AWS Agentic AI Foundations

Course 1969

  • Duration: 1 day
  • Language: English
  • Level: Foundation

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.

AWS Agentic AI Foundations Course Delivery Methods

  • Online

  • Upskill your whole team by bringing Private Team Training to your facility.

AWS Agentic AI Foundations Course

In this AWS course, you will:

  • 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.

Prerequisites

We recommend that attendees of this course have:

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

AWS Agentic AI Foundations 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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AWS Agentic AI Foundations Course FAQs

Agentic AI refers to artificial intelligence systems that can act as autonomous agents—meaning they don’t just generate outputs (like text or images) when prompted, but they can perceive, reason, make decisions, and take actions toward goals in dynamic environments.

    Attendees will be introduced to Amazon Bedrock, Kiro and AmazonQ

    Generative AI is like a talented creator — it produces high-quality content when asked.  Agentic AI is like a skilled worker or digital teammate — it can use generative AI (and other tools) but adds decision-making, autonomy, and action-taking.

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