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GenAI for Product Designers: Enhancing UX with AI

Starweaver via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

2 weeks, 2 hours a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Overview

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This AI for UX design course gives product designers, UX researchers, and design leads a practical playbook for using generative AI in real workflows — not just prompt tricks. You'll learn AI UX research methods to synthesize interviews and support data into evidence-backed personas and journey maps, run AI-augmented usability and accessibility reviews, and use a Figma AI workflow for wireframing and rapid prototyping across SaaS, mobile, and enterprise products. This AI product design course also covers UX copy generation, design system compliance, and AI-assisted documentation, showing you how to keep output consistent and on-brand. You'll measure AI's real impact using metrics like speed and accessibility coverage, then build a responsible 90-day adoption roadmap — through hands-on activities and a course-end project that builds lasting, measurable AI-enhanced UX skills.

Syllabus

GenAI Foundations for UX Research and Analysis
- This module helps learners understand where generative AI fits in modern product design work and how it can strengthen research-informed UX decisions. It introduces the main types of AI technologies relevant to designers, reviews the current tool landscape and adoption patterns, and explains how GenAI supports the product design lifecycle from discovery through iteration. Learners then move into high-impact research workflows such as synthesis, persona creation, journey mapping, heuristic evaluation, accessibility analysis, and competitor benchmarking so they can connect AI support to evidence-based design practice rather than novelty.
AI-Powered Design Execution and Responsible Adoption
- This module focuses on how GenAI can support day-to-day product design execution and how teams can evaluate whether AI adoption is actually improving outcomes. Learners explore AI-assisted ideation, wireframe concept generation, UX copy creation, visual exploration, design system compliance, documentation, critique, and stakeholder communication. The module then turns to measurement, feedback loops, prompt refinement, team enablement, and roadmap planning so learners can introduce AI-enhanced design workflows in a structured, measurable, and responsible way.