Amazon Web Services (AWS)
AWS Agentic AI Foundations
Understand agentic AI on AWS in one day.
1 dayFoundation7 modules
About this course
Understand agentic AI on AWS in one day. You will trace the move from LLMs to agents, learn the parts of an agentic system, compare workflow, autonomous and hybrid agents, and see what Amazon Bedrock and Amazon Q offer.
What you'll learn
- Summarize the evolution of Agentic AI and define what makes something "agentic"
- Identify core components of agentic systems
- Distinguish between workflow, autonomous, and hybrid agents
- Compare AWS service options for Agentic AI
- Describe capabilities and use cases of Amazon Q Developer, Amazon Q Business, and Kiro
- Explain Amazon Bedrock AgentCore and Amazon Bedrock Agents fundamentals
- Identify basic implementation patterns for Agentic AI
- Describe observability and interoperability patterns for production agentic AI systems
Curriculum
7 modules
- Understanding Large Language Models (LLMs)
- Innovations powering agents
- Evolution timeline from LLMs to Agents
- Understanding Agentic AI
- Types of AI agents
- Agentic AI applications
- Workflow patterns
- Amazon Bedrock flows overview
- How Autonomous Agents work
- ReAct
- ReWoo
- Multi-agent collaboration
- AWS Agentic AI solutions
- Amazon Q Developer
- Amazon Q Business
- Amazon Q in AWS Services
- Kiro: AI-powered IDE with spec-driven development
- Amazon Bedrock Agents
- Amazon Bedrock AgentCore
- Hands-on lab: Explore Amazon Bedrock Agents integrated with Amazon Bedrock Knowledge Bases and Amazon Bedrock Guardrails
- DIY solutions
- Observability and Monitoring
- Agent Interoperability
- Module 8: Course Wrap-up
- Next steps and additional resources
- Course summary
Who it's for
Technical decision-makers, architects and developers exploring AI agents.
Before you start
- Generative AI Essentials or equivalent work experience
- Basic AWS knowledge and software development experience
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