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 landscapes driving responsible AI (EU AI Act, GDPR, etc.)
- Ollama’s specific role in enterprise AI governance
Identifying and Addressing Bias
- Detecting bias within model outputs
- Techniques for reducing bias and enhancing fairness
- Assessing model performance using fairness metrics
Safe Prompt Engineering and Alignment
- Crafting prompts for safety and reliability
- Mitigating risks associated with unsafe or harmful outputs
- Applying alignment techniques suited for enterprise applications
Content Filtering and Moderation Strategies
- Architecting content filtering pipelines
- Deploying moderation safeguards
- Striking a balance between user experience and compliance obligations
Governance Workflow Design
- Establishing governance frameworks tailored to 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 traceability of model decisions
- Mechanisms for audit readiness and reporting
Case Studies and Industry Best Practices
- Enterprise deployments adhering to responsible AI principles
- Insights gained from real-world governance challenges
- Cultivating sustainable and ethical AI practices
Conclusion and Future Pathways
Requirements
- A solid grasp of AI/ML fundamentals
- Knowledge of compliance and governance frameworks
- Hands-on experience with enterprise IT or model deployment environments
Target Audience
- AI Ethics Leaders
- Compliance Officers
- Legal and Regulatory Engineers
- Enterprise Architects
