This course contains the use of artificial intelligence.

Designing AI products is no longer about placing a chatbot on a screen or styling a fancy generative feature. It’s about understanding how intelligent systems actually behave — the unpredictability, the ambiguity, the confidence swings, and the strange-but-useful suggestions that make AI feel both powerful and unstable. This course teaches you how to design for that reality.

You’ll learn how to map and prototype AI behavior, create workflows that respond to uncertainty, and design transparent, trustworthy interactions for real users. Instead of focusing on generic UX processes, we go deep into the design challenges that make AI products fundamentally different: handling variable outputs, integrating behavioral states, interpreting confidence levels, guiding users through confusion, and shaping trust over time.

Throughout the course, you’ll explore practical methods like:

• AI-in-the-loop prototyping,

• behavioral mapping,

• trust curve analysis,

• adaptive UI design, and

• model-aware usability testing.

AI-in-the-loop prototyping,

behavioral mapping,

trust curve analysis,

adaptive UI design, and

model-aware usability testing.

These approaches help you build interfaces that feel intelligent, safe, and human-centered — even when the system behind them is complex or unpredictable.

Whether you’re designing assistants, automation tools, creative generators, analysis dashboards, or decision-support features, this course gives you the mental models and tools to collaborate confidently with engineers, work effectively with model constraints, and build AI experiences that scale responsibly.

If you’re ready to move beyond surface-level AI UI trends and learn how to design real AI products — the kind used in workplaces, workflows, and everyday life — this course will give you clarity, structure, and skills you can apply immediately.

Enroll to level up your design practice for the era of intelligent systems.