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Starts 2 July 2025 14:34

Ends 2 July 2025

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The complete guide to Build on-Device AI Applications

You will learn how to build on-Device AI Applications with JavaScript and deploy AI Applications to various devices!
via Udemy

4123 Courses


1 day 6 hours 55 minutes

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Overview

You are going to learn how to Build on-Device AI Applications with AI. On-device AI applications represent a significant evolution in the way artificial intelligence is deployed and utilized, allowing for real-time data processing and decision-making directly on a user's device, without relying on cloud services.

This advancement leverages the increasing computational power of smartphones, tablets, and other edge devices, creating a powerful blend of speed, privacy, and functionality that benefits both users and developers.

Syllabus

  • Introduction to On-Device AI
  • Overview of AI and Machine Learning
    Importance of On-Device AI
    Benefits over Cloud-Based AI
  • Foundations of On-Device AI Technology
  • Hardware and Software Requirements
    Edge Devices: Smartphones, Tablets, and IoT Devices
    Performance and Resource Constraints
  • Designing On-Device AI Models
  • Model Selection for On-Device Applications
    Techniques for Optimizing Model Performance
    Model Compression and Quantization
  • Development Tools and Frameworks
  • Introduction to TensorFlow Lite
    Overview of Core ML for iOS
    PyTorch Mobile Basics
  • Implementing On-Device AI
  • Setting Up Development Environment
    Building and Deploying AI Models
    Integrating AI Models with Mobile Applications
  • Real-Time Data Processing and Decision Making
  • Handling Data Locally on Devices
    Real-Time Inference and Feedback
    Privacy and Security Considerations
  • Practical Applications and Use Cases
  • Image and Video Processing
    Natural Language Processing on-Device
    AR and VR Enhancements with AI
  • Testing and Debugging On-Device AI Applications
  • Unit and Integration Testing
    Performance Profiling and Monitoring
    Addressing Common Issues and Bugs
  • Future Trends and Developments
  • Advances in Edge Computing
    Potential for AI in Emerging Technologies
    The Evolving Landscape of Mobile AI
  • Course Wrap-Up and Project Work
  • Recap of Key Concepts
    Capstone Project: Building an On-Device AI Application
    Resources for Continued Learning

Taught by

Kumari Ravva


Subjects

Programming