7 Best Generative AI Courses for UX/UI Designers in 2026

If you are new to generative AI, start with Generative AI for Everyone by DeepLearning.AI for a no-code foundation. If you want a personalised path built around your own UX/UI design goal, Upskili is the option to consider. If you need a certificate or deeper technical skills, choose from the remaining verified courses based on your focus.

Quick comparison

How we chose these courses

We selected these seven courses by looking for what matters in a UX/UI designer's week. Here are the criteria we used:

• Relevance to design tasks: The course must teach skills you can apply directly to research synthesis, UI copy, design system work, or concept exploration. A course on general AI ethics or business strategy had to connect clearly to design decisions.
• No unnecessary prerequisites: A beginner should not need a machine learning background to get started. Where a course requires prior knowledge, we state it plainly.
• Hands-on practice: We favoured courses that include projects, prompts, or exercises you can try with real design scenarios, not just video lectures.
• Clear cost: We looked for courses where the price is stated upfront, so you can make a decision without hunting for it.
• Recognised certificate where it matters: For designers who need evidence for an employer or continuing education credits, we noted which providers offer a formal certificate.

The list runs from the most accessible starting point to the most specialised. Course details come from each provider's own page, checked on the dates given. We did not take these courses ourselves.

The 7 best generative AI courses for UX/UI designers, one by one

1. Generative AI for Everyone (DeepLearning.AI)

Best for: UX/UI designers with no prior AI knowledge who need a quick, practical grounding.

This is a beginner course taught by Andrew Ng that explains how generative AI works, what it can do, and its impact on business and society. It requires no coding and gives you a mental model for all the tools you will encounter later. Generative AI for Everyone is the fastest way to get your bearings.

What you'll learn:

• How generative AI actually works, without the jargon
• What the main tools are and how to think about using them
• The real-world uses that go beyond generating images
• The broader impact of generative AI on business and society

Worth knowing: This is a conceptual foundation, not a design-tool tutorial. You will understand the technology, but you will still need to practise applying it to Figma files, research transcripts, and design handoffs on your own.

Cost and certificate: Check the provider's current pricing. A certificate is available with a PRO subscription.

2. Upskili: a personalised path for your goal

Best for: Designers who want the learning built around their own work, not a generic syllabus.

Traditional courses are prepared in advance for a broad audience. Upskili, the platform that publishes this guide, works differently. You state your goal—for example, "use generative AI in my UX/UI design workflow"—and it builds a personalised, AI-powered learning path that adapts as you learn. It starts from your current skill level and what you specifically need to achieve. This makes it especially relevant if your role mixes research, interaction design, and UI work in a way no off-the-shelf course covers.

Here is the path Upskili generated for the goal "use generative AI in my UX/UI design workflow":

1. Get Started with Generative AI: You can explain what generative AI is, how it works, and set up the tools you'll use.
   • What Generative AI Can Do for UX/UI
   • Set Up Your AI Toolkit
   • Craft Effective Prompts
2. Use AI in Research and Ideation: You can use AI to gather user insights and generate design concepts.
3. Create Visuals and Prototypes with AI: You can generate visual assets and interactive prototypes using AI tools.
4. Integrate AI into Your Workflow: You can incorporate AI tools into your daily design process and collaborate effectively.

What you'll learn:

• How to set up an AI toolkit specifically for design tasks
• Techniques for writing effective prompts that produce useful design outputs
• Ways to use AI for user research synthesis and concept ideation
• Methods for generating visual assets and prototypes
• How to weave AI tools into your existing design workflow and team collaboration

Worth knowing: This is not a fixed, pre-written course. Every learner's path differs based on their stated goal and progress. It is ideal if you know what you want to achieve but less suited if you prefer a set, predictable curriculum.

Cost and certificate: Free to approximately $20, depending on AI token/credit usage. Certificate is not stated.

3. Free Online Certificate in Artificial Intelligence and Career Empowerment (Robert H. Smith School of Business, University of Maryland)

Best for: Early to mid-career designers who want a free, accredited certificate and a broad view of AI in business.

This free online certificate from the University of Maryland's business school covers an overview of Artificial Intelligence and how it transforms business functions. It also includes career empowerment topics such as job searching and consulting.

What you'll learn:

• An overview of Artificial Intelligence and its core concepts
• How AI is transforming different business functional areas
• Career empowerment strategies, including job searching and consulting in an AI-driven market

Worth knowing: The lens is business and career-focused, not design-practice-focused. You will learn how AI changes the landscape you work in, but you will get little hands-on practice with design-specific tools or tasks.

Cost and certificate: Free. You earn a free certificate in "Artificial Intelligence and Career Empowerment" from the Robert H. Smith School of Business at the University of Maryland.

4. Explore the business value of generative AI solutions (Microsoft Learn)

Best for: Lead designers, design managers, and heads of design who need to make the business case for AI.

This Microsoft Learn learning path is built for business leaders. It guides you through identifying high-value generative AI opportunities, assessing your organisation's readiness, and implementing responsible AI solutions. It covers generative AI concepts, Microsoft Copilot, Azure AI, and intelligent agents.

What you'll learn:

• How to identify high-value generative AI opportunities in a business
• Methods for assessing organisational readiness for AI adoption
• How to implement responsible AI solutions
• An understanding of Microsoft's AI tools, including Copilot and Azure AI

Worth knowing: This course will help you build a strategy and speak to stakeholders. It will not teach you how to write better prompts for UI copy or generate design concepts. It is a leadership course, not a practitioner's workshop.

Cost and certificate: Check the provider's current pricing. Certificate is not stated.

5. Applied Generative AI and Agentic AI (Johns Hopkins University)

Best for: Designers who want a deep, structured, university-backed program and are ready for a significant time commitment.

This is a 16-week online certificate program from Johns Hopkins University designed for technology and data professionals. It covers LLMs, RAG, prompt engineering, fine-tuning, agentic workflows, and responsible AI through hands-on projects.

What you'll learn:

• How to work with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG)
• Advanced prompt engineering techniques
• Fine-tuning models for specific tasks
• Building agentic workflows
• Principles of responsible AI implementation

Worth knowing: This is a serious commitment at 16 weeks. The content is designed for technology professionals, so expect a technical depth that goes well beyond using no-code AI tools. It is overkill if you only want to improve your daily Figma workflow.

Cost and certificate: Check the provider's current pricing. You earn a Certificate of Completion from Johns Hopkins University and 11 CEUs.

6. Applied Generative AI Engineering (Udacity)

Best for: Designers who code and want to build their own custom AI tools or deeply integrate APIs into their design systems.

This Udacity nanodegree is an intermediate program on building and deploying generative AI solutions. It covers model selection, prompt engineering, PEFT, RAG systems, vector databases, and multimodal applications. It is aimed at developers.

What you'll learn:

• How to select the right model for a generative task
• Advanced prompt engineering and fine-tuning with PEFT
• Building RAG systems and working with vector databases
• Developing multimodal AI applications

Worth knowing: This is a developer's course. You need a coding background to succeed. A designer who does not write code will find this path frustrating and largely irrelevant to their daily work.

Cost and certificate: Subscription · Monthly. You earn Program Certificates.

7. Advanced: Generative AI for Developers (Google Cloud, Google Skills)

Best for: UX engineers and design technologists with a strong machine learning background.

This is a technical Generative AI learning path with 12 activities built for App Developers, Machine Learning Engineers, and Data Scientists. It has a recommended prerequisite: the Introduction to Generative AI learning path.

What you'll learn:

• A deep, technical curriculum on generative AI development on Google Cloud
• Skills designed for application development and machine learning engineering

Worth knowing: This is the most specialised and technically demanding course on the list. The recommended prerequisite means it is not a starting point. For a typical UX/UI designer who does not work as a developer, the content will be too far removed from day-to-day design tasks.

Cost and certificate: Check the provider's current pricing. Certificate is not stated.

Which course should you start with?

Your choice depends on where you are now and what you need next.

• If you are brand new to generative AI: Start with #1, Generative AI for Everyone. It is the shortest path to a solid mental model and requires no coding.
• If you want a path built on your own design goal: Look at #2, Upskili. It starts from your specific UX/UI workflow and adapts as you go, which is useful if your needs do not fit a standard syllabus.
• If you need a free certificate for your CV: Choose #3, the University of Maryland's free certificate. It is a credential from a recognised business school at no cost.
• If you are a design leader building a business case: Go with #4, Microsoft Learn's business value path. It gives you the language and framework to talk to executives.
• If you want deep, hands-on technical skills and have the time: Commit to #5, Johns Hopkins University's 16-week program. It is the most comprehensive, structured option with a university certificate and CEUs.
• If you are a designer who codes and wants to build custom solutions: Pick #6, Udacity's Applied Generative AI Engineering, but only if you meet the developer prerequisites.
• If you are a UX engineer with an ML background: #7, Google Cloud's advanced learning path is your most direct route to production-level skills on that platform.

A learning path for UX/UI designers

You do not need to pick just one course. Here is a phased approach that builds your skills in a logical order.

Phase 1: Foundations Begin with #1, Generative AI for Everyone. This gives you a clear, no-code understanding of how the technology works and what it is capable of. It is the prerequisite for everything else.

Phase 2: Hands-on practice with your own design tasks Next, apply the concepts directly to your work. #2, Upskili builds a personalised path around your specific UX/UI workflow, from research to handoff. If you prefer a more structured, technical deep-dive and have the time, #5, Johns Hopkins University's program is an alternative, though it is broader than just design.

Phase 3: Specialisation This phase depends on your career direction. If you are moving into design engineering, #6, Udacity's nanodegree or #7, Google Cloud's advanced path will give you the technical depth to build and deploy AI solutions. For most designers, deep practice in Phase 2 will be sufficient.

Where generative AI fits in UX/UI design work

Here is where the skills from these courses connect to your actual daily tasks. Remember, any AI-generated output needs your professional review. It cannot replace your design judgement, ethical responsibility, or sign-off.

Research synthesis You can use generative AI to turn raw interview transcripts and usability test notes into structured themes, affinity maps, and draft personas. For example, suppose you have just finished six user interviews and need to turn the transcripts into an affinity map and draft personas. You paste anonymised notes into an AI tool, ask it to cluster recurring pain points and suggest persona archetypes, then manually review each cluster against your own observations and rewrite the persona descriptions in your team's voice before sharing them with product managers.

UI copy and content design Drafting and iterating microcopy, error messages, and empty states is a natural fit for generative AI. You can prompt an AI tool with your component's constraints, tone guidelines, and the user's context to generate dozens of variations in seconds. You then pick and refine the best ones, ensuring they meet accessibility and localisation requirements.

Design system documentation Generating the first draft of component descriptions, usage guidelines, and accessibility annotations can save hours of tedious writing. You give the AI your component's specs and variants; it drafts the documentation. You then edit for accuracy, add code snippets, and ensure it matches your team's documentation standards.

Concept exploration Before a stakeholder review, you can use AI to quickly generate multiple layout or flow options for a feature. You describe the user goal and constraints, and the AI produces a set of low-fidelity variations. You then evaluate each against usability heuristics and your brand guidelines, selecting the most promising directions to refine yourself.

Decide where to start

The right course is the one that matches your current skill level, your available time, and whether you need a formal certificate. If you are unsure, the safest starting point is a short, no-code foundation course that gives you a mental model for everything else. From there, you can decide whether to pursue a personalised path, a deep technical program, or a business-focused certificate.

If you want to skip the guesswork and start learning exactly what you need for your own design workflow, you can create a personalised path on Upskili built around your specific goal.