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Focuses on integrating third-party security tools, configuring organization-wide logging, and implementing automated remediation workflows for AWS threat detection and response.
Learn to manage AWS keys and certificates and apply encryption services to protect data both at rest and in transit.
Apply AWS services and tools to implement compliance, governance, security, and transparency controls for generative AI applications.
Explore enterprise integration patterns connecting foundation models with business applications and data through secure, scalable, event-driven, cross-environment architectures.
Implement application integration patterns and AI-assisted development tools to enhance enterprise systems and build generative AI applications.
Explore foundation model API request patterns and streaming responses for conversational AI applications on AWS.
Implement monitoring for generative AI applications with actionable dashboards, performance baselines, anomaly detection, and vector database oversight.
Build evaluation systems for generative AI that measure relevance and accuracy, compare models, and support continuous quality improvement.
Explores defense-in-depth and seven-layer security for AI data, including VPC isolation, IAM, identity federation, RBAC, and granular access controls.
Learn to secure Gen AI interactions through input safety, output filtering, hallucination mitigation, and multilayer content safety architectures.
Implement generative AI cost optimization through token efficiency, cost-effective model selection, resource utilization, throughput maximization, and caching strategies.
Optimize generative AI application performance systematically through pre-computation, retrieval systems, model configuration, and API profiling.
Learn error monitoring and troubleshooting frameworks for diagnosing common issues in generative AI applications.
Experiment with Amazon Nova Lite on Bedrock, comparing zero-shot and context-enhanced question answering through complete and streaming responses in a simplified RAG workflow.
Practice deploying AWS Network Firewall specifically for threat hunting in a focused lab.
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