Visão Geral

Este curso aborda o desenvolvimento de agentes de Inteligência Artificial autônomos capazes de planejar, raciocinar, tomar decisões e executar tarefas complexas com mínima intervenção humana. O participante aprenderá como projetar sistemas agentic avançados utilizando Large Language Models (LLMs), memória persistente, ferramentas externas, mecanismos de planejamento, recuperação de conhecimento e execução autônoma de workflows. O curso explora arquiteturas modernas para construção de agentes autônomos corporativos, além de aspectos relacionados à segurança, governança, observabilidade e controle operacional.

Objetivo

Após realizar este curso, você será capaz de:

• Compreender os fundamentos dos agentes autônomos de IA
• Projetar arquiteturas para execução autônoma de tarefas complexas
• Implementar mecanismos de planejamento, memória e tomada de decisão
• Integrar agentes com sistemas corporativos e ferramentas externas
• Aplicar controles de segurança e governança para agentes autônomos
• Construir soluções empresariais escaláveis baseadas em Autonomous AI Agents

Publico Alvo

• Engenheiros de IA e Machine Learning
• Desenvolvedores de Software
• Arquitetos de Soluções
• Engenheiros de Automação
• Profissionais de LLMOps e Platform Engineering
• Líderes técnicos envolvidos em projetos de IA avançada

Pre-Requisitos

• Conhecimentos equivalentes aos cursos AI Agents Fundamentals e Agentic AI
• Familiaridade com Large Language Models
• Conhecimentos básicos de APIs e integração de sistemas
• Experiência com aplicações baseadas em IA Generativa é recomendada

Conteúdo Programatico

Module 1: Introduction to Autonomous AI Agents

1. Evolution of autonomous intelligent systems
2. Fundamentals of autonomous agents
3. Agent autonomy levels
4. Enterprise applications and opportunities
5. Challenges of autonomous execution
6. Autonomous agent ecosystem overview

Module 2: Autonomous Agent Architectures

1. Core architecture components
2. Perception, reasoning and action loops
3. Goal-oriented system design
4. Agent execution lifecycle
5. Decision-making frameworks
6. Architectural design patterns

Module 3: Planning and Reasoning Systems

1. Task decomposition methodologies
2. Strategic planning techniques
3. Dynamic planning and replanning
4. Goal management mechanisms
5. Autonomous reasoning workflows
6. Execution optimization strategies

Module 4: Memory and Context Management

1. Memory architecture fundamentals
2. Short-term memory systems
3. Long-term memory mechanisms
4. Persistent knowledge storage
5. Context management strategies
6. Memory optimization techniques

Module 5: Tool Use and System Integration

1. Tool calling architectures
2. API orchestration techniques
3. Enterprise application integration
4. Data access strategies
5. Workflow execution mechanisms
6. External system governance

Module 6: Autonomous Knowledge Retrieval

1. Agentic RAG fundamentals
2. Dynamic retrieval workflows
3. Semantic search integration
4. Knowledge-grounded execution
5. Retrieval optimization techniques
6. Enterprise knowledge applications

Module 7: Multi-Step Workflow Automation

1. Autonomous workflow design
2. Sequential execution models
3. Parallel execution strategies
4. Workflow monitoring mechanisms
5. Failure recovery approaches
6. Process optimization techniques

Module 8: Multi-Agent Autonomous Systems

1. Multi-agent architecture fundamentals
2. Agent communication protocols
3. Collaborative execution models
4. Distributed decision-making
5. Agent orchestration strategies
6. Enterprise multi-agent systems

Module 9: Security and Governance

1. Security risks in autonomous agents
2. Access control mechanisms
3. Permission management strategies
4. Governance frameworks
5. Risk mitigation approaches
6. Responsible AI principles

Module 10: Monitoring and Operational Control

1. Agent observability concepts
2. Execution monitoring techniques
3. Performance measurement frameworks
4. Operational dashboards
5. Reliability engineering principles
6. Continuous optimization processes

Module 11: Enterprise Autonomous Agent Solutions

1. Autonomous customer service agents
2. IT operations automation agents
3. Enterprise productivity assistants
4. Knowledge management agents
5. Business process automation
6. Industry-specific autonomous solutions

Module 12: Autonomous AI Agents Workshop

1. Autonomous agent architecture design
2. Planning and memory implementation
3. Enterprise tool integration laboratories
4. Multi-agent collaboration exercises
5. Governance and monitoring validation
6. Final autonomous AI agent project