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AI Model Risk Management

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AI Model Risk Management

This course is part of multiple programs.

Instructor: ansrsource instructors

Included with

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1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There is 1 module in this course

AI models create value, but they also create risks — from data drift and bias to regulatory non-compliance. In this short, practical course, you’ll learn how to make those risks visible, measurable, and governable. First, you’ll explore the main categories of model risk and practice mapping them to governance controls and KPIs. Next, you’ll learn how to evaluate model validation results against standards such as SR 11-7, the Basel Principles, and the EU AI Act, identifying compliance gaps and recommending corrective actions. Finally, you’ll draft a simple model-risk control framework with clear documentation standards, escalation paths, and review cadences. By the end, you’ll be able to demonstrate governance skills that help organizations deploy AI responsibly and maintain trust.