What You Need to Know Before
You Start
Starts 2 July 2025 14:34
Ends 2 July 2025
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Days
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Hours
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Minutes
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1 day 6 hours 55 minutes
Optional upgrade avallable
Not Specified
Progress at your own speed
Paid Course
Optional upgrade avallable
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
- Foundations of On-Device AI Technology
- Designing On-Device AI Models
- Development Tools and Frameworks
- Implementing On-Device AI
- Real-Time Data Processing and Decision Making
- Practical Applications and Use Cases
- Testing and Debugging On-Device AI Applications
- Future Trends and Developments
- Course Wrap-Up and Project Work
Overview of AI and Machine Learning
Importance of On-Device AI
Benefits over Cloud-Based AI
Hardware and Software Requirements
Edge Devices: Smartphones, Tablets, and IoT Devices
Performance and Resource Constraints
Model Selection for On-Device Applications
Techniques for Optimizing Model Performance
Model Compression and Quantization
Introduction to TensorFlow Lite
Overview of Core ML for iOS
PyTorch Mobile Basics
Setting Up Development Environment
Building and Deploying AI Models
Integrating AI Models with Mobile Applications
Handling Data Locally on Devices
Real-Time Inference and Feedback
Privacy and Security Considerations
Image and Video Processing
Natural Language Processing on-Device
AR and VR Enhancements with AI
Unit and Integration Testing
Performance Profiling and Monitoring
Addressing Common Issues and Bugs
Advances in Edge Computing
Potential for AI in Emerging Technologies
The Evolving Landscape of Mobile AI
Recap of Key Concepts
Capstone Project: Building an On-Device AI Application
Resources for Continued Learning
Taught by
Kumari Ravva
Subjects
Programming