Certificate in Data Visualization
Start anytime. Learn at your own pace.
Reveal insights, drive decisions, advance your career.
Data Science
Online Self-Paced
60 hours
7 CEUs
$1200
Instructor: Dr. Jesus Caban
Curriculum designed and delivered by Johns Hopkins faculty
LIVE monthly seminars and office hours
Engaging learning including video walkthroughs and hands-on activities
Use your platform of choice (Tableau, Power BI, Python, etc.)
Satisfaction guaranteed. Explore the course with no risk.
Turning raw data into clear, compelling visuals isn’t just a technical skill—it’s a career game-changer. With it, your work gets noticed and your proposals get approved. Without it, your audience tunes out, trips on irrelevant data, or draws the wrong conclusion.
In his three course Certificate in Data Visualization Dr. Jesus Caban instills in you the mindset and skillset for visualizations that support decision-making, inspire confidence, and ensure your insights land—even for the most technical projects.
No more:
- Scrolling through chart options for the one that “looks right”
- Adding 100 words to the bottom of your graph to explain it
- Giving up on a figure because the data “can’t be represented visually”
Because you’ll know which charts communicate which relationships, how color can enhance understanding rather than confuse it, and how to design visualizations that reveal insights rather than decorate a screen.
In video lectures, selected readings, hands-on assignments and ready-to-use notebooks, you’ll turn real-world datasets into inspiring views that reveal hidden trends and make your conclusions clear.
Work in the platform of your choice: Tableau, Power BI, and Python are great options. And you’ll supplement them with new skills in more advanced tools:
- Libraries including Matplotlib, Seaborn, and Plotly, for custom visualizations and automate reporting processes.
- D3.js, the powerful JavaScript library that gives you complete control over your visualizations for the web
- ParaView and VTK for complex spatial data
- QGIS and mapping libraries for geographic insight.
The Certificate combines Dr. Caban’s 3 sequential data visualization courses:
into one bundle, saving you $300 off the cost of buying separately
Who is This Certificate For?
- Data analysts and business intelligence professionals who want to drive decisions
- Healthcare and medical imaging specialists who need to interpret complex patient data
- Scientists and researchers who want to make complex findings accessible to broader audiences
- Financial and market analysts seeking to represent trends and forecasts with greater impact
- Marketing and UX professionals aiming to represent customer journeys and behavior patterns visually
- Journalists and data storytellers who need to communicate complex information to the public clearly
Prerequisites
You should be comfortable reading basic charts, understanding data types (like categorical and quantitative), and thinking critically about how visuals communicate. You don’t need to be a Python expert—but some familiarity helps. Projects use tools like Jupyter Notebooks, Plotly, and networkx, with sample code and detailed walkthroughs provided. If you’ve worked through the first course or have experience exploring datasets in Python (even with help), you’ll be well-prepared. All projects can be completed using free, browser-based tools like Google Colab, Kaggle, or Binder—no installations required.
No Risk: Satisfaction Guaranteed
Feel confident in your learning journey! If the course content is too advanced, not advanced enough, or simply doesn’t meet your expectations, we’ve got you covered with our money-back guarantee. Just contact our team within 7 days from purchase to receive a full refund—no questions asked.
Meet Your Instructor
Dr. Jesus Caban
Johns Hopkins University, Defense Healthcare Management Systems
Jesus Caban is Chief Data Scientist in the Program Executive Office, Defense Healthcare Management Systems and instructor in Johns Hopkins Engineering’s #1 ranked online master’s program in Data Science. he has served in different roles including the Chair of the DHA Enterprise Intelligence and Analytics IPT, the Chair of the American Medical Informatics Association (AMIA) Visual Analytics working group, and the Vice Chair of the 2016 IEEE Visualization conference. He earned his PhD in computer science from the University of Maryland Baltimore County.
Dr. Caban is Here to Help!
Questions about course content? Looking for insight on specific visualization challenges?? Stop by monthly Zoom office hours to talk with Jesus and fellow students about what you’re learning in the course and your own professional projects.
Course Summaries
Well-designed visualizations don’t just present data—they make it easier to understand, remember, and act on. This course helps you build that skill from the ground up, showing how to turn complex information into clear, trustworthy visual communication.
You’ll explore how design choices align with human perception to enhance clarity and impact. You’ll study real examples—good and bad—and practice applying core techniques like color, layout, and chart selection for different data types.
By the end, you’ll have a strong foundation in visualization best practices and a sharper eye for ethical, effective design.
Projects:
- Misleading Data in the Wild: Analyze a series of deceptive charts to learn how visual decisions can mislead audiences and undermine trust.
- Building the Basics with the Iris Dataset: Create classic visualizations and practice the fundamentals with this famous dataset of flowers from 1936.
- Designing with Encodings: Explore the power of position, color, size, and shape to express patterns and comparisons more effectively.
- Critiquing a Complex Dashboard Evaluate the U.S. Debt Clock dashboard through the lens of simplicity, structure, and graphical excellence to understand how overwhelming design choices can obscure meaning.
Start designing with purpose and handle complexity with clarity.
When your data goes beyond rows and columns—into networks, hierarchies, maps, or unstructured text—you need more powerful tools and techniques. This course teaches you how to design visualizations that do more than display: they help you explore, compare, and discover.
Learn how to enhance clarity with color theory, enable exploration through interaction, and tackle complex data using specialized visual forms—from node-link diagrams and treemaps to geospatial maps and text analysis tools.
By the end, you’ll have the confidence and flexibility to visualize almost any kind of data.
Projects:
- Color in Context: Explore colormaps and complementary colors in Python to understand how hue, contrast, and palette choices shape meaning and perception in your visualizations.
- Interactive Insights: Build interactive charts using Plotly or Altair—adding dropdowns, sliders, and tooltips to turn static visuals into tools for deeper exploration.
- Networks & Trees: Use networkx and Plotly to visualize relationships and hierarchies, from simple graphs to structured trees—revealing connections that charts alone can’t.
- Data on the Map: Plot geographic data using map projections, spatial markers, and hover info to show how place impacts patterns—and why map design matters.
- Visualizing Text: Clean and visualize text data with word clouds, frequency charts, and co-occurrence networks—turning raw language into clear insight.
Specialized fields demand specialized tools.
Some data is too complex for traditional dashboards. In fields like healthcare, engineering, and environmental science, information often spans time, space, and multiple dimensions—demanding more advanced visualization techniques.
Get equipped to handle high-complexity data using methods tailored for temporal patterns, 3D models, vector fields, and multivariate time series. Through hands-on projects and expert guidance, you’ll learn how to make change, movement, and depth both visible and understandable.
Projects:
- Time, Trends, and Patterns: Visualize and explore temporal data to reveal trends, cycles, and anomalies
- Slicing Through Space: Use ImageJ to navigate and analyze 3D image stacks—learning how volumetric data can be explored slice-by-slice to uncover internal structure
- Rendering Reality with VolView: Experiment with direct volume rendering techniques, turning dense medical or scientific datasets into interpretable 3D models.
- Shaping Surfaces with ParaView: Extract iso-surfaces from scalar fields and explore how changing thresholds reshapes what we see
- Visualization Checkpoint: Critically evaluate a sample chart and propose methods to test its effectiveness
Tab 4 content.
Earning Your Certificate
After completing the course content, you can successfully complete and submit a capstone project to earn your Certificate of Achievement—proving to colleagues and employers that you’re ready to take the lead in data visualization challenges of every size and scope.
The capstone requires apply your data visualization and analytical skills by selecting a real-world dataset and developing two interactive dashboards. These dashboards should answer a set of analytical questions and follow a strong understanding of design principles, interactivity, and storytelling.
The image is for illustrative purposes only. Actual certificate design subject to change,
Then, you will create a professional report on your dashboards. The project will be reviewed by Dr. Caban, who will provide feedback, which can be discussed further during live office hours.
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Course Delivery and Support
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Certificate in Data Visualization
Data Science
Online Self-Paced
60 hours
7 CEUs
$1200
No Risk: 7-Day Money Back Guarantee