
Hands-On Learning
Apply generative AI to real research tasks with guided prompts, use cases, and interactive activities.

Research-Focused Instruction
Learn from in-depth, interdisciplinary examples rooted in academic and applied research practice.

Flexible, Self-Paced Study
Work through structured lessons at your own pace, with tools to support your current research projects.
About the Course
This course on AI for Research Collaboration & Knowledge Management is designed to help researchers harness generative AI to support teamwork, idea development, and shared learning. Whether you’re coordinating across disciplines, refining research questions, or managing group notes and feedback, this course offers hands-on guidance and real-world examples. Gain the skills to use AI responsibly and effectively in collaborative settings—and strengthen your research through smarter, more connected workflows.

Meet Your Instructor
I'm Jonathan Wong, a Lead AI Scientist and researcher specialising in medical diagnostics, data science, and advanced research technologies. My work focuses on applying generative AI and machine learning to improve healthcare outcomes and support complex research workflows. In this course, I share practical tools, ethical strategies, and real-world insights developed through applied experience in research and development. Whether you're just beginning or looking to deepen your skills, you'll find structured guidance to help you use AI effectively, creatively, and responsibly in your research practice.
Curriculum
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1
Introduction
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9.1 AI as a Collaborative Thinking Partner
- 9.1.1 How AI Can Facilitate Collaboration and Idea Generation in Research Teams Free preview
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9.1.2 Leveraging Generative AI for Brainstorming and Innovation in Team Settings
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9.1.3 Using AI Tools to Enhance Communication and Knowledge Sharing in Research Groups
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9.1.4 AI’s Role in Supporting Cross-Disciplinary Collaboration and Fostering New Insights
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9.1.5 How AI Can Act as a Virtual Research Partner in Academic Projects
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9.1.6 Key Takeaways
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9.1.7 Knowledge Check
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9.1.A Practical Use Cases
- 9.1.B Learning Activities Free preview
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9.1.C Prompt Templates
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9.1.D Innovative Use Cases
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9.1.E Reflection & Discussion
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9.1.F Productivity Tips
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9.2 AI for Refining Research Questions and Hypotheses in Teams
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9.2.1 Collaborating with AI to Generate and Refine Research Questions in Team Settings
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9.2.2 How AI Tools Can Help Generate Diverse Hypotheses Based on Team Discussions
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9.2.3 Using AI for Dynamic Hypothesis Testing as a Group
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9.2.4 Enhancing Team Discussions with AI-Driven Insights and Data-Driven Suggestions
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9.2.5 AI’s Role in Supporting Consensus-Building in Research Teams
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9.2.6 Key Takeaways
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9.2.7 Knowledge Check
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9.2.A Practical Use Cases
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9.2.B Learning Activities
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9.2.C Prompt Templates
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9.2.D Innovative Use Cases
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9.2.E Reflection & Discussion
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9.2.F Productivity Tips
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9.3 Managing Research Notes and Ideas with AI
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9.3.1 Using AI Tools to Organise and Categorise Research Notes, Data, and Ideas
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9.3.2 Automating the Capture and Retrieval of Research Materials with Generative AI
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9.3.3 How AI-Driven Knowledge Management Systems Can Improve Efficiency and Access to Research Content
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9.3.4 AI Tools for Managing Collaborative Research Materials in Real-Time
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9.3.5 Ensuring Data Security and Privacy When Using AI-Based Systems to Manage Research Ideas
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9.3.6 Key Takeaways
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9.3.7 Knowledge Check
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9.3.A Practical Use Cases
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9.3.B Learning Activities
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9.3.C Prompt Templates
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9.3.D Innovative Use Cases
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9.3.E Reflection & Discussion
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9.3.F Productivity Tips
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9.4 AI for Cross-Disciplinary Knowledge Integration
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9.4.1 AI Tools for Facilitating Cross-Disciplinary Research by Integrating Knowledge from Different Fields
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9.4.2 Using Generative AI to Synthesise Information Across Multiple Disciplines
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9.4.3 Enhancing Interdisciplinary Collaboration with AI-Driven Insights across Diverse Research Domains
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9.4.4 The Role of Generative AI in Tackling Complex, Multi-Disciplinary Research Challenges
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9.4.5 AI as a Tool for Building Bridges Between Academic Silos and Fostering Collaborative Research
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9.4.6 Key Takeaways
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9.4.7 Knowledge Check
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9.4.A Practical Use Cases
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9.4.B Learning Activities
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9.4.C Prompt Templates
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(Included in full purchase)
9.4.D Innovative Use Cases
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9.4.E Reflection & Discussion
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9.4.F Productivity Tips
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9.5 Conversational AI for Peer Review and Research Feedback
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9.5.1 Using Conversational AI to Support and Streamline Peer Review Processes
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9.5.2 Enhancing the Quality and Efficiency of Feedback Through AI-Driven Systems
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9.5.3 How AI Can Detect Biases and Errors in Peer-Reviewed Manuscripts
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9.5.4 Using AI to Streamline the Peer Review Workflow and Manage Reviewer Comments
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9.5.5 AI’s Role in Ensuring Fairness and Objectivity in the Peer Review Process
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9.5.6 Key Takeaways
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9.5.7 Knowledge Check
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9.5.A Practical Use Cases
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(Included in full purchase)
9.5.B Learning Activities
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(Included in full purchase)
9.5.C Prompt Templates
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(Included in full purchase)
9.5.D Innovative Use Cases
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(Included in full purchase)
9.5.E Reflection & Discussion
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(Included in full purchase)
9.5.F Productivity Tips
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Final Lesson Message
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Course Complete: Share Your Feedback
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Feedback
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End of Course Survey
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Unlock Your Research 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