AI Upskilling
Project
A quick request to update a few AI courses evolved into a rich design challenge that pushed me to rethink what effective AI education should look and feel like. Here’s the story of how four of my AI upskilling courses were built and the impact they continue to make.
Teaches HR and L&D professionals how to use AI and analytics to personalize training, improve performance, and build ethical, future-focused talent strategies.
Empowers professionals to apply generative AI to real workplace challenges, improving decision-making, collaboration, and operations—no technical background required.
Upskills educators to build AI-driven strategies that enhance instructional design, deepen student engagement, and close feedback loops across the higher ed ecosystem.
Guides educators in applying AI tools confidently and responsibly to transform lesson planning, assessment, and student learning in modern classrooms.
Context
ASU launched a university-wide initiative to upskill learners around the world in AI—an effort spanning faculty, staff, and professionals across industries. As part of this vision, the Learning Enterprise asked me to elevate several existing asynchronous AI courses to better support learners seeking practical, workforce-aligned AI skills. What began as a quick refresh assignment quickly evolved into a multi-month redesign, giving me the opportunity to reimagine how ASU teaches AI and to set a new standard for high-quality, future-ready AI education.
Challenge
As I evaluated the existing courses, it became clear they needed more than light updates. While a few concepts could be carried over, the courses lacked up-to-date AI content, meaningful skill-building, workforce relevance, modern UX design, or any sort of compelling portfolio artifact. They also didn’t currently reflect ASU’s aspirations for innovative asynchronous learning. The challenge quickly grew from polishing some content to absolutely rethinking the entire learning experience—transforming something unusable into something truly future and workforce-ready.
Role
I served as the architect and lead for the full redesign of the AI courses—guiding the learning experience strategy, instructional approach, UX vision, and content overhaul. I collaborated closely with instructional and graphic designers, marketing partners, and product teams, while also leveraging ASU’s partnership with OpenAI to integrate premium ChatGPT into both the course design process and the learning experience itself. My role spanned research, vision-setting, prototyping, cross-team coordination, and ensuring the final products met the university’s goals for ethical, effective, high-impact education.
Process
Once the need for a full redesign was clear, I shifted into building a new instructional architecture for the courses. I defined core learning outcomes, mapped skill progression across modules, and designed a consistent experience model that could flex across different audiences while maintaining shared design principles.
From there, I collaborated closely with instructional designers, visual designers, and technical partners to prototype activities, assessments, and AI-enabled workflows. Each course was developed iteratively, with regular checkpoints to refine learning flow, UX patterns, and the balance between instruction, practice, and reflection. The focus was on creating experiences learners could actively engage with—not just content to move through.
Solution
The final solution was a fully redesigned suite of four AI courses built around a shared instructional philosophy: AI is not just a topic to learn about—it’s a collaboration partner learners actively work with throughout the experience.
Each course was rebuilt with a clear learning arc that blends concept-building, guided practice, reflection, and applied project work. Learners engage with AI tools continuously—using them to explore ideas, generate drafts, test assumptions, and refine their thinking—while also learning how to evaluate outputs critically and ethically. To support this, I designed an AI-powered feedback grader that provides learners with immediate, structured feedback on their project work, reinforcing learning in real time and modeling how AI can support—not replace—human judgment.
Reflection is embedded throughout the experience via a guided learning journal, prompting learners to pause, make meaning, and articulate how AI is shaping their thinking, decisions, and professional practice. This combination of collaboration, feedback, and reflection transforms AI from a passive tool into an active learning partner.
Each course now includes…
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Up-to-date AI concepts contextualized for distinct audiences (higher education, K–12, workplace, HR/L&D)
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Hands-on activities and practice prompts grounded in real-world use cases
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AI-as-collaborator workflows embedded across modules
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An AI-powered feedback grader delivering immediate, formative feedback on project work
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Ethics and risk-assessment frameworks woven throughout the learning journey
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A capstone artifact (e.g., AI Teaching & Engagement Strategy, AI Talent Strategy Plan) learners can use beyond the course
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Clear UX patterns that reduce cognitive load and support intuitive navigation
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Modern visual and instructional design aligned with ASU brand and accessibility standards
Impact
My redesigned AI learning suite has become a cornerstone of ASU’s broader AI upskilling efforts. Nancy Gonzales, Executive Vice President and University Provost, has made the courses available at no cost to all ASU staff, signaling strong institutional confidence in their quality and relevance.
The Learning Enterprise has since incorporated the courses into its organizational OKRs, using them to support AI upskilling across the enterprise. Learner feedback reflected increased confidence, clarity, and readiness to apply AI in real work contexts—supported by hands-on practice, immediate feedback, and portfolio-ready artifacts. Together, these outcomes helped establish a new standard for scalable, ethical, and applied AI education at ASU.