Agentic AI Foundation

Course Overview

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. You’ll also discover how to use tools like Amazon Q Developer, Amazon Quick Suite, Kiro, Strands Agents SDK, and Amazon Bedrock AgentCore to build autonomous, goal-driven solutions that solve real-world problems.

Listed below is the course level and duration of this course:

• Course level: Fundamental
• Duration: 1 day

Course Objectives

In this 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
• Identify basic implementation patterns for agentic AI
• Compare AWS service options for agentic AI
• Describe capabilities and use cases of Amazon Quick Suite, Amazon Q Developer, and Kiro
• Explain Strands Agents framework and its applications
• Build and customize a basic AI agent using Strands Agents SDK
• Develop a simple task-specific agent for real-world application using Strands Agents SDK
• Explain Amazon Bedrock AgentCore
• Describe observability and interoperability patterns for production agentic AI systems

Methodology

This course includes presentations, hands-on labs, and group exercises.

Target 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 Quick Suite, and Amazon Bedrock AgentCore

Prerequisites

We recommend that attendees of this course have:

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

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