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

Our Template Course for Generative AI in Research is meticulously crafted to equip researchers with the knowledge and skills needed to excel in the field. Whether you are new to Generative AI or looking to deepen your expertise, this course offers a comprehensive curriculum and practical insights to support your research endeavors. Join us and embark on a transformative learning journey that will elevate your research capabilities.

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

    6.1 Foundations of Interdisciplinary Curriculum Design

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      6.1.1 Key Principles and Terminology in Interdisciplinarity

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      6.1.2 Challenges and Opportunities in Programme-Level Integration

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      6.1.3 Curriculum Models for Interdisciplinary Learning

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      6.1.4 Role of GenAI in Identifying Thematic and Conceptual Links

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      6.1.5 Designing Shared Learning Outcomes Across Disciplines

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      6.1.6 Key Takeaways

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      6.1.A Practical Use Cases

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      6.1.B Learning Activities

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      6.1.C Prompt Templates

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      6.1.D Innovative Use Cases

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      6.1.E Reflection & Discussion

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      6.1.F Productivity Tips

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      6.1.G Prompt Library

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      6.1.H Applying the GenAI Framework

  3. 3

    6.2 Facilitating Cross-Departmental Collaboration with GenAI

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      6.2.1 Using AI to Synthesize Inputs from Diverse Academic Teams

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      6.2.2 Co-Creating Interdisciplinary Rubrics and Learning Activities

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      6.2.3 AI Support for Curriculum Alignment Across Faculties

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      6.2.4 Visualising Overlaps and Gaps Between Disciplines

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      6.2.5 Moderating Language and Epistemology Differences with AI Tools

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      6.2.6 Key Takeaways

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      6.2.A Practical Use Cases

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      6.2.B Learning Activities

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      6.2.C Prompt Templates

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      6.2.D Innovative Use Cases

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      6.2.E Reflection & Discussion

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      6.2.F Productivity Tips

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      6.2.G Prompt Library

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      6.2.H Applying the GenAI Framework

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    6.3 Building Flexible Pathways Across Faculties

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      6.3.1 AI-Supported Design of Electives and Minors with Thematic Cohesion

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      6.3.2 GenAI for Mapping Student-Created Interdisciplinary Programmes

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      6.3.3 Enabling Transitions Between Disciplines Through Microcredentials

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      6.3.4 Co-Designing Interdisciplinary Modules with Students and AI

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      6.3.5 Ensuring Assessment Validity in Interdisciplinary Programmes

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      6.3.6 Key Takeaways

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      6.3.A Practical Use Cases

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      6.3.B Learning Activities

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      6.3.C Prompt Templates

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      6.3.D Innovative Use Cases

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      6.3.E Reflection & Discussion

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      6.3.F Productivity Tips

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      6.3.G Prompt Library

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      6.3.H Applying the GenAI Framework

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    6.4 Industry and Societal Challenge-Based Integration

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      6.4.1 Using GenAI to Translate Global Challenges into Curriculum Themes

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      6.4.2 Embedding Real-World Problem Solving in Programme Design

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      6.4.3 AI Tools for Facilitating External Co-Design with Industry Experts

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      6.4.4 Mapping UN SDGs and Societal Goals onto Curriculum Content

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      6.4.5 Designing Experiential Interdisciplinary Projects with GenAI

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      6.4.6 Key Takeaways

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      6.4.A Practical Use Cases

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      6.4.B Learning Activities

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      6.4.C Prompt Templates

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      6.4.D Innovative Use Cases

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      6.4.E Reflection & Discussion

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      6.4.F Productivity Tips

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      6.4.G Prompt Library

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      6.4.H Applying the Framework in Practice

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    6.5 Sustaining and Evolving Interdisciplinary Programmes

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      6.5.1 Institutional Strategies for Supporting Interdisciplinary Teaching

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      6.5.2 Building Communities of Practice Across Faculties with AI Tools

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      6.5.3 Evaluating Programme Impact Across Disciplinary Lines

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      6.5.4 Leveraging GenAI for Continuous Redesign and Feedback Loops

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      6.5.5 Planning for Growth and Curriculum Complexity with AI Modelling

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      6.5.6 Key Takeaways

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      6.5.A Practical Use Cases

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      6.5.B Learning Activities

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      6.5.C Prompt Templates

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      6.5.D Innovative Use Cases

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      6.5.E Reflection & Discussion

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      6.5.F Productivity Tips

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      6.5.G Prompt Library

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      6.5.H Applying the GenAI Framework

  7. 7

    Final Lesson Message

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      Course Complete: Share Your Feedback

  8. 8

    Feedback

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      End of Course Survey

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.

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