Training goals

code: AWS-AAIF | version: 1.0.0

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

Conspect Show list

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

Download conspect training as PDF

Additional information

Prerequisites	We recommend that attendees of this course have: Generative AI Essentials or equivalent work experience Basic AWS knowledge and software development experience
Difficulty level
Duration	1 day
Certificate	The participants will obtain certificates signed by AWS (course completion).
Trainer	AWS Authorized Instructor (AAI)

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