Visão Geral
Este curso foi desenvolvido para profissionais que desejam compreender e utilizar Inteligência Artificial sem a necessidade de conhecimentos em programação. O participante aprenderá os conceitos fundamentais da IA, suas aplicações práticas, ferramentas de IA generativa, automação de tarefas, análise de dados assistida por IA e estratégias para aumentar produtividade, inovação e eficiência nos negócios.
Conteúdo Programatico
Module 1: Introduction to Artificial Intelligence
- What is Artificial Intelligence
- History and evolution of AI
- Types of AI systems
- AI in everyday life
- Current AI trends
- Opportunities and challenges of AI adoption
Module 2: Understanding How AI Works
- Fundamentals of Machine Learning
- Deep Learning overview
- Generative AI concepts
- Large Language Models (LLMs)
- Data and AI relationships
- Understanding AI capabilities and limitations
Module 3: Generative AI for Daily Work
- Introduction to generative AI tools
- Text generation applications
- Content creation workflows
- Summarization and research assistance
- Productivity enhancement techniques
- Common business use cases
Module 4: Prompt Engineering Fundamentals
- What is prompt engineering
- Writing effective prompts
- Structuring instructions for AI systems
- Context and role-based prompting
- Iterative prompt improvement
- Avoiding common prompting mistakes
Module 5: AI for Communication and Content Creation
- Drafting emails and reports
- Creating presentations and summaries
- Marketing content generation
- Social media content assistance
- Meeting note generation
- Customer communication support
Module 6: AI for Data Analysis and Decision Support
- AI-assisted data analysis concepts
- Working with spreadsheets and reports
- Data interpretation techniques
- Business insights generation
- Decision-making support tools
- Analytical productivity workflows
Module 7: No-Code and Low-Code AI Tools
- Introduction to no-code AI platforms
- Workflow automation concepts
- AI-powered business applications
- Integrating AI into daily processes
- Automation opportunities identification
- Practical no-code use cases
Module 8: AI for Business and Organizational Transformation
- AI adoption strategies
- Process optimization opportunities
- Innovation with AI
- Customer experience enhancement
- AI-driven business models
- Measuring AI value and impact
Module 9: Ethics, Security and Responsible AI
- Ethical use of AI
- Privacy and data protection
- Bias and fairness considerations
- Responsible AI practices
- Security risks and mitigation
- Governance fundamentals
Module 10: Practical Applications and AI Adoption Roadmap
- Real-world business case studies
- Hands-on AI tool exercises
- Building personal AI workflows
- AI implementation planning
- Future trends in AI
- Developing an AI adoption roadmap