Agentic AI Foundations

This course is intended for:

Software developers new to Agentic AI seeking foundational knowledge

Technical professionals exploring AI capabilities and interested in core components and applications of agentic AI

Development teams evaluating Agentic AI solutions and needing to differentiate between agent types

AWS Users expanding into Agentic AI, including current users of Amazon Q Developer, Amazon Q Business, and Amazon Bedrock Agents

After completing this course you should be able to:

• 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

Module 1: From LLMs to Agents

• Understanding Large Language Models (LLMs) • Innovations powering agents
• Evolution timeline from LLMs to Agents

Module 2: Exploring Agentic AI

• Understanding Agentic AI
• Types of AI agents
• Agentic AI applications

Module 3: Understanding Agentic AI Workflows

• Workflow patterns
• Amazon Bedrock flows overview

Module 4: Introducing Autonomous Agents

• How Autonomous Agents work
• ReAct
• ReWoo
• Multi-agent collaboration
• AWS Agentic AI solutions

Module 5: Amazon Q and Agentic Development Tools

• Amazon Q Developer
• Amazon Q Business
• Amazon Q in AWS Services
• Kiro: AI-powered IDE with spec-driven development

Module 6: Agentic AI with Amazon Bedrock

• Amazon Bedrock Agents
• Amazon Bedrock AgentCore
• Hands-on lab: Explore Amazon Bedrock Agents integrated with Amazon Bedrock Knowledge Bases and Amazon Bedrock Guardrails

Module 7: Building DIY Solutions

• DIY solutions
• Observability and Monitoring
• Agent Interoperability

Module 8: Course Wrap-up

• Next steps and additional resources
• Course summary

Attendees should meet the following pre-requisites:

• Generative AI Essentials or equivalent work experience
• Basic AWS knowledge and software development experience

• GK4501 - AWS Technical Essentials
• GK910027 - Generative AI Essentials on AWS

Recommended as preparation for the following exams:

• There is no exam currently linked to this course.