Automating Business Operations with AI Agents

Move beyond basic automation as you dive deep into AI agent architecture, development frameworks, and production deployment. Through hands-on exercises, you'll build agents using Amazon Bedrock that can understand context, make decisions, and execute complex workflows autonomously.

Core Learning Areas Master the essential components of AI agent development:

Architectural patterns for robust agent systems Advanced frameworks like LangChain for agent orchestration RAG implementation for context-aware decision making API integration and workflow automation Production deployment with containerization Performance monitoring and optimization Multi-agent system design and coordination

Hands-On Experience Throughout the workshop, you'll work on practical exercises including:

Building an intelligent agent from the ground up Implementing RAG for enhanced decision-making Orchestrating multi-agent workflows Deploying agents using Docker and cloud platforms Testing and optimizing agent performance

Ideal For

Software Engineers expanding into AI automation Data Engineers building data processing pipelines Technical Leaders architecting automation solutions DevOps Engineers managing AI infrastructure

Implementation Focus This workshop emphasizes practical implementation. You'll learn to:

Design modular agent architectures that scale Connect agents to business systems via AWS API Gateway, EventBridge, and Step Functions. Deploy AI agents with AWS Fargate, Amazon ECS, and EKS for containerized, scalable solutions. Use Amazon CloudWatch, AWS X-Ray, and SageMaker Model Monitor to track and improve agent efficiency. Optimize agent performance and reliability Build secure and maintainable agent systems

Space is limited to ensure personalized guidance and support.