Visão Geral
Este curso apresenta os fundamentos da Engenharia de Prompts (Prompt Engineering), capacitando os participantes a interagir de forma eficaz com Large Language Models (LLMs) e sistemas de Inteligência Artificial Generativa. O curso aborda técnicas para criação, refinamento e otimização de prompts, permitindo obter respostas mais precisas, consistentes e alinhadas aos objetivos de negócio. Além disso, explora boas práticas, padrões de prompting, limitações dos modelos e aplicações corporativas da Engenharia de Prompts.
Conteúdo Programatico
Module 1: Introduction to Prompt Engineering
- Fundamentals of Prompt Engineering
- Evolution of Generative AI
- Large Language Models overview
- How AI models interpret prompts
- Capabilities and limitations of AI systems
- Business applications of prompting
Module 2: Understanding Prompts and Responses
- Anatomy of a prompt
- Instructions, context and constraints
- Input and output relationships
- Response generation mechanisms
- Factors affecting output quality
- Common prompting mistakes
Module 3: Principles of Effective Prompt Design
- Clarity and specificity
- Goal-oriented prompting
- Context-rich instructions
- Structured communication techniques
- Output formatting strategies
- Prompt quality evaluation
Module 4: Core Prompting Techniques
- Zero-shot prompting
- One-shot prompting
- Few-shot prompting
- Role-based prompting
- Template-based prompting
- Comparative prompting approaches
Module 5: Advanced Prompt Engineering Techniques
- Chain-of-thought concepts
- Step-by-step reasoning prompts
- Self-reflection prompting
- Context expansion techniques
- Prompt chaining workflows
- Multi-step task orchestration
Module 6: Structured Output Generation
- Generating formatted responses
- Tables and reports
- JSON and structured outputs
- Business document generation
- Data extraction techniques
- Response validation methods
Module 7: Prompt Engineering for Business Applications
- Marketing and content creation
- Customer service interactions
- Human resources use cases
- Business analysis support
- Knowledge management applications
- Productivity enhancement workflows
Module 8: Prompt Engineering for Technical Users
- Software development assistance
- Documentation generation
- Code explanation and review
- Data analysis support
- Technical research workflows
- Automation opportunities
Module 9: Risks, Limitations and Responsible Use
- Hallucinations and inaccuracies
- Bias and fairness considerations
- Privacy and confidentiality concerns
- Security-related risks
- Prompt injection awareness
- Responsible AI practices
Module 10: Prompt Optimization Workshop
- Prompt testing methodologies
- Iterative prompt refinement
- Performance evaluation techniques
- Prompt library development
- Real-world case studies
- Final prompt engineering project