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

Foundations of Conversational AI for Research is designed to help researchers use generative tools like ChatGPT with clarity, creativity, and confidence. You’ll explore the strengths and limitations of AI, learn how to craft effective prompts, and apply critical thinking to verify and refine outputs. Through five structured modules, this course builds your practical skills in using AI to support literature reviews, research design, communication, and more—without compromising quality or academic integrity.

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

8 Chapters · 69 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

    1.1 What is Generative AI and How Can It Assist in Research?

    1. 1.1.1 Introduction to Generative AI Tools and Their Role in Academic Research Free preview
    2. 1.1.2 Distinguishing Between Rule-Based Systems and Generative AI Assistants Free preview
    3. 1.1.3 Key Features of Conversational AI and How It Enhances Research Workflows Free preview
    4. 1.1.4 Benefits of Generative AI: Speed, Accessibility, Automation, and Creativity Free preview
    5. 1.1.5 Key Takeaways Free preview
    6. 1.1.6 Knowledge Check Free preview
    7. 1.1.A Practical Use Cases Free preview
    8. 1.1.B Learning Activities Free preview
    9. 1.1.C Prompt Templates Free preview
    10. 1.1.D Innovative Use Cases Free preview
    11. 1.1.E Reflection & Discussion Free preview
    12. 1.1.F Productivity Tips Free preview
  3. 3

    1.2 Understanding AI Strengths, Weaknesses, and Biases

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      1.2.1 Advantages of Generative AI in Accelerating Research Processes

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      1.2.2 Common Limitations – Biases, Hallucinations, and Lack of Reasoning

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      1.2.3 Ethical Concerns – Misinformation, Privacy, and Data Misuse Risks

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      1.2.4 Managing Misinformation and Ensuring Accurate Outputs in Research Contexts

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      1.2.5 Strategies to Mitigate AI Weaknesses and Biases in Academic Work

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      1.2.6 Key Takeaways

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      1.2.7 Knowledge Check

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      1.2.A Practical Use Cases

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      1.2.B Learning Activities

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      1.2.C Prompt Templates

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      1.2.D Innovative Use Cases

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      1.2.E Reflection & Discussion

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      1.2.F Productivity Tips

  4. 4

    1.3 Effective Prompting: Getting the Most from Generative AI

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      1.3.1 Techniques for Crafting Precise and Effective Prompts for AI

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      1.3.2 Iterative Prompt Refinement for Optimised AI Responses

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      1.3.3 Best Practices for AI–Human Collaboration in Research Activities

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      1.3.4 Common Mistakes in Prompting and How to Avoid Them

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      1.3.5 Practical Examples of Prompt Crafting for Various Research Needs

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      1.3.6 Key Takeaways

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      1.3.7 Knowledge Check

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      1.3.A Practical Use Cases

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      1.3.B Learning Activities

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      1.3.C Prompt Templates

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      1.3.D Innovative Use Cases

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      1.3.E Reflection & Discussion

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      1.3.F Productivity Tips

  5. 5

    1.4 Critical Thinking with AI: Trust but Verify

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      1.4.1 Evaluating the Credibility and Accuracy of AI-Generated Content

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      1.4.2 How to Cross-Check AI Outputs with Primary Sources and Peer-Reviewed Literature

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      1.4.3 Managing Contradictions in AI Outputs: Recognising Hallucinations and Inconsistencies

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      1.4.4 Incorporating Human Expertise in Validating AI-Generated Research Findings

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      1.4.5 Building a Culture of Critical Thinking in AI-Assisted Academic Workflows

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      1.4.6 Key Takeaways

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      1.4.7 Knowledge Check

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      1.4.A Practical Use Cases

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      1.4.B Learning Activities

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      1.4.C Prompt Templates

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      1.4.D Innovative Use Cases

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      1.4.E Reflection & Discussion

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      1.4.F Productivity Tips

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    1.5 Integrating AI into Daily Academic Workflows

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      1.5.1 Practical Uses of Generative AI in Everyday Research Activities

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      1.5.2 Automating Repetitive Tasks Like Citation Management and Document Formatting

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      1.5.3 Enhancing Collaboration with AI for Brainstorming and Refining Research Questions

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      1.5.4 Using AI for Data Collection and Synthesis in Large Research Projects

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      1.5.5 Streamlining the Writing and Editing Process with AI-Driven Tools

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      1.5.6 Key Takeaways

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      1.5.7 Knowledge Check

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      1.5.A Practical Use Cases

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      1.5.B Learning Activities

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      1.5.C Prompt Templates

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      1.5.D Innovative Use Cases

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      1.5.E Reflection & Discussion

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      1.5.F Productivity Tips

  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 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

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