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 Duration 14 hours

Course Outline

Introduction to Vertex AI for Mobile and Web Applications

  • Exploring the potential of Gemini within applications
  • Integration strategies using Firebase and SDKs
  • Real-world use cases for embedded AI

Preparing the Development Environment

  • Initiating and configuring Firebase projects
  • Setup and configuration of Vertex AI SDKs
  • Practical lab: Establishing the development environment

Integrating Gemini into Applications

  • Interacting with Gemini APIs from client applications
  • Implementing text, image, and audio functionality
  • Practical lab: Developing a feature powered by Gemini

Managing Multimodal Inputs

  • Capturing and processing diverse user inputs (voice, image, text)
  • Designing interactive workflows with Gemini
  • Practical lab: Implementing multimodal input features

Application Deployment and Oversight

  • Releasing AI-enhanced applications to production
  • Tracking performance and usage via Firebase
  • Practical lab: Deploying and verifying app functionality

Addressing Security and Compliance

  • Best practices for data management in AI contexts
  • Ensuring user privacy and consent mechanisms
  • Practical lab: Hardening AI features for security

Case Studies and Industry Best Practices

  • Illustrative examples of Gemini in consumer and enterprise contexts
  • Insights gained from real-world implementations
  • Optimizing for scalable AI features in applications

Recap and Future Directions

Requirements

  • Fundamental programming proficiency in JavaScript, Kotlin, or Swift
  • Working knowledge of mobile or web application development
  • Practical experience with Firebase or other cloud-based SDKs

Intended Audience

  • Mobile developers
  • Web developers
  • Product teams

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