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AWS Discovery Day: Agentic AI Foundations

  • Código del Curso GKAWS-DDAAF
  • Duración 1 Día

Otros Métodos de Impartición

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Método de Impartición

Este curso está disponible en los siguientes formatos:

  • Cerrado

    Cerrado

  • Clase de calendario

    Aprendizaje tradicional en el aula

  • Aprendizaje Virtual

    Aprendizaje virtual

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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

Calendario

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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

Objetivos del Curso

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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

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

Pre-requisitos

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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

Certificación de Prueba

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None

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