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Explore the cutting-edge security features of Amazon's AI services, including Bedrock, Amazon Q, and SageMaker Clarify. MLOps expert Noah Gift shows you how to implement a comprehensive security architecture that integrates multiple layers of protection. Discover methods to enforce the principle of least privilege through IAM roles and resource policies, while also using CloudTrail and CloudWatch for real-time monitoring and detailed auditing. Gain insights into advanced bias detection and model explainability with SageMaker Clarify. Learn how to configure Bedrock’s guardrails for robust content filtering and validation to prevent inappropriate or harmful outputs. Enhance your understanding of security boundaries, anomaly detection, and automated security responses to maintain the integrity and confidentiality of your AI applications. By the end of this course, you will secure AI workflows, enhance performance monitoring, and ensure compliance with industry standards.
This course was created by Noah Gift and Pragmatic AI Labs. We are pleased to host this training in our library.
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