AWS-AGT_ESS | Agentic AI Foundations
 
In this course, you’ll explore the core principles and strategies for designing Agentic AI systems using AWS services. You’ll learn how Agentic AI differs from traditional conversational systems, and how to use tools like Amazon Q, Kiro, Amazon Bedrock Agents, and Amazon Bedrock AgentCore to build autonomous, goal-driven solutions that solve real-world problems.
 
Course objectives
In this course, you will learn 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.

Intended audience
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.

Prerequisites
We recommend that attendees of this course have:
Generative AI Essentials or equivalent work experience.
Basic AWS knowledge and software development experience.

Course Outline
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
 
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