Course Outline

Introduction to Responsible AI

  • Principles of fairness, accountability, and transparency
  • Regulatory drivers for responsible AI (EU AI Act, GDPR, etc.)
  • The role of Ollama in enterprise AI governance

Bias Detection and Mitigation

  • Identifying bias in model outputs
  • Strategies for bias reduction and fairness improvement
  • Evaluating model performance with fairness metrics

Safe Prompting and Alignment

  • Prompt design for safety and reliability
  • Mitigating risks of unsafe or harmful outputs
  • Alignment techniques for enterprise applications

Content Filtering and Moderation

  • Designing content filtering pipelines
  • Implementing moderation safeguards
  • Balancing user experience with compliance needs

Governance Workflows

  • Defining governance frameworks for Ollama
  • Workflow integration with compliance systems
  • Model approval and audit procedures

Logging, Traceability, and Auditability

  • Secure logging practices for AI systems
  • Traceability of model decisions
  • Audit readiness and reporting mechanisms

Case Studies and Best Practices

  • Enterprise deployments with responsible AI principles
  • Lessons learned from real-world governance failures
  • Building sustainable and ethical AI practices

Summary and Next Steps

Requirements

  • Understanding of AI/ML fundamentals
  • Familiarity with compliance and governance concepts
  • Experience with enterprise IT or model deployment environments

Audience

  • AI ethics leads
  • Compliance officers
  • Legal and regulatory engineers
  • Enterprise architects
 14 Hours

Delivery Options

Private Group Training

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  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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