Certified Responsible AI Ethics Officer (CRAIEO) Certification Exam

1. CRAIEO Domain One - AI/ML Fundamentals (15% of Exam)

   31 lessons

   1. Download CRAIEO eBook
   2. Course Welcome/Overview
   3. What is the CRAIEO Exam
   4. Exam Objectives
   5. Download Course Resources
   6. Module One - AI Fundamentals Overview

   1. Section 1.1 Core Concepts

      1. Section 1.1 Core Concepts
      2. Discussion - The Importance of AI Ethics in the Enterprise
      3. What is AI and ML?
      4. What are the Machine Learning Types?
      5. What is Deep Learning?
      6. Compare and Contrast AI and ML
      7. Generative AI, Predictive AI, Agentic AI, and others.
      8. Natural Language Processing (NLP)
      9. Understanding Algorithms
      10. Large Language Models (LLM)
      11. Whiteboard - How AI Works 10,000 foot level (Google Example)
      12. 4 Pillars of AI Strategy
      13. Importance of Data in AI/ML
      14. AI/ML Use Case - Finance
      15. AI/ML Use Case - Logistics
      16. Whiteboard - AI Resume Filtering

   2. Section 1.2 Prompt and Context Engineering

      1. Prompt and Context Engineering
      2. What is Prompt Engineering
      3. What is Context Engineering
      4. Comparing Prompt Engineering to Context Engineering
      5. Demonstration - Prompts and Context
      6. Whiteboard - Retrieval-Augmented Generation (RAG)
      7. Retrieval-Augmented Generation (RAG)
      8. Module Review Questions
      9. Module Review Summary

2. CRAIEO Domain Two - AI Ethics Foundational Concepts (20% of Exam)

   24 lesson

   1. Module Two Overview

   1. Section 2.1 - Core AI Ethics Foundational Concepts

      1. 2.1 Section Overview - Core AI Ethics Foundational Concepts
      2. Defining AI Ethics
      3. Core AI Ethical Principles
      4. Responsible AI Ethics and Governance
      5. Seven C's of AI
      6. Key AI Ethical Frameworks
      7. Understanding Transparancy with AI
      8. Case Study - AI Ethics Driven Strategy
      9. Sources of AI Bias

   2. Section 2.2 - Ethical Challenges Development and Deployment

      1. Section 2.2 Overview
      2. The Moral and Social Implications of AI Deployment
      3. AI and Job Displacement
      4. Principles of Ethical Development
      5. Potential Security Vulnerabilities
      6. Principles of Ethical Deployment

   3. Section 2.3 - Role of an AI Ethics Officer

      1. Role of An AI Ethics Officer
      2. Main Roles and Responsibilities
      3. Creating Ethical Policies, Frameworks and Practices
      4. Ethical AI in a Changing Landscape
      5. Whiteboard - Implement Responsible AI Principals
      6. Module Review Summary
      7. Module Review Questions
      8. Ethics Review Board

3. CRAIEO Domain Three - AI and Data Governance, Privacy and Compliance (25% of Exam)

   24 lesson

   1. Module 3 Overview

   1. Section 3.1 - Core Foundational Concepts

      1. Section 3.1 - Core Foundational Concepts Overview
      2. Defining Data Governance
      3. Defining Data Privacy
      4. Defining Data Compliance
      5. Data Mapping and Inventory
      6. Data Collection and Usage
      7. Privacy Impact Assessments (PIA)
      8. Whiteboard - Facebook(Meta) GDPR Compliance

   2. Section 3.2 - Frameworks and Lifecycles

      1. Section 3.2 Frameworks and Lifecycle
      2. Risk Management Frameworks
      3. NIST AI Framework
      4. Whiteboard - Implement NIST RMF
      5. Fedramp AI Guidance
      6. AI Lifecycles
      7. Software Development Lifecycle (SDLC)

   3. Section 3.3 - Data Governance and Ethical Data Use

      1. Data Governance and Ethical Data Use
      2. Creating the rules (Guardrails, Policies)
      3. Applying the Rules (Policies and Guardrails)
      4. Enforcing the Rules (Oversight and Action)
      5. Use Case - AI Ethics in Facial Recognition
      6. Whiteboard - AWS AI Patterns
      7. Module Review Summary
      8. Module Review Questions

4. CRAIEO Domain Four - AI Accountability, Transparency, and Explainability (20% of Exam)

   15 lesson

   1. Module Four Overview

   1. Section 4.1 - The Need for Explainable AI (XAI)

      1. Section 4.1 Overview
      2. What is Explainable AI
      3. Section 4.1 Overview
      4. Defining Explainable AI
      5. Demonstration - AWS Compliance
      6. Legal Frameworks that Establish Requirements
      7. White Box vs Black Box

   2. Section 4.2 - Establishing Legal and Professional Accountability for Decisions

      1. Section 4.2 Overview
      2. AI Center of Excellence
      3. Legal and Professional Accountability
      4. Code of Conduct
      5. Cloud Shared Responsibility Model
      6. Module Review Summary
      7. Module Review Questions

5. Domain Five (CRAIEO) - Regulations and Frameworks (20% of Exam)

   13 lesson

   1. Module Five Overview

   1. Section 5.1 - AI focused Regulations and Frameworks

      1. Section 5.1 Overview
      2. NIST AI Framework
      3. ISO/IEC 27001
      4. EU General Data Protection Regulation (GDPR)
      5. EU Artificial Intelligence Act (EU AI Act)

   2. Section 5.2 Applying International Ethical Guidelines and Standards

      1. Module 5.2 Overview
      2. OECD AI Principles
      3. UNESCO's Recommendation on the Ethics of Artificial Intelligence (2021)
      4. EU Ethics Guidelines for Trustworthy AI (2019)
      5. Module Review Summary
      6. Module Review Questions
      7. Course Closeout

6. Certified Responsible AI Ethics Officer (CRAIEO) Certification Exam

   1 lesson

   1. Certified Responsible AI Ethics Officer (CRAIEO) Certification Exam