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Home / Courses / AI / Detail
AI · AIC-82

AI for UX/UI and Product Design

AI for UX/UI and Product Design is a practical course in using AI at every stage of UX and UI work, from research planning, interview synthesis, personas and journey maps to generating UI with Google Stitch and building prototypes with Figma Make, v0 and Claude. It suits UX/UI designers, UX researchers and product managers who want to work faster while staying grounded in real users.

Updated
AI for UX/UI and Product Design
From 6,210 THB / person 6,900 −10% excl. VAT 7% · group rates available
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PDFDownload the course outline
  • Duration12 hours · 2 days
  • FormatOnsite / live online
  • Next roundOn request
  • CertificateIncluded

Course overview

UX and UI work now has to move faster at every step, from synthesising user interviews to producing prototypes that let the team and clients see the idea. AI tools can draft surveys, cluster insights, generate screens from a description and build clickable prototypes in very little time. Used carelessly, though, they leave teams with invented personas, insights with no evidence behind them, or screens that look good but do not solve real users' problems.

This course builds on UX Design and Design Thinking and Figma for beginners, bringing AI into every stage of the design process. Learners plan research and draft surveys, synthesise interviews into an affinity map, build personas, journey maps and problem statements from real data, and use AI to support heuristic and accessibility reviews. They then draft user flows and UX writing, generate UI with Google Stitch, use AI in Figma and Figma Make, and build working prototypes with v0 and Claude, always keeping people in charge of decisions and checking every result. The course closes with testing on real users and a presentation of the work. (2 days, 6 hours per day, 12 hours in total, Intermediate level.)

What you’ll gain

  • Know which stages of the UX process AI can support and where real user data is essential
  • Use AI to plan research, draft surveys and synthesise interviews while keeping the evidence
  • Build personas, journey maps and problem statements from real data rather than AI inventions
  • Use AI to support heuristic reviews, accessibility checks and UX writing
  • Generate and refine UI quickly with Google Stitch and AI features in Figma
  • Build working prototypes with Figma Make, v0 and Claude for testing with users
  • Protect user and client data in line with PDPA principles when using AI tools

Who this course is for

  • UX/UI and product designers who want to work faster with AI
  • UX researchers who need to synthesise large numbers of interviews and survey responses
  • Product managers and product owners who want to prototype and test ideas themselves
  • Graduates of UX Design and Design Thinking or Figma for beginners who want to go further

Prerequisites

  • A basic understanding of the UX process or Design Thinking
  • Basic Figma skills: frames, components and simple prototypes
  • Your own or a company Figma account and Google account
  • A laptop with internet access and an up-to-date browser

Curriculum

Course Details

The course runs for 2 days, 6 hours per day (12 hours in total, 09:00-16:00), as a workshop that follows one sample service brief throughout. Intermediate level. It builds on UX Design and Design Thinking and Figma for beginners, so it does not repeat UX or Figma basics and focuses instead on using AI at each stage of the design process. Learners use their own or company accounts. Figma's AI features and Figma Make have plan-based quotas and some require a paid plan, while Google Stitch, v0, Claude and ChatGPT offer limited free tiers. All practice data is simulated. Learners take home the course handbook, a prompt library, Figma files and templates covering research through to testing.

Day 1 AI in Research and Definition

Section 1: AI in the UX/UI Process

  • Which stages of Design Thinking and the Double Diamond AI can genuinely support
  • Risks: insights with no evidence, and synthetic users that cannot replace real ones
  • User data and PDPA: what must never be uploaded and how to remove personal data
  • Choosing tools for the job: AI assistants, UI generators and prototyping tools
  • Lab: set up an AI workspace and agree usage rules for the team

Section 2: Lab: Planning Research with AI

  • Draft a research plan: goals, research questions and methods
  • Draft an interview guide and a screener for recruiting participants
  • Draft a survey and have AI check for leading or biased questions
  • Lab: a research plan and interview guide for a sample service brief

Section 3: Lab: Interview Synthesis and Affinity Mapping

  • Transcribe interviews with consent and remove identifying details before analysis
  • Have AI cluster themes and draft an affinity map from several interviews
  • Check every insight against users' actual words and drop anything without evidence
  • Analyse large numbers of open-ended survey answers
  • Lab: synthesise insights from six simulated interviews

Section 4: Lab: Personas, Journey Maps and Problem Statements

  • Draft personas from evidenced insights, not from AI imagination
  • Build a customer journey map with pain points and design opportunities
  • Write a problem statement and How Might We questions
  • Lab: a persona and journey map from the Section 3 research

Section 5: Lab: Heuristic and Accessibility Reviews with AI

  • Have AI review screenshots against Nielsen's heuristics
  • Compare flows of competitors or similar services from screenshots
  • Check contrast, text size and basic accessibility issues
  • Rank issues by severity and re-check them with a designer's judgement
  • Lab: a review report for the screens of a sample app
Day 2 From Idea to Prototype and Testing

Section 6: Lab: IA, User Flows and UX Writing

  • Draft a sitemap and information architecture from the problem statement
  • Draft user flows for the main path and error cases
  • Write microcopy, error messages and empty states in Thai and English
  • Define a tone of voice so AI writes consistently across the product
  • Lab: the user flow and on-screen copy for the main flow

Section 7: Lab: Fast UI Generation with Google Stitch

  • Generate screens from a description or sketch and ask for alternatives
  • Refine layout, colour and elements step by step
  • Move the work into Figma to align it with the design system
  • Lab: draft three key screens for the sample service

Section 8: Lab: AI in Figma and Figma Make

  • AI features in Figma that handle repetitive work, such as renaming layers and filling sample content
  • Figma Make: build a working prototype from a description and existing designs
  • Use existing components and the design system so results stay on brand
  • The limits of AI-generated work and what designers still need to finish themselves
  • Lab: a prototype of the main flow in Figma

Section 9: Lab: Working Prototypes with v0 and Claude

  • Build a code prototype from a description or screenshot with v0
  • Refine the look with Design Mode and hand the code over to developers
  • Use Claude to build interactive prototypes for quick concept tests
  • Choose between a Figma prototype and a code prototype based on what you need to test
  • Lab: a clickable prototype running on mock data

Section 10: Workshop: Usability Testing and Presentation

  • Use AI to draft a test script and tasks for usability testing
  • Test the prototype with classmates acting as users and record the findings
  • Synthesise the results with AI and prioritise what to fix
  • Present the journey from insight to prototype and plan the team's AI workflow

Schedule & training options

For individuals — public rounds

No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770

Join the waiting list Ask about rounds

For organisations — in-house / private

  • Tailor the content to your team’s tools and projects
  • Your dates, at your office or live online
  • Quotation with tax ID for procurement
Corporate training quote

Instructors

Frequently asked questions

Which parts of UX work can AI help with, and which still need data from real users?

AI helps most with drafting and summarising at volume: planning research, drafting surveys and interview questions, clustering interview findings, heuristic and accessibility reviews, UX writing and generating UI or prototypes quickly. However, users' needs, problems and behaviour must come from interviews and testing with real people, so personas or journey maps that AI invents without supporting data should not drive decisions.

How do you summarise user interviews into an affinity map with AI and keep it trustworthy?

Transcribe the interviews and remove details that identify participants. Ask the AI to extract key observations as separate points, each linked to the original quote or its location in the transcript, then group similar observations into themes as an affinity map. Finally, the researcher checks that every theme is backed by evidence from several users rather than conclusions the AI made up.

How do Google Stitch and Figma Make differ, and what is each best used for?

Google Stitch generates UI screens quickly from a description or sketch, which suits exploring several visual directions early on before continuing in Figma. Figma Make builds interactive prototypes from prompts inside Figma, which suits creating working prototypes to test with users. This course uses both, alongside v0 and Claude, in the stage that takes ideas to prototypes.

Who is the AI for UX/UI and Product Design course for, and what should I know beforehand?

It suits UX/UI and product designers who want to work faster with AI, UX researchers who summarise large volumes of interviews, and product managers or product owners who want to prototype ideas themselves. It is intermediate level, so you should understand the basic UX or design thinking process and be able to create frames, components and simple prototypes in Figma, as the basics are not retaught.

What will I be able to do after the AI for UX/UI and Product Design course?

You will be able to plan research and summarise interviews with AI while keeping the evidence, build personas, journey maps and problem statements from real data, run heuristic, accessibility and UX writing reviews, generate UI with Google Stitch and Figma's AI features, and build working prototypes with Figma Make, v0 and Claude for user testing. Participants receive a Certificate of Completion with its own number that can be verified online.

Which accounts and tools do I need for the AI for UX/UI and Product Design course?

You need your own or your company's Figma and Google accounts, plus a laptop with internet access and an up-to-date browser. Figma's AI features and Figma Make have quotas by plan and some require a paid plan, while Google Stitch, v0, Claude and ChatGPT offer limited free tiers. All practice data is simulated.