
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 continuous curriculum improvement across review, mapping, and quality assurance workflows. You’ll learn how to visualise programme coherence, audit for equity and relevance, engage stakeholders with AI-powered tools, and build responsive QA systems that align with strategic goals. Through practical examples and guided exercises, you’ll gain confidence in embedding GenAI responsibly into curriculum evaluation and governance.

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
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1
Introduction
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2
7.1 Foundations of Curriculum Review in Higher Education
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7.1.1 Understanding QA Cycles and Curriculum Review Principles
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7.1.2 Common Gaps and Risks in Programme-Level Review
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7.1.3 Role of AI in Supporting Evidence-Informed Review Processes
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7.1.4 Aligning Internal QA with External Accreditation Bodies
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7.1.5 Building AI-Aware Review Frameworks for HE Institutions
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7.1.6 Key Takeaways
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7.1.A Practical Use Cases
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7.1.B Learning Activities
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7.1.C Prompt Templates
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7.1.D Innovative Use Cases
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7.1.E Reflection & Discussion
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7.1.F Productivity Tips
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7.1.G Prompt Library
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7.1.H Applying the GenAI Framework
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3
7.2 GenAI Tools for Curriculum Mapping and Visualisation
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7.2.1 Building Dynamic Curriculum Maps Using Generative Tools
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7.2.2 Mapping Programme Outcomes to Graduate Attributes with AI
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7.2.3 Identifying Skill Redundancies and Gaps Across Modules
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7.2.4 Visualising Curriculum Alignment with Strategic Goals
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7.2.5 Using GenAI to Generate QA Documentation and Narratives
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7.2.6 Key Takeaways
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7.2.A Practical Use Cases
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7.2.B Learning Activities
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7.2.C Prompt Templates
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7.2.D Innovative Use Cases
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7.2.E Reflection & Discussion
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7.2.F Productivity Tips
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7.2.G Prompt Library
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7.2.H Applying the GenAI Framework
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7.3 Auditing for Inclusivity, Innovation, and Relevance
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7.3.1 Using AI to Analyse Representation and Accessibility in Curriculum
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7.3.2 Identifying Outdated or Unaligned Content with GenAI
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7.3.3 Generative Reviews of Assessment Variety and Rigour
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7.3.4 Student Feedback Integration and Analysis Using AI
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7.3.5 Auditing Curricula for Innovation Readiness and Responsiveness
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7.3.6 Key Takeaways
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7.3.A Practical Use Cases
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7.3.B Learning Activities
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7.3.C Prompt Templates
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7.3.D Innovative Use Cases
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7.3.E Reflection & Discussion
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7.3.F Productivity Tips
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7.3.G Prompt Library
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7.3.H Applying the GenAI Framework
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7.4 Stakeholder Engagement in AI-Enhanced QA Processes
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7.4.1 AI Support for Curriculum Committees and Peer Review Panels
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7.4.2 Capturing Cross-Departmental Insights Through GenAI Summaries
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7.4.3 Integrating Employer and Industry Feedback with AI Tools
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7.4.4 Facilitating Evidence-Based Discussion Using AI-Generated Reports
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7.4.5 Building Transparent, Collaborative QA Workflows with AI
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7.4.6 Key Takeaways
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7.4.A Practical Use Cases
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7.4.B Learning Activities
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7.4.C Prompt Templates
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7.4.D Innovative Use Cases
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7.4.E Reflection & Discussion
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7.4.F Productivity Tips
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7.4.G Prompt Library
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7.4.H Applying the Framework in Practice
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7.5 Towards Continuous, Responsive Curriculum Quality
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7.5.1 Building Dashboards for Curriculum Performance Monitoring
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7.5.2 Moving from Periodic Review to Continuous Improvement with AI
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7.5.3 Creating Institutional Memory Through AI-Enabled Logs
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7.5.4 AI Support for Comparative Benchmarking Across Programmes
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7.5.5 From QA to Curriculum Foresight: Strategic Futures Thinking
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7.5.6 Key Takeaways
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7.5.A Practical Use Cases
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7.5.B Learning Activities
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7.5.C Prompt Templates
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7.5.D Innovative Use Cases
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7.5.E Reflection & Discussion
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7.5.F Productivity Tips
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7.5.G Prompt Library
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7.5.H Applying the GenAI Framework
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7
Final Lesson Message
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Course Complete: Share Your Feedback
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8
Feedback
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End of Course Survey
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Unlock Your Genai Potential
Join our course today and unlock the full potential of Generative AI in your research projects. Empower yourself with the knowledge and skills to drive innovation and make a significant impact in your field.
£97.00