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AWS Discovery Day: Agentic AI Foundations

  • Course Code GKAWS-DDAAF
  • Duration 1 day

Course Delivery

Virtual Learning Price

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Course Delivery

This course is available in the following formats:

  • Company Event

    Event at company

  • Public Classroom

    Traditional Classroom Learning

  • Virtual Learning

    Learning that is virtual

Request this course in a different delivery format.

Course Overview

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In this course, you’ll explore the core principles and strategies to consider when designing Agentic AI systems on AWS.

 

You’ll learn how Agentic AI differs from traditional conversational systems, and how using agents helps build autonomous, goal-driven solutions that solve real-world problems.

 

Updated August 2026

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

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    • Delivery Format: Virtual Learning
    • Date: 16 November, 2026 | 9:00 AM to 5:00 PM
    • Location: Virtual (GMT Standa)
    • Language: English
    Please call

Target Audience

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This course is intended for:

- Software developers new to Agentic AI seeking foundational knowledge

- Technical professionals exploring AI capabilities who are interested in core components and applications of agentic AI

- Development teams evaluating Agentic AI solutions and needing to differentiate between agent types

Course Objectives

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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
  • Identify basic implementation patterns for Agentic AI

Course Content

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Module 1: Exploring Agentic AI

This course introduction provides a standard level of understanding for students in the course.

  • What is an AI agent?
  • Understanding agentic AI
  • Types of AI agents
  • Agentic AI applications

Module 2: Large Language Models (LLMs)

Discuss the benefits and challenges of using agents in your workflows with LLMs.

  • What are LLMs?
  • Understanding LLMs
  • How are LLMs trained?
  • LLM capabilities
  • Challenges associated with LLMs
  • Limitations of LLMs
  • Fallacy of composition

Module 3: Innovations Powering Agents

Explore factors shaping agent development and its breadth of capabilities.

  • Innovations shaping AI agents
  • How AI-software integration works
  • How chain-of-thought reasoning works
  • Impact of multimodal inference
  • Multi-agent collaboration
  • Agentic frameworks to build agents

Module 4: Evolution Timeline

Learn how long each phase is to take your agentic AI pipelines to production.

  • Workflows to go from LLMs to agents
  • Evolution of generative AI models
  • Differences and similarities between assistants, agents, and AI systems

Module 5: Knowledge Check and Summary

Review what was learned in the course and advise on the next steps.

  • Quiz questions
  • Course summary
  • Next steps and additional resources

Course Prerequisites

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We recommend that attendees of this course have:

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

Test Certification

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None

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