Course curriculum

    1. Welcome to the Board Certification Preparation Program

    2. Competencies for the AI Leadership: Board Certification Assessment Program

    1. Introduction to Strategic AI Leadership & Organizational Alignment

    2. Defining an AI-Driven Vision Aligned with Enterprise Strategy

    3. AI Maturity Models: Assessing Readiness Across the Enterprise

    4. Building the AI Roadmap: From Pilot to Scale

    5. Identifying High-Impact AI Opportunities for Innovation

    6. Evaluating Business Models in the Age of AI

    7. Aligning AI Strategy with Enterprise Architecture and Operations

    8. Leading Cross-Functional AI Teams and Initiatives

    9. Building a Business Case for AI Investments

    10. Executive Communication for AI Strategy and Results

    11. Organizational Models for Scaling AI Adoption

    12. Flash Cards

    13. Scenario-Based Application Exercise

    14. Assignment I. BCAIL

    1. Introduction to AI Governance, Ethics & Responsible AI Use

    2. The Foundations of Responsible AI

    3. Comparing Global Responsible AI Frameworks (OECD, NIST, ISO/IEC)

    4. Establishing Governance Structures Across the AI Lifecycle

    5. Algorithmic Fairness and Bias Mitigation Strategies

    6. Explainability and Transparency in AI Systems

    7. Data Privacy and Ethical Risk in AI Applications

    8. Legal & Regulatory Compliance (GDPR, HIPAA, etc.)

    9. Developing Organizational AI Ethics Policies

    10. Monitoring and Auditing AI for Responsible Use

    11. Board-Level Oversight and Ethical Accountability for AI

    12. Flash Cards

    13. Scenario-Based Application Exercise

    14. Assignment II. BCAIL

    1. Introduction to AI Technology Fluency & Systems Thinking

    2. AI Fundamentals: ML, Deep Learning, Generative AI

    3. Understanding AI System Architectures and Pipelines

    4. Model Inputs, Outputs, and Evaluation Metrics

    5. Understanding AI Limitations: Accuracy, Drift, Hallucinations

    6. AI Product Lifecycle: From Development to Deployment

    7. APIs, Microservices, and Integration in AI Systems

    8. Bridging the Gap: Communicating AI to Non-Technical Stakeholders

    9. Systems Thinking in Complex AI Ecosystems

    10. AI Stack Overview: Infrastructure, Tools, and Platforms

    11. Vendor Selection and Technical Due Diligence

    12. Flash Cards

    13. Scenario-Based Application Exercise

    14. Assignment III. BCAIL

    1. Introduction to Data Governance & AI-Ready Infrastructure

    2. Foundations of Data Governance for AI

    3. Managing the Data Lifecycle in AI-Driven Organizations

    4. Ensuring Data Quality, Stewardship, and Availability

    5. Data Anonymization, Privacy, and Sovereignty Challenges

    6. Information Security for AI Systems

    7. Designing AI-Ready Infrastructure: Cloud, Edge, On-Prem

    8. Compliance and Regulatory Considerations in Data Use

    9. Data Strategy Alignment with AI Objectives

    10. AI Data Risk Assessment and Mitigation

    11. Operationalizing Data Governance Across the Enterprise

    12. Flash Cards

    13. Scenario-Based Application Exercise

    14. Assignment IV. BCAIL

    1. Introduction to Human-AI Collaboration & Change Management

    2. Principles of Human-AI Collaboration

    3. Redesigning Roles and Workflows with AI Integration

    4. Human-Centered AI Design and Experience

    5. Cognitive Load, Trust, and Human-in-the-Loop Design

    6. Workforce Impact: Augmentation, Displacement, Empowerment

    7. Leading AI Change with the ADKAR and Kotter Models

    8. Building Organizational AI Literacy

    9. Designing Upskilling and Reskilling Programs for AI

    10. Fostering Psychological Safety in AI-Enabled Teams

    11. Trust-Building and Ethical Leadership During AI Transition

    12. Flash Cards

    13. Scenario-Based Application Exercise

    14. Assignment V. BCAIL

About this course

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  • 88 lessons
  • 0.5 hours of video content

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