
- The Challenger: An Information Disaster
- Module 3 Quiz
- Design for Understanding
- Design For Understanding Introduction
- Know Your Audience(s)
- Design For Purpose
- Data, Relationships, and Design
- Static Versus Interactive Visualizations
- Multiple, Connected View
- Language, Labeling, and Scales
- Visual Lies and Cognitive Bias
- Final Thoughts
- Blogs and Articles About Data Visualization
- Selected Books About Data Visualization, Data Analysis, and Perception/Cognition
- Module 4 Quiz
Summary of User Reviews
This course on data visualization design has received positive reviews from learners. Many users appreciated the course's comprehensive coverage of visualization design principles and techniques.Key Aspect Users Liked About This Course
Comprehensive coverage of visualization design principles and techniquesPros from User Reviews
- Well-structured and engaging course content
- Clear explanations and examples of visualization design concepts
- Good balance of theory and practical application
- Great instructor support and feedback
- Opportunities for hands-on practice with data visualization tools
Cons from User Reviews
- Some users found the course content too basic or introductory
- A few technical issues with the online platform or video lectures
- Limited opportunities for peer interaction or collaboration
- The course may be too focused on design and less on data analysis or interpretation
- Some users found the course too time-consuming or demanding
Govind Acharya
4.5 Raiting
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