AI+ Ethics Fundamentals™ eLearning
Formerly known as AI+ Ethics™
Navigate the Intersection of AI and Ethics in Business Landscape
- Responsible AI Focus: Master ethical AI use aligned with business and societal values
- Risk Mitigation: Learn to manage compliance, transparency, and AI decision-making
- Strategic Guidance: Integrate ethical practices into AI adoption and leadership
- Reputation Builder: Build organisational trust and credibility in AI deployments
- Leer in je eigen tempo, waar en wanneer jij wilt
- Betalen op factuur, annuleren volgens heldere voorwaarden
- Ook incompany voor je hele team
500+ IT-trainingen voor professionals en organisaties
Voor wie
Voor wie is deze training
Ethics Professionals:Enhance your expertise in AI ethics to guide responsible AI deployment.
AI & Data Enthusiasts:Learn how to apply ethical frameworks in AI decision-making processes.
Compliance Officers:Ensure AI technologies comply with legal and ethical standards to mitigate risks.
Technology Leaders:Drive ethical AI strategies and lead responsible AI initiatives within organizations.
Students & New Graduates:Gain a competitive edge in the rapidly growing field of AI ethics.
De training
Dit leer je tijdens de training
Praktijkgericht, met een trainer die zelf in het veld werkt. Geen theorie om de theorie.
Na deze training
Wat deze training je oplevert
- In-Depth Ethical Understanding:Understand ethical considerations and social impacts of AI for responsible decision-making.
- Bias Mitigation and Fairness:Learn strategies to identify and prevent biases in AI systems, ensuring fairness and transparency.
- Privacy and Security Assurance:Explore strategies to safeguard privacy and secure AI systems and data.
- Legal and Regulatory Compliance:Understand global AI regulations to ensure compliance with legal and ethical standards.
Inhoud
Het programma
- Course Introduction Preview
- 1.1 Understanding AI in a Modern Ethics Context
- 1.2 The Societal Impact of AI Technologies
- 1.3 Core Principles and Stakeholders
- 1.4 Building AI Literacy for the Workplace
- 1.5 Human Rights, Democracy, and AI Ethics
- 1.6 Case Studies
- 2.1 Where Bias Enters AI Systems
- 2.2 Fairness Concepts and Practical Evaluation
- 2.3 Mitigation and Inclusive Design
- 2.4 Applied Fairness Cases
- 2.5 Case Studies
- 3.1 Why Transparency Matters
- 3.2 Explainability Methods and Documentation Standards
- 3.3 Communicating AI Decisions Responsibly
- 3.4 Transparency, Documentation, and Governance Practices
- 3.5 Case Studies
- 4.1 Privacy Principles in AI
- 4.2 AI Data Governance and Data Quality
- 4.3 Security Risks in AI Systems
- 4.4 Privacy-Preserving AI Techniques
- 4.5 Content Authenticity, Provenance, and Trust
- 4.6 Real World Case Studies
- 5.1 Accountability Across the AI Lifecycle
- 5.2 Human Oversight and Control
- 5.3 Risk Management and Assurance
- 5.4 Red Teaming and Safety Testing
- 5.5 Governance Operating Model
- 5.6 Grievance and Remedy Processes
- 5.7 System Retirement and Decommissioning
- 5.8 Applied Case Studies
- 6.1 International Principles and Treaties
- 6.2 Management and Technical Standards
- 6.3 Binding Regional Laws
- 6.4 National Guidance and Voluntary Frameworks
- 6.5 Sector-Specific and Cross-Border Compliance
- 6.6 Case Studies
- 7.1 How Modern Generative and Agentic AI Systems Work
- 7.2 New Risks Introduced by Generative AI
- 7.3 Agentic AI Risks and Governance
- 7.4 Evaluation and Safe Deployment
- 7.5 Responsible Use Cases and Boundaries
- 8.1 Select an AI Use Case
- 8.2 Perform an Ethics and Risk Assessment
- 8.3 Develop an AI Governance Package Using the NIST AI RMF
- 8.4 Final Capstone Deliverable
- 8.5 Review and Reflection
- 1.1 What Are AI Agents?
- 1.2 Applications and Trends of AI Agents for Ethics
- 1.3 How Does an AI Agent Work?
- 1.4 Core Characteristics of AI Agents
- 1.5 Importance of AI Agents
- 1.6 Types of AI Agents
- AI4People (Atomium - European Institute for Science, Media, and Democracy)
- IBM - AI Fairness 360
- IBM - AI Explainability 360
- European Commission High-Level Expert Group on AI
Praktisch
Goed om te weten
Lesmethode
Kenmerken
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Voorkennis
- Basic knowledge of artificial intelligence, machine learning concepts, Python familiarity, fundamental AI/ML concepts
Inschrijven
Alles op een rij
AI+ Ethics Fundamentals™ eLearning
- Betalen op factuur mogelijk
- Verschuiven of annuleren volgens onze voorwaarden
- Ook incompany voor je hele team via maatwerk
Zekerheid
Inschrijven zonder verrassingen
Heldere voorwaarden
Verschuiven of annuleren doe je volgens onze algemene voorwaarden. Geen kleine lettertjes achteraf.
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