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 Duration 14 hours

Course Outline

Introduction to the Nano Banana Framework

  • An overview of the framework’s core capabilities
  • Analyzing the architecture and data processing pipeline
  • Comparative analysis of Nano Banana against other on-device AI alternatives

Configuring the Development Environment

  • Preparing Android Studio to handle AI workloads
  • Incorporating the Nano Banana SDK into the project
  • Managing project configurations and dependencies

Utilizing Nano Banana APIs

  • Investigating essential API methods
  • Loading and administering lightweight models
  • Performing inference tasks in real time

Enhancing AI Performance on Android

  • Methods for achieving low-latency inference
  • Tactics for managing memory and system resources
  • Benchmarking methodologies and available optimization tools

Crafting AI-Driven User Experiences

  • Building responsive user interface interactions
  • Managing asynchronous operations and callback functions
  • Aligning AI behaviors with Android UX standards

Security and Privacy in On-Device AI

  • Guaranteeing the secure processing of user data
  • Implementing privacy-preserving inference techniques
  • Addressing compliance requirements for enterprise rollouts

Deployment and Maintenance of AI Features

  • Packaging and releasing applications with embedded AI
  • Managing versioning and updates for local models
  • Monitoring and refining performance after deployment

Advanced Applications and Integrations

  • Combining Nano Banana with existing Android ML utilities
  • Developing multimodal AI functionalities
  • Extending applications using custom lightweight models

Recap and Future Directions

Requirements

  • A solid grasp of Android application development basics
  • Practical experience working with Kotlin or Java
  • Foundational knowledge of mobile app debugging processes

Target Audience

  • Android developers focused on creating AI-augmented applications
  • Software engineers investigating on-device machine learning workflows
  • Technical teams assessing lightweight AI deployment strategies on Android

Number of participants


Price per participant

Open Training Courses require 5+ participants.

Testimonials (1)

Flow , vibe and topic on presentation

Lukasz Kowalczyk - Allegro Sp. z o.o.
Course - Google Gemini AI for Data Analysis

Upcoming Courses

Nano Banana for Android Developers: Lightweight AI Integration

2026-11-05 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Nano Banana for Android Developers: Lightweight AI Integration

2026-11-19 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Nano Banana for Android Developers: Lightweight AI Integration

2026-12-03 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Nano Banana for Android Developers: Lightweight AI Integration

2026-12-17 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Nano Banana for Android Developers: Lightweight AI Integration

2026-12-31 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Nano Banana for Android Developers: Lightweight AI Integration

2027-01-14 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

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