Visão Geral

Este curso mostra como usar GPT-4 e GPT-5 de forma estratégica tanto para negócios quanto para desenvolvimento. A proposta é unir visão tradicional de resolução de problemas, estrutura sólida, boas práticas e processos com a inovação dos modelos avançados de IA. Você aprende a criar automações, fluxos inteligentes, análises, produtos digitais e soluções de produtividade para equipes e empresas.

Objetivo

Após realizar este curso, você será capaz de:

• Aplicar GPT-4 e GPT-5 em soluções reais
• Criar automações inteligentes para negócios
• Desenvolver aplicações com uso de IA
• Criar assistentes especializados
• Implementar fluxos de RAG, memória e ferramentas
• Integrar GPT a sistemas internos e externos
• Aplicar boas práticas de segurança e escalabilidade

Publico Alvo

• Desenvolvedores iniciantes e experientes
• Profissionais de TI
• Empreendedores
• Gestores e líderes de times
• Analistas de negócios
• Criadores de automações e produtos digitais
• Pessoas que querem dominar GPT na prática

Pre-Requisitos

• Lógica de programação básica
• Noções de APIs
• Conta na OpenAI
• Conhecimentos básicos em Python ou JavaScript

Conteúdo Programatico

Module 1 — Understanding GPT-4 and GPT-5

1. Capabilities and differences between models
2. Strengths, limitations, and ideal use cases
3. Reasoning, multimodality, and advanced features
4. Pricing and usage planning for teams

Module 2 — Prompt Engineering for Professionals

1. Core prompting techniques
2. Structured prompts for business and dev tasks
3. Role-based prompting and instruction design
4. Improving determinism and output quality

Module 3 — GPT for Business Operations

1. Workflow automation
2. Email, documentation, and report generation
3. Customer service assistants
4. Process optimization and templates

Module 4 — GPT for Data and Decision-Making

1. Data summarization and analysis
2. Structured reasoning for decisions
3. KPI tracking with AI support
4. Creating dashboards powered by GPT

Module 5 — Building Applications with GPT

1. API integration
2. Understanding chat, system prompts, and message roles
3. Multi-step reasoning with functions
4. Error handling and robust architectures

Module 6 — Developing AI Agents

1. Multi-agent systems
2. Planning, reasoning, and tool orchestration
3. Memory design and agent collaboration
4. Practical use cases in industry

Module 7 — RAG (Retrieval-Augmented Generation)

1. Concepts and architecture
2. Building vector stores
3. Document ingestion pipelines
4. Retrieval strategies and evaluation

Module 8 — GPT for Product Development

1. Brainstorming features and UX flows
2. Technical documentation creation
3. Creating user stories and dev tickets
4. QA automation with GPT

Module 9 — Multimodal Capabilities

1. Vision: reading images, PDFs and screenshots
2. Audio: transcription and voice generation
3. Image generation workflows with DALL·E
4. Use cases across business areas

Module 10 — Security and Compliance

1. Data handling and privacy
2. Rate limits and scaling
3. Governance strategies for enterprise use
4. Safety, ethics, and human-in-the-loop systems

Module 11 — Productivity Systems for Devs and Teams

1. AI-assisted coding
2. Code reviews and refactoring
3. Documentation pipelines
4. Meeting summaries and planning tools

Module 12 — Final Project: GPT Business/Product Solution

Create a complete solution, such as:

1. AI internal assistant for a company
2. Automated business workflow
3. Multi-agent reasoning system
4. RAG knowledge base for support
5. AI-driven product MVP

Includes:

1. Planning
2. Development
3. Testing
4. Deployment