Hands-On Learning

Simulate real-world teaching and institutional scenarios with guided AI prompts, case studies and interactive activities.

Education-Focused Insights

Explore best practices and real examples of AI integration in pedagogy, curriculum design and student support.

Flexible, Self-Paced Learning

Work through structured, on-demand modules at your own pace, with resources tailored to your teaching and leadership goals.

About the Course

Design curricula and learning outcomes hand-in-hand with generative AI: in this course, you’ll explore how to map your programme goals to AI-enhanced strategies, sequence and scaffold modules for optimal progression, and co-create clear, measurable objectives and syllabi. You’ll also learn to embed graduate attributes and future-proof skills using AI prompts, while ensuring your curriculum planning remains inclusive and ethically grounded. Whether you’re designing a single course or an entire programme, you’ll come away with practical workflows for AI-supported curriculum design.

Meet Your Instructor

I'm Jonathan Wong, Founder of CloudPedagogy, Lead AI Educator, and research and innovation strategist with over 20 years in higher education and research, specialising in data science, AI, and advanced cloud technologies. My work focuses on applying generative AI to enhance teaching, research, and institutional operations, build intelligent AI systems, and advance ethical AI governance. In this course, I share practical frameworks, hands-on tools, and sector-specific examples developed through applied work in higher education and research. Whether you're starting your AI journey or aiming to deepen your expertise, you'll gain the skills and strategies to apply AI effectively, creatively, and responsibly in your professional context.

Curriculum

9 Chapters · 66 Lessons

  1. 1

    Introduction

    1. Welcome to the Course Free preview
    2. How This Course Works Free preview
    3. Legal Disclaimer & Terms of Use Free preview
  2. 2

    2.1 Mapping Curriculum Goals to AI-Supported Strategies

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      2.1.1 Aligning Curriculum with Strategic Priorities

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      2.1.2 Embedding Employability through Market Scanning

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      2.1.3 Visualising Curriculum Structures and Gaps

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      2.1.4 Co-Designing with Stakeholders Using Generative AI

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      2.1.5 Persona Simulation and Curriculum Testing

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      2.1.6 Key Takeaways

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      2.1.A Practical Use Cases

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      2.1.B Learning Activities

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      2.1.C Prompt Templates

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      2.1.D Innovative Use Cases

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      2.1.E Reflection & Discussion

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      2.1.F Productivity Tips

  3. 3

    2.2 AI for Programme-Level Design: Sequencing, Scaffolding, and Outcomes

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      2.2.1 Foundations of Programme-Level Thinking with Generative AI

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      2.2.2 Simulating Multiple Learner Pathways

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      2.2.3 Scaffolding and Feedback Loops Across Programmes

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      2.2.4 Visualising Whole-of-Programme Design

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      2.2.5 Embedding Ethical and Transversal Competencies

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      2.2.6 Key Takeaways

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      2.2.A Practical Use Cases

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      2.2.B Learning Activities

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      2.2.C Prompt Templates

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      2.2.D Innovative Use Cases

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      2.2.E Reflection & Discussion

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      2.2.F Productivity Tips

  4. 4

    2.3 Co-Creating Learning Objectives and Syllabi with AI

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      2.3.1 Reframing Curriculum Design through Backward Planning and AI

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      2.3.2 Enhancing Learning Objectives Using Taxonomies and AI Prompt Calibration

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      2.3.3 AI-Facilitated Co-Design with Students: Towards Participatory Syllabi

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      2.3.4 Creating Localised and Inclusive Syllabi for Global Learners

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      2.3.5 Embedding Reflective Prompts and AI Engagement into the Syllabus

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      2.3.6 Key Takeaways

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      2.3.A Practical Use Cases

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      2.3.B Learning Activities

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      2.3.C Prompt Templates

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      2.3.D Innovative Use Cases

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      2.3.E Reflection & Discussion

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      2.3.F Productivity Tips

  5. 5

    2.4 Embedding Graduate Attributes and Future Skills Using AI

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      2.4.1 Identifying Future-Facing Graduate Attributes with AI

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      2.4.2 Mapping Graduate Attributes Across Modules and Programmes

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      2.4.3 Personalising Graduate Attribute Development Through AI

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      2.4.4 Embedding Future Skills in Learning and Assessment

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      2.4.5 Tracking and Evidencing Graduate Impact Over Time

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      2.4.6 Key Takeaways

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      2.4.A Practical Use Cases

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      2.4.B Learning Activities

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      2.4.C Prompt Templates

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      2.4.D Innovative Use Cases

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      2.4.E Reflection & Discussion

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      2.4.F Productivity Tips

  6. 6

    2.5 Inclusive and Ethical Curriculum Planning Using AI Prompts

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      2.5.1 Rethinking Inclusion in Curriculum Design

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      2.5.2 Prompting for Equity: The Power of Structured Inquiry

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      2.5.3 Designing for Neurodiversity and Cognitive Inclusion

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      2.5.4 Auditing Course Content with AI Support

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      2.5.5 Co-Creation and Student-Led AI Interventions

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      2.5.6 Key Takeaways

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      2.5.A Practical Use Cases

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      2.5.B Learning Activities

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      2.5.C Prompt Templates

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      2.5.D Innovative Use Cases

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      2.5.E Reflection & Discussion

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      2.5.F Productivity Tips

  7. 7

    Knowledge Check (Coming Soon!)

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      Knowledge Check: Quiz

  8. 8

    Final Lesson Message

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      Course Complete: Share Your Feedback

  9. 9

    Feedback

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      End of Course Survey

Unlock Your Genai Potential

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