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AWS Authorized Training Course - Agentic AI Foundations

Course Summary

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.

Prerequisites:

  • Generative AI Essentials or equivalent work experience 
  • Basic AWS knowledge 
  • Software development experience
Purpose
Learn the principles and strategies for designing Agentic AI systems using AWS services
Audience
Technical professionals new to Agentic AI seeking foundational knowledge and practical implementation skills
Role
Software Developers | Technical Professionals 
Skill level
Foundational
Style
Lecture | Hands-on Activities | Labs
Duration
1 day
Related technologies
Amazon Bedrock

 

Learning Objectives
  • Summarize the evolution of Agentic AI and define what makes something "agentic"
  • Identify core components of agentic systems: goals, memory, tools, and environment
  • Distinguish between workflow, autonomous, and hybrid agents
  • Compare AWS service options for Agentic AI (Specialized, Managed, and DIY approaches)
  • Describe capabilities and use cases of Amazon Q Developer, Amazon Q Business, and Kiro
  • Explain Amazon AgentCore and Amazon Bedrock Agents core functionalities
  • Identify basic implementation patterns for Agentic AI
  • Describe observability and interoperability patterns for production agentic AI systems

What you'll learn:

In this AWS Authorized Training Course - Agentic AI Foundations , you'll learn:

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
  • Demo: Amazon Bedrock Flows

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
  • Demo: Amazon Q

Module 6: Agentic AI with Amazon Bedrock

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

Module 7: Building DIY Solutions

  • DIY solutions
  • Observability and Monitoring
  • Agent Interoperability

Module 8: Course Wrap-up

  • Next steps and additional resources
  • Course summary    

AWS Authorized Training Course - Agentic AI Foundations

real world content

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
expert practitioners

Expert Practitioners

Industry experts that bring their battle scars into the classroom.
experiential learning

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
fully customized

Tailored Outlines

Once-size-fits-all doesn't apply to training teams. That's where we come in!

Dive in and learn more

When transforming your workforce, it’s important to have expert advice and tailored solutions. We can help. Tell us your unique needs and we'll explore ways to address them.

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