AWS Free Class - Agentic AI Foundations
- Código del Curso GKAWS-FOC-AAF
- Duración 1 Día
Otros Métodos de Impartición
Salta a:
Método de Impartición
Este curso está disponible en los siguientes formatos:
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Clase de calendario
Aprendizaje tradicional en el aula
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Aprendizaje Virtual
Aprendizaje virtual
Solicitar este curso en un formato de entrega diferente.
Temario
Parte superiorThis course is free of charge for AWS customers
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.
Calendario
Parte superior-
- Método de Impartición: Aprendizaje Virtual
- Fecha: 01 julio, 2026 | 8:00 AM to 3:00 PM Evento Garantizado
- Sede: Aula Virtual (W. Europe )
- Idioma: Español
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Guaranteed To Run
Dirigido a
Parte superiorThis 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
Objetivos del Curso
Parte superiorAfter 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
Contenido
Parte superiorModule 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
Pre-requisitos
Parte superiorAttendees should meet the following pre-requisites:
- Generative AI Essentials or equivalent work experience
- Basic AWS knowledge and software development experience
Certificación de Prueba
Parte superiorRecommended as preparation for the following exams:
- There is no exam currently linked to this course.