AWS Partner Day - Agentic AI Foundations
- Course Code GKAWS-AAF
- Duration 1 day
Course Delivery
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Course Delivery
This course is available in the following formats:
-
Public Classroom
Traditional Classroom Learning
-
Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
TopFree of charge and dedicated to AWS partners
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.
Virtual Learning
This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.
Course Schedule
TopTarget Audience
TopThis 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
Course Objectives
TopAfter completing this course you should be able 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
Course Content
TopModule 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
Course Prerequisites
TopAttendees should meet the following pre-requisites:
- Generative AI Essentials or equivalent work experience
- Basic AWS knowledge and software development experience
Recommended prerequisites:
Test Certification
TopRecommended as preparation for the following exams:
- There is no exam currently linked to this course.