Learn how agentic AI differs from conversational AI and build your first agent with the Strands Agents SDK and Amazon Bedrock AgentCore. 1-day official AWS course with hands-on labs.

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Course Overview

Generative AI produces content when you ask. An agent decides what to do, uses tools to do it, and keeps going until the goal is met. That difference is the entire subject of this course.

Over one day, you will learn what actually makes a system agentic, why large language models alone fall short, and which innovations closed the gap. You will work through the three architectural patterns that matter in practice, workflow agents, autonomous agents, and hybrid designs, and learn when each one fits. From there the course maps AWS's agentic toolkit: Amazon Quick Suite and Amazon Q Developer for productivity and development acceleration, Kiro as a spec-driven AI development environment, the Strands Agents SDK for building agents in code, and Amazon Bedrock AgentCore for running them.

Two hands-on labs anchor the day. In the first, you use Amazon Q Developer to accelerate a real software development workflow. In the second, you build and customize an agent with the Strands Agents SDK. The course closes on the part most agent projects underestimate: customizing agentic infrastructure, observability and monitoring, and agent interoperability, which is what separates a demo from something you can run in production.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

Upcoming Schedules

Start Date	Time	Duration	Mode	Price
Aug 28, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Sep 11, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Sep 25, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Oct 09, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Oct 23, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Nov 06, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR

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What you will learn

Summarize the evolution of agentic AI and define what makes a system agentic
Identify the core components of agentic systems
Distinguish between workflow, autonomous, and hybrid agents
Identify basic implementation patterns for agentic AI
Compare AWS service options for agentic AI
Describe the capabilities and use cases of Amazon Quick Suite, Amazon Q Developer, and Kiro
Explain the Strands Agents framework and its applications
Build and customize a basic AI agent using the Strands Agents SDK
Develop a simple task-specific agent for a real-world application
Explain Amazon Bedrock AgentCore
Describe observability and interoperability patterns for production agentic AI systems

Who Should Attend This Course?

Software developers new to agentic AI who want foundational knowledge
Technical professionals exploring AI capabilities and the components of agentic systems
Development teams evaluating agentic AI solutions and needing to tell agent types apart
AWS users expanding into agentic AI, including current users of Amazon Q Developer, Amazon Quick Suite, and Amazon Bedrock AgentCore

Prerequisites

AWS recommends attendees have:

Generative AI Essentials on AWS, or equivalent practical experience with generative AI concepts
Basic AWS knowledge and software development experience

This is a fundamental-level course, but it is aimed at technical professionals. You will work with an SDK in the labs, so some development background matters more than deep AWS expertise.

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📘 Agentic AI Foundations on AWS Outline

The limitations of large language models
The innovations that made agents possible
How agentic AI systems evolved out of LLMs

What agentic AI actually is
Types of AI agents
Agentic AI applications in practice

Workflow patterns
Overview of Amazon Bedrock Flows

The AWS agentic AI solution landscape
Amazon Quick Suite
Amazon Q Developer
Hands-on lab: accelerating software development using Amazon Q Developer
Kiro, an AI-powered IDE built around spec-driven development

Agentic AI frameworks
Hands-on lab: getting started with Strands Agents
Amazon Bedrock AgentCore

Customizing agentic infrastructure
Observability and monitoring
Agent interoperability

Course summary
Next steps and additional resources

❓ Frequently Asked Questions

Generative AI responds to a prompt with content. Agentic AI pursues a goal: it plans, selects and calls tools, holds context across steps, and keeps working until the objective is met or it fails in a way you can observe. Think of generative AI as a capable writer and an agent as a colleague who can actually go and complete the task. Module 1 and Module 2 cover this distinction in depth, because getting it wrong leads to badly scoped projects.

You should have software development experience and be comfortable with an SDK, since the Strands Agents lab involves building an agent rather than configuring one. Deep AWS expertise is less important than general development ability.

They are the three implementation patterns the course centres on. Workflow agents follow defined paths with AI at decision points. Autonomous agents determine their own steps toward a goal. Hybrid designs combine both, which is what most production systems end up being. Knowing which pattern fits a use case is the single most useful thing this course teaches.

No. Agentic AI Foundations is a skills course with no associated exam. It builds knowledge that supports AWS AI certification paths, but it is not exam preparation, and there is no "Agentic AI Foundations" certification to earn.

AWS recommends it, or equivalent experience. If foundation models, prompting, and the generative AI landscape are already familiar to you, you can come directly to this course. If they are not, the concepts in Module 1 will move quickly.

Developing Generative AI Applications on AWS is the natural next step. It is a two-day advanced course that goes much deeper into building with Amazon Bedrock programmatically, including RAG with Knowledge Bases, Guardrails, and developing Bedrock Agents with AgentCore.

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