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3D Data Visualization for Science Communication

Approx. 32 hours to complete

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Course Summary

Learn how to effectively communicate your data through visualizations in this course. You'll explore various visualization types and techniques, as well as how to choose the right one for your data and audience.

Key Learning Points

Learn to tell a story with your data through effective visualizations
Explore different types of visualizations and when to use them
Understand the importance of audience and context in data communication

Job Positions & Salaries of people who have taken this course might have

- USA: $77,000
- India: ₹1,200,000
- Spain: €35,000
- USA: $77,000
- India: ₹1,200,000
- Spain: €35,000
- USA: $70,000
- India: ₹1,000,000
- Spain: €30,000
- USA: $77,000
- India: ₹1,200,000
- Spain: €35,000
- USA: $70,000
- India: ₹1,000,000
- Spain: €30,000
- USA: $50,000
- India: ₹700,000
- Spain: €25,000

Learning Outcomes

Learn to choose the right visualization for your data and audience
Develop skills to create effective visualizations that tell a story
Understand the importance of context and audience in data communication

Prerequisites or good to have knowledge before taking this course

Basic understanding of data analysis
Familiarity with tools such as Excel or Google Sheets

Course Difficulty Level

Intermediate

Course Format

Self-paced
Online

Similar Courses

Data Visualization with Tableau
Data Visualization and Communication with Tableau

Related Education Paths

Notable People in This Field

Alberto Cairo
Cole Nussbaumer Knaflic

Related Books

Description

This course is an introduction to 3D scientific data visualization, with an emphasis on science communication and cinematic design for appealing to broad audiences. You will develop visualization literacy, through being able to interpret/analyze (read) visualizations and create (write) your own visualizations.

By the end of this course, you will: -Develop visualization literacy. -Learn the practicality of working with spatial data. -Understand what makes a scientific visualization meaningful. -Learn how to create educational visualizations that maintain scientific accuracy. -Understand what makes a scientific visualization cinematic. -Learn how to create visualizations that appeal to broad audiences. -Learn how to work with image-making software. (for those completing the Honors track)

Outline

Course Orientation
Welcome to 3D Scientific Data Visualization!
Syllabus
About the Discussion Forums
Updating Your Profile
Social Media
Orientation Quiz

Week 1: Introduction
Introduction to Scientific Visualization
Visualization Pipeline
Computational Science
Computer Graphics
Rendering
Moving Pictures
Critiquing Visualization
Data and Visualization Ethics
Week 1 Quiz 1: What Is Visualization?
Week 1 Quiz 2: Components of Scientific Visualization
Week 1 Quiz 3: What Makes a Good Visualization?

Week 2: Data
Virtual Coordinates
3D Geometry
Data Representation
Finding and Using Data
Computational Resources
Optimization
Software
Transformations and Attributes
Programming
Week 2 Quiz 1: What Scientific Data Looks Like
Week 2 Quiz 2: Working with Data
Week 2 Quiz 3: How to Approach Loading Data into a New Tool
Week 2 Hands On Assignment: Part 1

Week 3: Meaningful Communication
Storytelling
Education
Color
Vision and Cameras
Driving Visual Features with Data
Abstraction and Representation
Data Artifacts
Previsualization
Derived Data
Week 3 Quiz 1: Understanding Humans
Week 3 Quiz 2: Designing for Human Perception
Week 3 Quiz 3: Refining Data

Week 4: Cinematic Presentation
Camera Design
Display Environments
Lighting
Designing Around the Data
Image Artifacts
Editing and Compositing
Narration and Sound
Packaging and Distribution
Week 4 Quiz 1: Action, Camera, Lights!
Week 4 Quiz 2: Digital Cosmetics
Week 4 Quiz 3: Finishing Touches

Conclusion
Closing
Course Credits

Summary of User Reviews

Learn about data visualization and science communication through this highly rated Coursera course. Users rave about the course's comprehensive content and engaging instructors. Many users appreciate the course's focus on practical applications of data visualization.

Key Aspect Users Liked About This Course

Practical applications of data visualization

Pros from User Reviews

Comprehensive content
Engaging instructors
Practical applications of data visualization
Hands-on assignments
Opportunities to learn from peers

Cons from User Reviews

Some users found the course challenging
Certain concepts can be difficult to grasp
Some users felt that the course lacked depth
Some users found the workload to be heavy
Not suitable for those without a basic understanding of data analysis

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