Visão Geral
Este curso apresenta os fundamentos da Inteligência Artificial Generativa, explorando como modelos avançados são capazes de criar textos, imagens, códigos, vídeos, áudios e outros tipos de conteúdo. O participante compreenderá os conceitos, tecnologias, aplicações práticas, oportunidades de negócio, riscos e limitações da IA Generativa, além de aprender a utilizar ferramentas modernas para aumentar produtividade, criatividade e inovação.
Conteúdo Programatico
Module 1: Introduction to Generative AI
- What is Generative AI
- Evolution of generative technologies
- Generative AI versus traditional AI
- Key concepts and terminology
- Current market landscape
- Business impact of Generative AI
Module 2: Foundations of Large Language Models
- Introduction to Large Language Models (LLMs)
- How language models work
- Training and inference concepts
- Tokens and embeddings fundamentals
- Capabilities and limitations of LLMs
- Examples of LLM applications
Module 3: Generative AI for Text Creation
- Text generation fundamentals
- Content creation workflows
- Summarization and rewriting
- Translation and language assistance
- Business communication use cases
- Productivity enhancement techniques
Module 4: Generative AI for Images, Audio and Video
- Image generation concepts
- AI-assisted design and creativity
- Audio generation fundamentals
- Video generation overview
- Multimodal AI concepts
- Creative industry applications
Module 5: Prompt Engineering Fundamentals
- Principles of effective prompting
- Structuring prompts for better results
- Context and instruction design
- Role-based prompting techniques
- Prompt refinement strategies
- Common prompting mistakes
Module 6: Generative AI for Business Applications
- Customer service automation
- Marketing and sales applications
- Human resources use cases
- Knowledge management support
- Process optimization opportunities
- Innovation and product development
Module 7: Generative AI for Software Development
- AI-assisted coding concepts
- Code generation fundamentals
- Documentation creation
- Testing and debugging assistance
- Developer productivity workflows
- Limitations of AI-generated code
Module 8: Risks, Ethics and Governance
- Ethical considerations in Generative AI
- Hallucinations and misinformation
- Bias and fairness challenges
- Privacy and data protection
- Intellectual property considerations
- Responsible AI practices
Module 9: Generative AI Adoption Strategies
- Organizational readiness assessment
- Identifying high-value use cases
- Implementation planning
- Change management considerations
- Measuring business value
- Governance frameworks
Module 10: Future Trends and Practical Applications
- Emerging Generative AI technologies
- Agentic AI and autonomous systems
- Industry transformation trends
- Real-world case studies
- Building an AI adoption roadmap
- Future skills and career opportunities