Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Edge AI Optimization
- General overview of edge AI and its associated challenges
- The significance of model optimization for edge devices
- Case studies featuring optimized AI models in edge applications
Model Compression Techniques
- Introduction to the concept of model compression
- Strategies for minimizing model size
- Practical exercises focused on model compression
Quantization Methods
- Overview of quantization and its advantages
- Categories of quantization (post-training, quantization-aware training)
- Practical exercises focused on model quantization
Pruning and Other Optimization Techniques
- Introduction to model pruning
- Approaches for pruning AI models
- Additional optimization techniques (e.g., knowledge distillation)
- Practical exercises focused on model pruning and optimization
Deploying Optimized Models on Edge Devices
- Setting up the edge device environment
- Deploying and evaluating optimized models
- Resolving deployment issues
- Practical exercises focused on model deployment
Tools and Frameworks for Optimization
- Overview of relevant tools and frameworks (e.g., TensorFlow Lite, ONNX)
- Utilizing TensorFlow Lite for model optimization
- Practical exercises using optimization tools
Real-World Applications and Case Studies
- Review of successful edge AI optimization projects
- Discussion of industry-specific use cases
- Practical project for building and optimizing a real-world application
Summary and Next Steps
Requirements
- A foundational grasp of AI and machine learning principles
- Practical experience in AI model development
- Fundamental programming proficiency (Python is recommended)
Target Audience
- AI developers
- Machine learning engineers
- System architects
Testimonials (2)
Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.
Matthew Gay - Tarsus Pharmaceuticals
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
