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Duration 14 hours
Course Outline
Introduction to Vertex AI for Mobile & Web Applications
- Overview of Gemini's capabilities within app contexts
- Integration pathways for Firebase and SDKs
- Practical use cases for embedded AI
Establishing the Development Environment
- Firebase project initiation and configuration
- Installation and setup of Vertex AI SDKs
- Practical exercise: Environment configuration
Integrating Gemini into Applications
- Invoking Gemini APIs from client-side applications
- Incorporating text, image, and audio functionalities
- Practical exercise: Developing a Gemini-powered feature
Managing Multimodal Inputs
- Capturing and processing user inputs (voice, image, text)
- Designing interactive app workflows with Gemini
- Practical exercise: Implementing multimodal input handling
Deployment and Monitoring of Applications
- Releasing AI-enhanced apps to production environments
- Tracking performance and usage metrics via Firebase
- Practical exercise: Deploying and testing applications
Security and Compliance Frameworks
- Best practices for data management in AI features
- Ensuring user privacy and consent within apps
- Practical exercise: Securing an AI feature
Case Studies and Industry Best Practices
- Real-world examples of Gemini in consumer and enterprise solutions
- Key insights from practical implementations
- Strategies for scaling AI features within applications
Conclusion and Future Directions
Requirements
- Fundamental programming skills in JavaScript, Kotlin, or Swift
- Working knowledge of mobile or web application development
- Prior experience with Firebase or cloud-based SDKs
Target Audience
- Mobile developers
- Web developers
- Product teams
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