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 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
Testimonials (1)
easy steps in ML