Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Vertex AI for Mobile & Web Applications
- Overview of Gemini’s capabilities within applications
- Integration pathways for Firebase and SDKs
- Practical use cases for embedded AI
Configuring the Development Environment
- Setting up and configuring Firebase projects
- Installing and configuring Vertex AI SDKs
- Practical lab: Environment initialization
Integrating Gemini into Applications
- Invoking Gemini APIs from client applications
- Incorporating text, image, and audio capabilities
- Practical lab: Developing a Gemini-driven feature
Managing Multimodal Input
- Capturing and processing user inputs (voice, image, text)
- Designing interactive app workflows with Gemini
- Practical lab: Implementing multimodal input features
App Deployment and Monitoring
- Releasing AI-enabled applications to production
- Tracking performance and usage via Firebase
- Practical lab: Deploying and testing applications
Security and Compliance Factors
- Best practices for data management in AI features
- User privacy and consent mechanisms in applications
- Practical lab: Securing AI-enabled components
Case Studies and Best Practices
- Illustrative examples of Gemini in consumer and enterprise applications
- Insights gained from real-world implementations
- Strategies for scalable AI features in applications
Conclusion and Next Steps
Requirements
- Foundational programming proficiency in JavaScript, Kotlin, or Swift
- Understanding of mobile or web application development workflows
- Prior experience with Firebase or cloud-based SDKs
Target Audience
- Mobile developers
- Web developers
- Product teams
Testimonials (1)
easy steps in ML