Hands-On Learning

Gain practical experience through hands-on projects and real-world applications.

Expert Guidance

Learn from industry experts with years of experience in Generative AI research.

Flexible Schedule

Study at your own pace with our online platform, allowing you to balance work and learning effectively.

About the Course

This course explores how generative AI can support the design and delivery of personalised curriculum pathways in higher education. You’ll examine how to build modular, flexible programme structures, respond to diverse learner profiles, and integrate AI-powered guidance tools to support student decision-making. Designed for academic leaders, course designers, and learning technologists, this course blends strategic insight with hands-on practice to help you personalise learning at scale — responsibly and effectively.

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

8 Chapters · 75 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

    5.1 Foundations of Personalised Learning in Higher Education

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      5.1.1 Principles and Benefits of Personalised Curriculum Design

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      5.1.2 Challenges of Scaling Personalisation in Traditional Systems

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      5.1.3 GenAI’s Role in Supporting Adaptive Learning Journeys

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      5.1.4 Balancing Flexibility and Structure in Programme Design

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      5.1.5 Case Examples of Personalisation in Higher Education

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      5.1.6 Key Takeaways

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      5.1.A Practical Use Cases

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      5.1.B Learning Activities

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      5.1.C Prompt Templates

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      5.1.D Innovative Use Cases

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      5.1.E Reflection & Discussion

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      5.1.F Productivity Tips

    13. (Included in full purchase)

      5.1.G Prompt Library

    14. (Included in full purchase)

      5.1.H Applying the GenAI Framework

  3. 3

    5.2 Designing Modular and Flexible Programme Structures

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      5.2.1 Creating AI-Supported Curriculum Maps for Student Choice

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      5.2.2 GenAI for Dynamic Credit and Microcredential Planning

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      5.2.3 Building Optionality Without Compromising Coherence

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      5.2.4 Using AI to Visualise Pathways and Prerequisite Structures

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      5.2.5 Designing for Vertical and Horizontal Integration of Content

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      5.2.6 Key Takeaways

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      5.2.A Practical Use Cases

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      5.2.B Learning Activities

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      5.2.C Prompt Templates

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      5.2.D Innovative Use Cases

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      5.2.E Reflection & Discussion

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      5.2.F Productivity Tips

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      5.2.G Prompt Library

    14. (Included in full purchase)

      5.2.H Applying the GenAI Framework

  4. 4

    5.3 Supporting Diverse Learner Profiles Through AI

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      5.3.1 Using GenAI to Identify Learning Preferences and Needs

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      5.3.2 Designing for Neurodiversity and Access Needs Using AI Insights

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      5.3.3 Multilingual Curriculum Support and Personalisation Tools

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      5.3.4 Cultural Responsiveness and Adaptive Content Creation

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      5.3.5 AI for Tailoring Support Services in Curriculum Contexts

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      5.3.6 Key Takeaways

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      5.3.A Practical Use Cases

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      5.3.B Learning Activities

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      5.3.C Prompt Templates

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      5.3.D Innovative Use Cases

    11. (Included in full purchase)

      5.3.E Reflection & Discussion

    12. (Included in full purchase)

      5.3.F Productivity Tips

    13. (Included in full purchase)

      5.3.G Prompt Library

    14. (Included in full purchase)

      5.3.H Applying the GenAI Framework

  5. 5

    5.4 Automating Guidance and Student Decision-Making Tools

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      5.4.1 GenAI-Driven Curriculum Recommendation Engines

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      5.4.2 Interactive Syllabi and Course Selection Aids

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      5.4.3 Personalised Timetabling and Learning Plan Generators

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      5.4.4 Conversational AI for Academic Advising and Progress Review

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      5.4.5 Managing Ethical Risks in AI-Powered Student Guidance

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      5.4.6 Key Takeaways

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      5.4.A Practical Use Cases

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      5.4.B Learning Activities

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      5.4.C Prompt Templates

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      5.4.D Innovative Use Cases

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      5.4.E Reflection & Discussion

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      5.4.F Productivity Tips

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      5.4.G Prompt Library

    14. (Included in full purchase)

      5.4.H Applying the Framework in Practice

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    5.5 Evaluation and Scalability of Personalised Programmes

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      5.5.1 Measuring Engagement and Success in Personalised Pathways

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      5.5.2 AI-Supported Monitoring of Learner Progress Over Time

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      5.5.3 Addressing Institutional Challenges in Scaling Personalisation

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      5.5.4 Building Infrastructure for Sustainable Personalised Learning

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      5.5.5 Future Trends in AI-Enabled Personalised HE Curricula

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      5.5.6 Key Takeaways

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      5.5.A Practical Use Cases

    8. (Included in full purchase)

      5.5.B Learning Activities

    9. (Included in full purchase)

      5.5.C Prompt Templates

    10. (Included in full purchase)

      5.5.D Innovative Use Cases

    11. (Included in full purchase)

      5.5.E Reflection & Discussion

    12. (Included in full purchase)

      5.5.F Productivity Tips

    13. (Included in full purchase)

      5.5.G Prompt Library

    14. (Included in full purchase)

      5.5.H Applying the GenAI Framework

  7. 7

    Final Lesson Message

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      Course Complete: Share Your Feedback

  8. 8

    Feedback

    1. (Included in full purchase)

      End of Course Survey

Unlock Your Genai Potential

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