Course Overview

This 1-day, fundamental-level training introduces participants to the principles, components, and AWS services that power Agentic AI. You’ll explore how agentic systems differ from traditional conversational AI, learn workflows, autonomous agents, hybrid architectures, and gain hands-on experience building goal-driven AI solutions with Amazon Bedrock Agents and AgentCore.

After completing this course of training, you will be able to:

  • Summarize the evolution of Agentic AI and what makes systems “agentic.”
  • Identify core components of agentic systems and different agent types.
  • Distinguish between workflow, autonomous, and hybrid agents Describe, Compare, and use cases AWS services supporting Agentic AI (Amazon Q Developer, Amazon Q Business, Kiro).
  • Explain fundamentals of Amazon Bedrock Agents and AgentCore.
  • Implement basic agent workflows and autonomous patterns.
  • Describe interoperability and observability practices for production AI systems.

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Key Features of Agentic AI Foundations

  • 1-day instructor-led classroom training. 

  • Hands-on labs with Amazon Bedrock Agents and Knowledge Bases. 

  • Real-world examples of workflow and autonomous agents. 

  • Group exercises to reinforce concepts. 

  • Official AWS training material.

Who Should Attend Agentic AI Foundations:

  • Software developers exploring Agentic AI.
  • Technical professionals evaluating agent-based solutions.
  • Development teams differentiating between workflow and autonomous agents.
  • AWS users expanding skills into Agentic AI (Amazon Q, Bedrock Agents).

Prerequisites Agentic AI Foundations:

  • Generative AI Essentials training or equivalent knowledge.
  • Basic AWS cloud knowledge.
  • Fundamental software development experience.

    • Learning Objective of the Course – On Completion, You Will Be Able To:

    • Design and evaluate Agentic AI workflows.
    • Build autonomous agents using AWS Bedrock Agents and AgentCore.
    • Apply observability and interoperability best practices.
    • Choose the right AWS service (Amazon Q, Kiro, Bedrock) for use cases.

    Why Choose CloudThat as Your Training Partner?

    • AWS Advanced Training Partner with certified instructors.
    • Proven expertise in Generative AI and Agentic AI implementations.
    • Hands-on lab environments for real-world learning.
    • Customized training pathways aligned to career goals.
    • Post-training mentorship and career support.

    Course Outline Download Course Outline

    • Understanding Large Language Models (LLMs)
    • Innovations powering agents
    • Evolution timeline from LLMs to Agents

    • Understanding Agentic AI
    • Types of AI agents
    • Agentic AI applications

    • Workflow patterns
    • Amazon Bedrock flows overview

    • How Autonomous Agents work
    • ReAct
    • ReWoo
    • Multi-agent collaboration
    • AWS Agentic AI solutions

    • Amazon Q Developer
    • Amazon Q Business
    • Amazon Q in AWS Services
    • Kiro: AI-powered IDE with spec-driven development

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

    • DIY solutions
    • Observability and Monitoring
    • Agent Interoperability

    • Next steps and additional resources
    • Course summary

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    Course ID: 25877

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    FAQs:

    Salaries vary by role and experience. In India, AI developers with agentic AI skills earn between ₹10–20 LPA, while senior roles may exceed ₹30 LPA. Globally, salaries range from $110K–$160K USD annually.

    Basic AWS knowledge, familiarity with Generative AI, and fundamental programming skills (Python or JavaScript recommended).

    Yes, hands-on labs include Amazon Bedrock Agents, Knowledge Bases, and Guardrails.

    No exam.

    Yes, you will gain practical patterns to design and implement workflow and autonomous agents in real-world projects.

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