Course Overview: What You’ll Learn in AI Dashboard and Data Visualization UI Design
Welcome to AI Dashboard and Data Visualization UI Design
Design data-dense product dashboards that engineers actually build and users actually read. AI-assisted layout, chart choice, filtering, and accessibility from day one.
What You Will Learn
By the end of this short, focused course you will have concrete, repeatable workflows that you can use on the very next project.
- How to frame every dashboard around a single decision the viewer must make.
- A five-chart playbook that covers 90% of real product dashboards.
- Filter, segment, and compare patterns that do not overwhelm the user.
- Loading, empty, populated, and error states designed before engineering ever touches the ticket.
- Accessible, dark-mode-ready color systems for data-heavy UIs.
- How to hand off to engineers in a way that survives charting-library reality.
- Performance-first design choices for 10,000+ row tables and 5,000+ point charts.
Full Course Breakdown
Here is every paid lesson in this course. You are reading the free preview now; unlock the full course to access the rest.
Choosing the Right Chart for the Right Question
A quick, opinionated playbook for picking line, bar, table, sparkline, or big-number when you are under deadline.
Filter, Segment, Compare: The Three Interactions That Make Data Useful
Design filtering and segmentation UX that does not feel like a tax form. Compare views that make before/after obvious.
Designing for Real Data: Edge Cases, Empty States, and Loading
What your dashboard looks like before data arrives, when data is missing, when numbers are zero, and when something breaks.
Color, Contrast, and Accessibility in Data-Heavy UIs
Color systems that survive colorblind users, printing, dark mode, and the engineer who just swapped your palette for Tailwind defaults.
From Figma to Production: Working With Charting Libraries, Not Against Them
What to specify so engineers pick the right charting library and your mockup survives implementation.
Performance and Perceived Speed: Designing for Large Datasets
Pagination, virtualization, progressive loading, and the AI-assisted tricks that make 100k-row tables feel instant.
Who This Course Is For
- Product designers tasked with a dashboard and given a week to ship it.
- UX leads pushing back on "just use whatever Chart.js gives you."
- Engineers who build internal tools and want fewer trips back to design.
- Founders designing their first analytics view for investors and ops.
What Makes This Course Different
- Decision-first: Every chart exists to support a specific decision, or it does not exist.
- Evergreen: Principles and tradeoffs — not a tour of whatever chart library is trending.
- Hands-on: Every lesson ends with an exercise you do in your current design tool.
- Ships to production: Specs, states, and handoff artifacts that engineers can actually build.
Ready to Get Started?
7 lessons of practical, AI-assisted, hands-on content. Lifetime access. No fluff.