Lilly Tech Systems
Enterprise Model Governance
Establish comprehensive governance frameworks for managing AI and ML models throughout their lifecycle. Learn to design approval workflows, maintain complete audit trails, generate compliance reports, and implement best practices for model governance at enterprise scale.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Why model governance matters, the governance landscape, and key principles for managing models at scale.
2. Lifecycle Governance
Governing models from development through deployment, monitoring, and retirement across the full lifecycle.
3. Approval Workflows
Design multi-stage approval processes with role-based gates, automated checks, and exception handling.
4. Audit Trail
Maintain complete, immutable audit trails for model decisions, changes, approvals, and operational events.
5. Reporting
Governance reporting for risk committees, regulators, and executive leadership with standardized metrics.
6. Best Practices
Scaling governance, automation strategies, cross-functional collaboration, and continuous improvement.
What You'll Learn
By the end of this course, you'll be able to:
Govern Model Lifecycles
Implement governance controls at every stage from model development through production deployment and retirement.
Design Approval Workflows
Create efficient, risk-proportionate approval processes that enable innovation while maintaining control.
Maintain Audit Trails
Build comprehensive, tamper-proof audit trails that satisfy regulatory examination and internal audit requirements.
Report Effectively
Generate governance reports that communicate model risk posture to diverse stakeholders from boards to regulators.