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
Foundations of Responsible AI
- Core principles of fairness, accountability, and transparency
- Regulatory influences on responsible AI (such as the EU AI Act and GDPR)
- Ollama's specific role in enterprise AI governance
Identifying and Reducing Bias
- Detecting bias within model outputs
- Techniques for reducing bias and enhancing fairness
- Assessing model performance using fairness metrics
Safe Prompting and Model Alignment
- Crafting prompts for enhanced safety and reliability
- Mitigating risks associated with unsafe or harmful outputs
- Applying alignment techniques suitable for enterprise environments
Content Filtering and Moderation
- Architecture of content filtering pipelines
- Deployment of moderation safeguards
- Striking a balance between user experience and compliance requirements
Governance Workflows
- Establishing governance frameworks tailored for Ollama
- Integrating workflows with existing compliance systems
- Procedures for model approval and auditing
Logging, Traceability, and Audit Readiness
- Best practices for secure logging in AI systems
- Ensuring full traceability of model decisions
- Maintaining audit readiness and structured reporting mechanisms
Case Studies and Industry Best Practices
- Enterprise implementations adhering to responsible AI principles
- Insights gained from past governance failures
- Cultivating sustainable and ethical AI operations
Conclusion and Future Directions
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
