Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Responsible AI
- Core principles of fairness, accountability, and transparency.
- Regulatory factors driving responsible AI, such as the EU AI Act and GDPR.
- The function of Ollama within enterprise AI governance.
Bias Detection and Mitigation
- Techniques for identifying bias in model outputs.
- Strategies to reduce bias and enhance fairness.
- Assessing model performance using fairness metrics.
Safe Prompting and Alignment
- Designing prompts for safety and reliability.
- Mitigating risks associated with unsafe or harmful outputs.
- Alignment techniques suited for enterprise applications.
Content Filtering and Moderation
- Architecting content filtering pipelines.
- Implementing moderation safeguards.
- Striking a balance between user experience and compliance requirements.
Governance Workflows
- Defining governance frameworks specifically for Ollama.
- Integrating workflows with compliance systems.
- Procedures for model approval and auditing.
Logging, Traceability, and Auditability
- Secure logging practices for AI systems.
- Ensuring traceability of model decisions.
- Mechanisms for audit readiness and reporting.
Case Studies and Best Practices
- Enterprise deployments that uphold responsible AI principles.
- Insights gained from real-world governance failures.
- Cultivating sustainable and ethical AI practices.
Summary and Next Steps
Requirements
- A solid understanding of AI/ML fundamentals.
- Familiarity with compliance and governance concepts.
- Hands-on experience with enterprise IT or model deployment environments.
Target Audience
- AI ethics leads
- Compliance officers
- Legal and regulatory engineers
- Enterprise architects
