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Duration 21 hours
Course Outline
Introduction to TinyML and Embedded AI
- Key characteristics of TinyML model deployment
- Limitations within microcontroller environments
- Overview of embedded AI toolchains
Foundations of Model Optimisation
- Understanding computational bottlenecks
- Identifying operations that consume significant memory
- Establishing baseline performance profiles
Quantisation Techniques
- Strategies for post-training quantisation
- Quantisation-aware training
- Assessing the trade-off between accuracy and resource usage
Pruning and Compression
- Structured and unstructured pruning methods
- Weight sharing and model sparsity
- Compression algorithms for lightweight inference
Hardware-Aware Optimisation
- Deploying models on ARM Cortex-M systems
- Optimising 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
- Utilising TensorFlow Lite Micro for embedded deployment
- Integrating TinyML models with Edge Impulse pipelines
- Testing and debugging on physical hardware
Advanced Optimisation Strategies
- Neural architecture search for TinyML
- Hybrid approaches combining quantisation and pruning
- Model distillation for embedded inference
Summary and Next Steps
Requirements
- A solid grasp of machine learning workflows
- Practical experience with embedded systems or microcontroller-based development
- Proficiency in Python programming
Target Audience
- AI researchers
- Embedded ML engineers
- Professionals developing resource-constrained inference systems
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 3900 € + VAT*
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