About the Course

Equip yourself with the essential knowledge and practical skills to navigate the transformative world of generative AI responsibly and ethically.  This course integrates the requirements of Saudi Arabia's Personal Data Protection Law (PDPL) and medical ethics with global best practices. Learn to distinguish safe uses, design culturally grounded prompts, validate outputs, and implement privacy controls using sovereign infrastructure. Generative AI is already in your hospital, the question is whether your team is using it safely. This course gives every healthcare professional the knowledge and hands-on skills to interact with AI tools responsibly: understanding their limits, protecting patient data, and following PDPL-compliant workflows aligned with SDAIA, NHIC, and MoH standards.

For Every Healthcare Professional

Learn how tools like ChatGPT, Claude, and Grok work, their healthcare applications, and the ethical principles guiding responsible AI use. Master the practical skills: crafting bilingual, anonymized prompts, applying clinical guardrails, and reviewing outputs before they reach patients.

Craft Safe AI Prompts

Whether you're a nurse, physician, administrator, or quality officer, learn why AI literacy is now a professional requirement, not an optional skill. Demonstrate crafting safe, de-identified AI prompts, evaluate outputs for accuracy and compliance, and apply workflows in non-clinical hospital tasks.

Maintain Patient Confidentiality

Recognize boundaries between AI support and clinical judgment, maintain patient confidentiality, and cultivate a responsible, security-aware mindset in healthcare. Walk through six real-world scenarios, from accidental data leaks to biased outputs, with step-by-step PDPL-mandated response protocols.

Course Curriculum

6 Chapters · 84 Lessons

  1. 1

    Introduction & Purpose

    1. (Included in full purchase)

      Introduction & Purpose

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      Introduction

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      The Civilizational Context: AI in Service of Vision 2030 and Islamic Values

    4. (Included in full purchase)

      The Legal Architecture: PDPL as the Foundation of Digital Trust

    5. (Included in full purchase)

      Institutional Oversight: The Triad of Governance (MoH, SDAIA, NHIC)

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      Landscape of the AI ecosystem in Saudi Arabia

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      The Professional Covenant: Judgment Over Automation

    8. (Included in full purchase)

      Why Courses Like This Are Not Optional

    9. (Included in full purchase)

      The Global Context: Saudi Arabia in the International AI Landscape

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      Policy Horizons

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      Conceptual Framework: The Three Pillars of Responsible AI in Saudi Healthcare

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      Global Case Study: Lessons from the Field & Policy Horizon

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      References

    14. (Included in full purchase)

      Assessment # 1

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      Assessment # 2

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      Discussion: How does the concept of amanah (trust) shape our approach to AI?

  2. 2

    What are online generative AI tools (ChatGPT example)?

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      Basic concept, capabilities, and limits

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      Why Healthcare Professionals Need Technical Clarity

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      What is Generative AI

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      What Is Generative AI? A Working Definition

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      How ChatGPT Works: A Simplified Technical Overview

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      Core Capabilities of Generative AI in Healthcare Contexts

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      Critical Limitations and Risks

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      Free vs. Enterprise AI: A Critical Distinction

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      Other Major Generative AI Tools: A Brief Overview

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      Conceptual Framework: The AI Capability-Limit Matrix

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      Policy Horizon

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      Discussion Prompts for Teams

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      References

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      Assessment # 3

    15. (Included in full purchase)

      Assessment # 4

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      Open Response Discussion: How can we ensure our prompts are inclusive of women and rural patients?

  3. 3

    Prompting Best Practices

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      Writing safe, effective prompts and reviewing outputs

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      Prompt Design as a First Line of Defence

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      Foundational Principles of Safe and Effective Prompting

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      Practical Example: Bilingual Hypertension Leaflet

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      Iterative Prompt Refinement

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      Advanced Prompting Strategies from Global Health Systems

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      Chain-of-Thought Prompting

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      AI Safety: Governance Perspective

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      Conceptual Framework: The Prompt Lifecycle

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      Global Case Studies: Lessons from the Field

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      Policy Horizon and Implementation Plan

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      Policy Horizon

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      Discussion Prompts for Teams and Implementation Tools

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      References

    15. (Included in full purchase)

      Assessment # 5

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      Assessment # 6

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      Open Response Discussion: How can we create a "just culture" for reporting AI near-misses?

  4. 4

    Common Risks & Mitigation “What if” scenarios and how to respond

    1. (Included in full purchase)

      Global Shift Towards Proactive Al Risk Management

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      Anticipating Risk as a Professional Duty

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      Risk Scenarios in Healthcare

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      Scenario 1: Accidental Input of Patient Data

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      Scenario 2: AI Generates Medically Incorrect or Misleading Advice

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      Scenario 3: AI Output Contains Culturally or Religiously Inappropriate Content

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      Scenario 4: AI Vendor Stores or Processes Data Outside Saudi Arabia

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      Scenario 5: AI Output Is Used Without Human Review

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      Scenario 6: AI Generates Content That Reinforces Health Inequities or Systemic Bias

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      AI Risk Prioritization Matrix

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      Conceptual Framework: The AI Risk Matrix

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      Policy Horizon: Emerging Regulatory Trends

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      Discussion Prompts

    14. (Included in full purchase)

      Discussion Prompts for Teams

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      References

    16. (Included in full purchase)

      Assessment # 7

    17. (Included in full purchase)

      Assessment # 8

    18. (Included in full purchase)

      Open Response Discussion: What is our biggest AI security gap, and how can we close it?

  5. 5

    Safe Workflow Example Walkthrough of a real, compliant use case

    1. (Included in full purchase)

      Global BesIntroduction: From Theory to Practicet Practices in AI Ethics

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      Output Validation Protocol

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      Prompt Crafting: Precision, Localization, Constraints

    4. (Included in full purchase)

      The Use Case: Bilingual Wound Care Leaflet for Adult Surgical Patients

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      Five Step Validation Process

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      Output Validation , The Five-Layer Review and Approvals

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      Post-Deployment Monitoring

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      Output Validation Protocol Summary

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      Global Case Studies & Conceptual Framework: The Al Workflow Lifecycle

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      Policy Horizons

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      Policy Horizon: Scaling the Workflow Nationally

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      Discussion & Implementation Tools

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      Section References & Further Reading

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      Assessment # 9

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      Assessment # 10

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      Open Response Discussion: How can we ensure our workflows respect regional diversity?

  6. 6

    Zero-retention Sandbox Environment

    1. (Included in full purchase)

      AI Governance Sandbox Web Application

Meet Your Instructor

Dr. Ibrahim El-Chami is a researcher and technology entrepreneur with a PhD in sensors microfabrication for IoT and edge AI for sustainable smart city applications.  He completed postdoctoral research at the University of British Columbia as a part of the Rogers-UBC smart 5G campus.  Ibrahim advises governments on advancing responsible AI governance with a focus on agentic and embodied AI. He has authored AI governance frameworks for Canada, the EU, and other parts of the world, and developed responsible AI and AI safety curricula internationally. At UBC, Ibrahim collaborates with the DASH cluster on AI education initiatives for the Department of Medicine, contributing to curriculum design for DASH educational activities and events. He also supervises ECE students developing edge AI sensors for climate change monitoring and adaptation, supported by various NSERC Alliance grants. Ibrahim is a founding engineer at Agrobotic, Mostar Labs, and IoT-World with global project scopes, and has served as an AI consultant to the UN Food and Agriculture Organization. His work has been recognized with over 30 global awards in IoT and AI.

What People Are Saying

Discover how this course is transforming the way healthcare professionals engage with AI technology.

”
This course serves as the first stepping stone into the realm of generative AI in healthcare. Well thought-of. 
Ali W.

Vancouver, Canada

”
The scope of this course is beyond any other programs and workshops I took. This course helped me think about patient biases not taken into account
Dr. Sadeghe H.

Senior Engineer, Google

”
The sandbox environment gave me hands-on insight about the course materials. I am able to apply what I learn immediately in a secure testing environment, without worrying about data retention with companies.  
Dr. Mohamed B.

Amateur photographer

Ready to Dive In?

Take the first step towards becoming a generative AI expert in healthcare.  Enroll now and unlock a world of opportunities.

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