Temario del curso

Introduction to Google AI Studio

  • Core features and capabilities
  • Understanding workflow components
  • Exploring the Google AI model ecosystem

Designing AI Workflows

  • Structuring end-to-end workflows
  • Choosing components for automation
  • Managing inputs, outputs, and parameters

Model Integration and API Usage

  • Connecting AI Studio with Google AI APIs
  • Integrating custom and third-party models
  • Building reusable components

Testing and Validation

  • Creating test scenarios
  • Validating workflow reliability
  • Debugging model interactions

Performance Optimization

  • Improving response speed and efficiency
  • Managing resource usage
  • Scaling workflows for production

Security and Compliance

  • Access control and user management
  • Data protection principles
  • Ensuring secure API communication

Monitoring and Maintenance

  • Monitoring workflow performance
  • Logging and analytics
  • Lifecycle management for deployed workflows

Extending AI Studio Workflows

  • Integrating with external tools
  • Automating with cloud functions
  • Enhancing functionality using third-party services

Summary and Next Steps

Requerimientos

  • An understanding of AI model development workflows
  • Experience with cloud-based tools or platforms
  • Familiarity with prompt engineering concepts

Audience

  • AI operations teams
  • DevOps professionals
  • System administrators
 14 Horas

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