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 Nano Banana
- Fundamental overview of the framework and its features
- Insight into the underlying architecture and data processing flow
- Evaluation of Nano Banana against alternative on-device AI options
Configuring the Development Workspace
- Setting up Android Studio to handle AI-specific tasks
- Incorporating the Nano Banana SDK into the project
- Managing project settings and library dependencies
Utilizing Nano Banana Interfaces
- Investigation of primary API functions
- Loading and overseeing compact models
- Carrying out inference operations with minimal delay
Enhancing AI Efficiency on Android
- Approaches for achieving low-latency responses
- Techniques for managing memory and system resources
- Methods for benchmarking and utilizing optimization utilities
Crafting AI-Centric User Interfaces
- Building responsive user interactions
- Managing asynchronous operations and callback mechanisms
- Ensuring AI behavior aligns with Android user experience standards
Security and Privacy in Local AI
- Safeguarding user information during processing
- Implementing methods that protect privacy during inference
- Addressing compliance requirements for corporate use cases
Releasing and Managing AI Capabilities
- Prepping and distributing apps with integrated AI
- Managing version control and updates for local models
- Tracking and refining performance after launch
Complex Applications and Extensions
- Integrating Nano Banana with current Android ML utilities
- Developing multimodal AI functionalities
- Expanding app capabilities using custom, lightweight models
Recap and Future Directions
Requirements
- Foundational knowledge of Android application development
- Proficiency in Kotlin or Java
- Basic knowledge of mobile app debugging processes
Target Audience
- Android developers creating AI-powered applications
- Software engineers investigating on-device machine learning pipelines
- Technical teams assessing lightweight AI deployment strategies on Android
Testimonials (1)
Flow , vibe and topic on presentation
