
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
Our AI for Research Ideation & Literature Exploration course is designed to help researchers generate, refine, and deepen their research ideas using generative AI. Whether you're developing a new proposal, exploring unfamiliar fields, or sharpening your research questions, this course provides practical strategies to support creativity, clarity, and efficiency. With structured modules and real-world prompts, you'll learn how to use AI not just to save time, but to think more critically and design stronger research from the start.

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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2
2.1 Using AI to Generate and Refine Research Topics
- 2.1.1 Leveraging Generative AI to Brainstorm and Develop Novel Research Questions Free preview
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2.1.2 How AI Helps Identify and Refine Research Topics by Analysing Existing Literature
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2.1.3 Real-Time Exploration of Emerging Topics Through AI-Driven Analysis
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2.1.4 Generating Innovative Research Questions with the Help of AI Assistants
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2.1.5 AI’s Role in Narrowing Down Broad Research Ideas into Focused Topics
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2.1.6 Key Takeaways
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2.1.7 Knowledge Check
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2.1.A Practical Use Cases
- 2.1.B Learning Activities Free preview
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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
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2.2 AI for Conducting Literature Reviews
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2.2.1 Using AI to Automatically Summarise Large Volumes of Academic Papers
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2.2.2 AI Tools for Identifying Key Themes, Methodologies, and Results in Literature
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2.2.3 How AI Simplifies the Process of Generating Comprehensive Literature Reviews Quickly
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2.2.4 Cross-Referencing Research Papers with AI Tools to Ensure Comprehensive Coverage
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2.2.5 How AI Helps with Literature Review Organisation and Documenting Findings
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2.2.6 Key Takeaways
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2.2.7 Knowledge Check
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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
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2.3 AI for Identifying Knowledge Gaps and Emerging Trends
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2.3.1 How Generative AI Detects Gaps in Research and Uncovers Areas for Further Exploration
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2.3.2 AI’s Ability to Forecast Emerging Research Topics by Analysing Citation Patterns
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2.3.3 Leveraging AI to Track the Evolution of Academic Fields and New Trends
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2.3.4 Using AI to Find Unexplored Areas Ripe for Investigation
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2.3.5 AI Tools for Staying Ahead in Rapidly Evolving Research Fields
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2.3.6 Key Takeaways
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2.3.7 Knowledge Check
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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
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2.4 Conversational AI for Literature Summarisation
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2.4.1 Using Conversational AI to Condense and Summarise Complex Academic Literature
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2.4.2 Best Practices for Employing AI to Summarise Findings Without Losing Critical Details
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2.4.3 Automating the Creation of Concise Literature Summaries for Quick Insights
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2.4.4 Cross-Checking AI-Generated Summaries for Accuracy and Completeness
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2.4.5 How AI Can Facilitate the Extraction of Actionable Insights from Literature
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2.4.6 Key Takeaways
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2.4.7 Knowledge Check
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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
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6
2.5 AI for Refining Research Questions and Hypotheses
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2.5.1 Using AI Tools to Refine and Develop Precise Research Questions
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2.5.2 Generating Testable Hypotheses with AI Assistance Based on Existing Research
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2.5.3 AI Tools for Adjusting Research Questions in Real Time Based on Emerging Data
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2.5.4 Collaborating with AI to Fine-Tune Research Focus
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2.5.5 Ensuring Research Questions Align with Current Academic Gaps Using AI Tools
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2.5.6 Key Takeaways
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2.5.7 Knowledge Check
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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
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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 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