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 Duration 14 hours

Course Outline

Foundations of On-Device AI with Nano Banana

  • Essential mechanics of local inference
  • Overview of Nano Banana’s model structure and features
  • Strategic considerations for mobile platform implementation

Setting Up Nano Banana and the Development Workspace

  • Installation of Nano Banana SDK utilities
  • Configuration of Android and iOS build setups
  • Handling dependencies and ensuring version alignment

Executing Nano Banana Models on Mobile Hardware

  • Loading and running ready-made models
  • Navigating memory and processing limits on mobile chips
  • Techniques for real-time prediction

Developing AI Capabilities with Nano Banana

  • Embedding text generation services
  • Building workflows for image creation and modification
  • Merging multiple input types within applications

Enhancing Performance and Conducting Benchmarks

  • Analyzing latency and data throughput
  • Applying quantization, pruning, and compression methods
  • Optimizing for thermal stability, battery life, and resource consumption

Safeguarding Security and Privacy in Local AI

  • Managing local data flow and regulatory compliance
  • Securing models and execution environments
  • Identifying risks and implementing countermeasures

Advanced Implementation Strategies

  • Blending local and cloud-based operations
  • Maintaining offline-priority AI services
  • Expanding capacity for extensive user populations

Quality Assurance, Debugging, and Continuous Enhancement

  • Implementing CI/CD pipelines for AI-powered mobile apps
  • Conducting unit, integration, and performance assessments
  • Managing model iterations and maintaining backward compatibility

Recap and Future Pathways

Requirements

  • Foundational knowledge in mobile app creation
  • Proficiency in Python, Kotlin, or Swift
  • Working comprehension of machine learning principles

Target Audience

  • Mobile software engineers
  • AI specialists
  • Technical staff investigating local AI integration strategies

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

Building On-Device AI Apps with Nano Banana

2026-11-16 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Building On-Device AI Apps with Nano Banana

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

Building On-Device AI Apps with Nano Banana

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

Building On-Device AI Apps with Nano Banana

2026-12-28 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Building On-Device AI Apps with Nano Banana

2027-01-11 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

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