Build robust security frameworks for AI implementations through hands-on coding. We'll implement data protection patterns, secure prompt handling, and PII detection. Code along as we create privacy-preserving pipelines in SageMaker, configure IAM policies for model access control, and automate compliance checks with AWS Config. Develop defenses against prompt injection attacks, implement differential privacy techniques, and build CloudTrail audit trails. Leave with production-ready code templates for governance guardrails and technical safeguards that protect sensitive data throughout the AI lifecycle while enabling innovation and maintaining trust in your AI applications.

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