Gracias por enviar su consulta! Uno de los miembros de nuestro equipo se pondrá en contacto con usted en breve.
Gracias por enviar su reserva! Uno de los miembros de nuestro equipo se pondrá en contacto con usted en breve.
Programa del Curso
Module 1: Introduction to AI and Google Gemini
- What is Artificial Intelligence (AI)?
- Overview of Google Gemini AI and its ecosystem
- Key features and advantages of Gemini over other AI models
- Hands-on Activity: Exploring Gemini AI through the Google AI Studio demo
Module 2: Understanding Large Language Models (LLMs)
- Fundamentals of large language models
- The architecture and operation of Gemini models
- Comparing Gemini with GPT and other leading models
- Practice Lab: Visualizing tokenization and model responses using sample prompts
Module 3: Getting Started with Gemini
- Setting up the development environment
- Working with the Gemini API and SDK
- Authentication, tokens, and API keys
- Hands-on Lab: Running your first Gemini prompt using Python
Module 4: Working with Gemini Models
- Exploring different Gemini model types and capabilities
- Selecting appropriate models for language, image, or multimodal tasks
- Initializing and testing generative models
- Practical Exercise: Comparing text-to-text and image-to-text model outputs
Module 5: Practical Applications and Use Cases
- Integrating Gemini AI into chat and Q&A applications
- Developing semantic search and summarization tools
- Ethical AI usage and bias considerations
- Group Project: Build a “Smart Research Assistant” using NotebookLM and Gemini
Module 6: Advanced Features and Customization
- Prompt optimization and advanced context handling
- Using Gemini for code generation and debugging
- Fine-tuning workflows with Google Cloud Vertex AI
- Hands-on Activity: Customizing model responses using parameters and temperature control
Module 7: Real-World Projects and Collaboration
- Collaborative project planning and workflow setup
- Integrating Gemini AI with other Google tools (Drive, Docs, Sheets)
- Team Project: Design and deploy a small AI application (e.g., content summarizer, chatbot, or idea generator)
- Peer review and discussion of project results
Module 8: Evaluation and Future Directions
- Troubleshooting common issues in Gemini projects
- Exploring the Gemini API roadmap and upcoming features
- Best practices for AI governance and scalability
- Wrap-up Activity: Reflection on practical lessons learned and career applications
Summary and Next Steps
Requerimientos
- An understanding of basic AI concepts
- Experience with APIs and cloud services
- Python programming experience
Audience
- Developers
- Data scientists
- AI enthusiasts
14 Horas
Testimonios (1)
Flow , vibe and topic on presentation
