Enterprise Generative AI Systems on AWS Certification Course

About this course

This course contains the use of artificial intelligence.

Build the skills to design, secure, deploy, and operate enterprise generative AI systems on AWS through a complete architecture-first learning experience. This course takes you from business requirements and interaction channels to production-ready platforms powered by Amazon Bedrock, foundation models, retrieval-augmented generation, AI agents, enterprise data, security controls, observability, and automation.

You will begin by exploring how large organizations such as Netflix, United Airlines, Walmart, and Tesla could apply AWS Generative AI architecture to real business scenarios. You will then learn how to read a complete architecture from left to right, understand the prompt-and-response lifecycle, identify trust boundaries, map data movement, and apply the AWS Well-Architected Generative AI Lens.

The course covers web, mobile, Slack, Microsoft Teams, APIs, and Amazon Connect experiences. You will learn how to connect structured and unstructured enterprise data from Amazon S3, Aurora, RDS, DynamoDB, Redshift, SaaS platforms, internal APIs, SharePoint, Salesforce, ServiceNow, and on-premises systems.

You will design secure application layers using Route 53, CloudFront, AWS WAF, Shield, API Gateway, Lambda, ECS, Fargate, App Runner, and EKS. You will compare synchronous and asynchronous workflows, serverless and container-based architectures, stateless and stateful services, and resilient patterns for scaling, retries, timeouts, and long-running AI tasks.

A major focus is Amazon Bedrock, including model selection, Amazon Nova, Anthropic Claude, Meta Llama, Mistral, embeddings, multimodal models, structured outputs, tool calling, prompt routing, model customization, and cost-aware inference. You will build RAG systems with Bedrock Knowledge Bases, OpenSearch Serverless, S3 Vectors, Aurora PostgreSQL with pgvector, and Nept

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