# AI for UX & UI Design (Self-Paced) Canonical URL: ## Overview Add AI to your UX toolkit on a schedule that fits your work, without loosening standards for design judgment, accessibility, or user control. The coursework centers on assembling a reusable AI-powered UX workflow that reaches from research and product thinking through design, prototyping, and evaluation. A single focused sample project anchors the material. You will establish an AI workspace that expands as the project develops, apply AI to sorting and interpreting research, settle on what an appropriate AI-powered experience should do, map an inclusive user flow, and convert that design into a working prototype. Realistic test scenarios come next, together with assessment of AI-generated output and refinement of the design and the AI instructions behind it. The material avoids dependence on any one AI model or vendor. Emphasis rests on transferable workflows and responsible AI practice suited to environments such as Claude Code, OpenAI Codex, Figma Make, and comparable AI development tools. ## What you'll learn - Assemble a reusable AI workspace covering the UX process from research through prototyping and testing; Put AI to work sorting research, spotting patterns, and shaping evidence-based product opportunities - Rework research findings into problem statements, user journeys, user stories, and feature priorities - Set the point at which AI should act, assist, recommend, request approval, or leave control with the user - Map inclusive AI-powered experiences that anticipate accessibility, uncertainty, errors, correction, and recovery - Render structured Figma designs as interactive prototypes through AI-assisted development tools - Try AI-powered experiences against realistic conditions, including partial information and uncertain or wrong output - Judge and sharpen AI-generated work on design quality, accessibility, consistency, trust, and user control - Settle on a repeatable Agentic AI workflow to carry into later UX projects ## Prerequisites This advanced course is intended for UX designers and graduates of the UX & UI certificate program who understand the UX process and are comfortable working independently in Figma. ## Curriculum #### Day 1: Build Your AI Brain - Capture your UX process, methods, standards, project goals, audience, constraints, measures of success, and expectations for how AI should support your work in one shared workspace. - Teach an AI agent how you approach research, design, testing, and decision-making, and create a system that improves as new project information is added. - Plug your Skills.MD into real research tasks and guide AI to generate research plans, questions, and hypotheses. - Use prepared competitive research, behavioral research, survey results, and interview notes to organize information, identify patterns, and suggest findings and opportunities. - Compare AI outputs with the original research, remove exaggerated, unsupported, or overly general findings, and refine instructions when the agent makes assumptions. - Develop a clear project brief, working AI Brain guidelines, and research findings to guide the next phase of the project. #### Day 2: Design the Product and How AI Should Help - Use your AI Brain to generate problem statements and opportunity areas, map user journeys, and turn research findings into user stories and feature priorities. - Choose one focused product opportunity and define where AI should act, assist, recommend, ask for approval, or leave control with the user. - Plan human review, approval, correction, and intervention, including smooth handoffs between AI support and human support. - Design an experience that helps users understand what AI is doing and accounts for consent, correction, undo, uncertainty, errors, and recovery. - Develop a mid-fidelity user flow that is inclusive, accessible, understandable, and grounded in the research findings. - Review the flow for accessibility, inclusive design, trust, and user control, then add the resulting product direction, AI responsibilities, interaction patterns, and accessibility guidelines to your AI Brain. #### Day 3: Turn Your Design into a Working Prototype - Prepare clean, structured Figma files with reusable components and consistent styles for AI-assisted development. - Use tools such as Figma Make, Claude Code, or Codex to turn designs into an interactive prototype using project goals, research findings, user needs, accessibility requirements, design guidelines, and expected AI behavior. - Review the AI agent’s proposed approach before building, then compare the generated prototype with the intended experience for design quality, accessibility, and consistency. - Define success criteria and create realistic testing situations involving successful tasks, incomplete information, uncertain AI responses, incorrect results, human approval, correction, and recovery. - Evaluate clarity, accessibility, trust, and user control, and determine whether issues should be corrected in the interface, user journey, AI instructions, accessibility guidance, project information, or testing criteria. - Update the appropriate parts of your AI Brain and prototype based on testing results, then test the experience again. #### Independent Student Project - Define a product challenge and audience, build and customize your own AI Brain, and create a focused research plan. - Gather and organize supporting evidence, analyze the research, and identify product opportunities. - Develop problem statements, a user journey, and user stories, and define how AI should support the experience and where human controls are needed. - Create a working prototype and vibe-code a React or Next.js prototype using design-system context. - Test realistic situations and AI responses, including variable AI outputs, and document improvements and design decisions. - Turn the completed work into a portfolio-ready case study. ## Schedule - Dec 13, 2026 12:00am–12:00am — Live Online ## Instructors ### Bruce Gay — Instructor Bruce is an engaging trainer and program manager who brings 25+ years of practical experience to deliver effective and experiential training to students. Able to engage adult learners with a range of backgrounds and professional experiences. Successful at building effective stakeholder relationships and coordinating multi-disciplinary teams for solution delivery. Bruce has over 25 years of project and program management experience across multiple industries. He has a master's degree from The George Washington University and a B.A. from the University of North Carolina Chapel Hill. Bruce currently runs his own freelance training and consulting business, helping project managers and team leaders improve their business skills, become better leaders, and achieve professional greatness. Bruce is a well-received speaker in the areas of design thinking, project management, cross-team collaboration, and AI tools for projects, and has presented at regional and international conferences. ### Steve Pesklo — Instructor Steve is an energetic trainer who focuses on applying technical concepts to everyday work practices. He is the founder and president of SoftLake Solutions, a company that specializes in providing data and AI applications to identify fraud for Internal Audit, Criminal Investigations, Forensic Accounting, Privacy, and Compliance. Steve brings a large amount of experience across multiple industries and government agencies. He is an expert in implementing large data analysis projects across the world, including Inland Revenue in the UK and Argentina, New Zealand, Africa and across Europe. Previously, he was the manager of Data Architecture and Data Services for a large mortgage company. He is a frequent speaker on data analytics and project management topics and speaks fluent German. He has been teaching at the Graduate School for over 10 years. Steve has an M.B.A. from the University of St. Thomas and a B.S. in Computer Science from California Lutheran University and the Universität Salzburg in Austria. He is certified as a Certified Fraud Examiner (CFE), Project Management Professional (PMP), and a Certified ScrumMaster (CSM). ### Brian Simms — Instructor Brian Simms is a seasoned educator and training leader with extensive experience developing and delivering innovative learning programs in project management and emerging technologies. Over the course of his career, he has designed adaptive learning models that combine instructor-led sessions, live online experiences, and self-paced study, ensuring professionals can access training in flexible and effective ways. His work has emphasized the integration of artificial intelligence into professional development, helping organizations and individuals understand how AI can be applied to solve real-world challenges in leadership, project execution, and decision-making. In addition to his instructional expertise, Brian has guided curriculum development, led large training initiatives, and advanced the use of collaboration tools that improve learner engagement and retention. His depth of experience and forward-looking perspective make him uniquely equipped to prepare federal professionals to navigate the complexities of data, project management, and the transformative potential of AI. ### Clarissa J. Corbin — Instructor Clarissa J. Corbin is an accomplished corporate trainer, project manager, and business consultant with over 25 years of experience designing and delivering impactful learning experiences. As President and CEO of Projections Training Solutions, she partners with federal agencies, private corporations, and international organizations to provide results-driven training in leadership, project management, business analysis, and emerging technologies. Clarissa has trained more than 10,000 professionals worldwide, serving clients such as the DoD, NASA, FEMA, Microsoft, Citibank, PNC Bank, Del Monte, and Symantec. Her expertise has taken her across the globe, leading initiatives in Singapore, China, Japan, South Korea, Africa, Jamaica, Trinidad & Tobago, and St. Thomas, USVI. Known for her ability to engage diverse audiences and create interactive, high-impact sessions, Clarissa equips participants with practical solutions they can apply immediately. At Graduate School USA (GSUSA), Clarissa is regarded as one of the most versatile and trusted instructors. She teaches across multiple programs. She played a pivotal role in redesigning the flagship “Managing for Results” course, while also contributing to the development and review of numerous others. Her contributions have earned her two GSUSA Customer Excellence Awards and a two-year appointment to the GSUSA Instructor Advisory Council, underscoring her commitment to innovation, quality, and learner success. ### Natalya H. Bah — Instructor Natalya Bah has been a part-time instructor at the Graduate School USA for over fifteen years. Natalya teaches across multiple curricula, including Leadership and Management, Project Management, and Human Resources. She has created a curriculum for the school, including Change Management Workshops and project management courses. She has served as an action learning coach, instructor, and facilitator for government leadership programs in the Center for Leadership and Management. Natalya also provides self-assessments and dynamic team-building sessions on behalf of the Graduate School USA. Outside of Graduate School USA, Ms. Bah is a self-employed business owner providing executive coaching, training, and consulting services to the public and private sectors. She created the Define and Achieve Your Goals Process™ and is a certified Birkman Method© Consultant. She received her Master of Science degree in Project Management from George Washington University’s School of Business, where she served as a teaching assistant and received the Project Management Award. She is also a certified Project Management Professional (PMP). ### Michiel Pruijssers Michiel is a Principal Designer and Forward Deployed Engineer at Microsoft's Industry Solutions Engineering Division, where he partners with strategic enterprise customers to architect and ship production AI systems. With over 15 years of experience, he operates at the intersection of user research, design, engineering, and cloud architecture, anchored by deep expertise in machine learning. His career spans senior roles at Snorkel AI, Determined.ai, and earlier Microsoft teams behind foundational AI products including LUIS.ai, Azure Bot Service, and Azure Stack, where he led both customer discovery and platform design for some of the industry's most technically ambitious ML offerings. He pairs rigorous qualitative research with hands-on building, shipping his own production SaaS products in Python while also teaching students through cohort-based AI courses. His instruction is grounded in real practice: what it takes to design, build, and operate AI systems that actually hold up in the wild. ## Pricing **Tuition:** $975