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.
Course Outline
Introduction to TinyML and Embedded AI
- Key characteristics of TinyML model deployment
- Constraints present in microcontroller environments
- Overview of embedded AI toolchains
Foundations of Model Optimization
- Identifying computational bottlenecks
- Detecting memory-intensive operations
- Conducting baseline performance profiling
Techniques for Quantization
- Strategies for post-training quantization
- Quantization-aware training methods
- Assessing the trade-off between accuracy and resource usage
Pruning and Compression
- Methods for structured and unstructured pruning
- Weight sharing and achieving model sparsity
- Compression algorithms designed for lightweight inference
Hardware-Aware Optimization
- Deploying models on ARM Cortex-M systems
- Optimizing for DSP and accelerator extensions
- Considerations for memory mapping and dataflow
Benchmarking and Validation
- Analysis of latency and throughput
- Measurement of power and energy consumption
- Testing for accuracy and robustness
Deployment Workflows and Tools
- Utilizing TensorFlow Lite Micro for embedded deployment
- Integrating TinyML models with Edge Impulse pipelines
- Testing and debugging on actual hardware
Advanced Optimization Strategies
- Neural architecture search applied to TinyML
- Hybrid approaches combining quantization and pruning
- Model distillation for embedded inference
Summary and Next Steps
Requirements
- A solid grasp of machine learning workflows
- Experience with embedded systems or development on microcontrollers
- Proficiency in Python programming
Target Audience
- AI researchers
- Embedded ML engineers
- Specialists working on resource-constrained inference systems
21 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
Contact us for an exact quote and to hear our latest promotions
