Self-Paced, Flexible Online Course
Advanced Techniques in Data Visualization
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Advanced Techniques in Data Visualization
LEARNING OUTCOMES
Visual Analytics for Complex Datasets
Transform data into powerful tools for analysis, exploration, and storytelling
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Apply perceptual color theory and color spaces to enhance clarity, accessibility, and meaning
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Design interactive visualizations that support exploration, filtering, and insight discovery
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Represent hierarchical and networked data using appropriate visualization models
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Visualize geospatial data accurately while accounting for projection, scale, and distortion
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Analyze and visualize unstructured text data to uncover patterns, themes, and relationships
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Select and apply advanced visualization techniques for diverse real-world data challenges
Earn a certificate of completion from Johns Hopkins University
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#6 National University Rankings
U.S. News & World Report, 2025
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#1 Computer Information Technology
U.S. News & World Report, 2025
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#1 Biomedical Engineering Program
US News and World Report
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#13 Best Global University
U.S. News & World Report, 2024
KEY HIGHLIGHTS
Why Choose This Course?
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Flexible format
Benefit from an asynchronous, self-paced learning journey, featuring engaging video walkthroughs and recorded sessions by Johns Hopkins University faculty.
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Hands-on learning
Build advanced visualizations through a comprehensive set of tools and techniques and hands-on Python assignments.
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Earn Continuing Education Units
Earn two Continuing Education Units upon completion of this course, allowing you to demonstrate your commitment to continuous learning and skill advancement.
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Globally recognized credential
Earn a professional certificate from Johns Hopkins University upon course completion.
Tools and Techniques
Python
Jupyter Notebooks
Plotly
NetworkX
Tabular
Altair
Python
Jupyter Notebooks
Plotly
NetworkX
Tabular
Altair
- Overview
- Learning Journey
- Curriculum
- Projects
- Certificate
- Faculty
- Fees
This Course is Ideal For
Professionals and graduate-level learners looking to expand beyond foundational visualization methods
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Data professionals
Seeking to visualize complex and non-traditional data types such as networks, maps, and text
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Analysts and researchers
Who require interactive and exploratory visualization techniques to uncover insights
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Engineers and technologists
Working with large structured and unstructured datasets
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Designers and communicators
Interested in advanced visual storytelling grounded in perception and cognition
Experience a Unique Learning Journey
Our pedagogy is designed to ensure a holistic learning experience
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Flexible learning journey
Learn at your own pace with a flexible, asynchronous format built for working professionals
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Engaging material
Learn through focused content, video walkthroughs, and recorded sessions by JHU faculty
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Application-focused approach
Gain actionable insights through engaging quizzes, readings, and hands-on projects
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Globally recognized credentials
Earn a Johns Hopkins Certificate of Completion and 2 Continuing Education Units upon completion
Curriculum
The curriculum for this course is designed by faculty at Johns Hopkins University in collaboration with leading industry practitioners and progresses through specialized visualization domains, beginning with perceptual and technical color spaces and advancing to interactive techniques that support exploratory analysis.
Module 01 | The Use of Color in Data Visualization
Concepts Covered: - Role of Color in Human Perception and Communication - Applying RGB and CIELab Color Spaces to Visualization Design - Designing Color Encodings for Clarity and Accessibility
Module 02 | User Interaction in Data Visualization
Concepts Covered: - Role of Interactivity in Data Exploration - Applying Interaction Techniques: Filtering, Zooming, Brushing, and Tooltips - Designing User-Centered Interactive Visualizations
Module 03 | Network Visualization
Concepts Covered: - Representing Hierarchical and Networked Data Effectively - Selecting Appropriate Layouts for Graphs and Trees - Improving Readability with Clustering and Edge Bundling
Module 04 | Visualization and Maps
Concepts Covered: - Visualizing Geospatial Data Responsibly - Understanding Map Projections, Scale, and Distortion - Designing Choropleth, Dot, and Flow Maps
Module 05 | Text Visualization
Concepts Covered: - Treating Text as Data for Analytical Visualization - Visualizing Document Content, Evolution, and Relationships - Analyzing Conversations and Large Text Corpora
Work on Hands-On Assignments
Apply advanced visualization tools and techniques in comprehensive assignments across data types.
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Advanced
Visualization techniques
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Hands-On
Python assignments
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New-Age
Tools and technologies
COLOR THEORY
Color in Context
Description
Explore colormaps and complementary colors in Python to understand how hue, contrast, and palette choices influence meaning and perception in your visualizations.
Skills you will learn
- Color Mapping
- Palette Design
- Perceptual Contrast
INTERACTIVE DATA VISUALIZATION
Interactive Insights
Description
Build interactive charts using Plotly or Altair by adding dropdowns, sliders, and tooltips to transform static visuals into tools for deeper exploration.
Skills you will learn
- Interactive Design
- User Controls
- Exploratory Analysis
HIERARCHICAL VISUALIZATION
Networks & Trees
Description
Use NetworkX and Plotly to visualize relationships and hierarchies, from simple graphs to structured trees that reveal connections beyond what charts alone can show.
Skills you will learn
- Graph Modeling
- Relationship Mapping
- Hierarchy Visualization
GEOSPATIAL DATA VISUALIZATION
Data on the Map
Description
Plot geographic data using map projections, spatial markers, and hover info to demonstrate how location influences patterns and why map design is crucial.
Skills you will learn
- Map Projections
- Spatial Mapping
- Interactive Geovisualization
Earn a Professional Certificate
Receive a certificate of completion from Johns Hopkins University and Great Learning.
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#1 Ranked Online Grad Program
Computer Information Technology by U.S. News & World Report
* Image for illustration only. Certificate subject to change.
Meet Your Faculty
Learn from world-renowned JHU faculty
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Dr. Jesus Caban
Chief Data Scientist in the Program Executive Office, Defense Healthcare Management Systems
Chair, AMIA Visual Analytics Working Group
Vice Chair, 2016 IEEE Visualization Conference
Know More
LinkedIn Profile
University LinkCourse Fees
The course fee is USD 500
Advance Your Career
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Enhance clarity and accessibility across data types with perceptual color theory and advanced visual encodings
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Design interactive visualizations that support filtering, insight discovery, and advanced analytical tasks
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Appropriately represent complex data structures, including hierarchical, networked, and unstructured text data
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Visualize geospatial and real-world data, ensuring projection, scale, distortion, and advanced techniques
Enrollment process
Get started instantly with our self-enrollment process and begin your learning journey today
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1. Enter your details
Provide your information to begin the enrollment process
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2. Make payment
Complete the payment to receive your enrollment confirmation via email
Prerequisites
- Learners are expected to have a foundational understanding of data visualization concepts and proficiency in the Python programming language, as the hands-on assignments and course materials are designed for application using Python and relevant frameworks.
Delivered in Collaboration with:
Johns Hopkins University is collaborating with online education provider Great Learning to offer the Advanced Techniques in Data Visualization course. Great Learning is a professional learning company with a global footprint in 14+ countries. Its mission is to make professionals around the globe proficient and future-ready. This course leverages JHU's leadership in innovation, science, engineering, and technical disciplines developed over years of research, teaching, and practice. Great Learning collaborates with institutions to manage enrollments (including all payment services and invoicing), technology, and participant support.
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