Ollama for Responsible AI and Governance Training Course
Ollama is a platform designed for running large language and multimodal models locally, with a strong focus on supporting governance and responsible AI practices.
This instructor-led, live training (available both online and onsite) is tailored for intermediate to advanced professionals who aim to implement fairness, transparency, and accountability in applications powered by Ollama.
By the end of this training, participants will be able to:
- Apply responsible AI principles in their Ollama deployments.
- Implement effective content filtering and bias mitigation strategies.
- Design governance workflows that ensure AI alignment and auditability.
- Establish robust monitoring and reporting frameworks for compliance.
Format of the Course
- Interactive lectures and discussions.
- Hands-on labs for designing governance workflows.
- Case studies and exercises focused on compliance.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
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
Open Training Courses require 5+ participants.
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