What You'll Learn
Comprehensive curriculum designed by industry experts
Mobile AI Basics
- AI in Mobile
- On-Device vs Cloud Inference
- TensorFlow Lite Overview
- Core ML Overview
- Use Cases
- performance Considerations
On-Device ML
- TFLite Implementation
- Core ML Models
- Image Classification
- Object Detection
- Audio Processing
- Text Recognition
Cloud AI Integration
- Firebase ML
- Google Cloud Vision API
- AWS Rekognition
- OpenAI API for Mobile
- Speech-to-Text
- Chat Interfaces
Full App Integration
- Model Optimization
- Real-time Inference
- Camera Integration
- AR Features
- User Experience for AI
- Privacy & Security
Live Projects
Build real-world applications that look great on your portfolio
Plant Disease Detector
Build an app that identifies plant diseases from camera photos using on-device ML.
Flutter/React NativeTFLiteCamera APIOffline Model
Voice Assistant App
Create a voice-controlled app with natural language understanding.
Speech APIOpenAI APIText-to-SpeechMobile UI
Prerequisites
- Strong mobile development skills (Flutter/RN/Native)
- Basic ML understanding
- Python knowledge (bonus)
Career Outcomes
- Integrate ML models in apps
- Build AI-powered features
- Optimize models for mobile
- Create smart user experiences
Tools You'll Master
TensorFlow LiteCore ML ToolsFirebase MLVS Code/Xcode
Certification
AI Mobile App Specialist Certificate
Performance-based stipend
Apply for This Internship
Start your journey with AI-Powered Mobile App Internship