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 Duration 21 hours

Course Outline

Introduction to Edge AI and TinyML

  • Overview of AI at the edge
  • Advantages and challenges of executing AI on devices
  • Applications in robotics and automation

Foundations of TinyML

  • Machine learning for resource-constrained systems
  • Model quantization, pruning, and compression techniques
  • Supported frameworks and hardware platforms

Model Development and Conversion

  • Training lightweight models using TensorFlow or PyTorch
  • Converting models to TensorFlow Lite and PyTorch Mobile
  • Testing and validating model accuracy

Implementing On-Device Inference

  • Deploying AI models to embedded boards (Arduino, Raspberry Pi, Jetson Nano)
  • Integrating inference with robotic perception and control
  • Executing real-time predictions and monitoring performance

Optimizing for Edge Performance

  • Reducing latency and energy consumption
  • Utilizing hardware acceleration with NPUs and GPUs
  • Benchmarking and profiling embedded inference

Edge AI Frameworks and Tools

  • Working with TensorFlow Lite and Edge Impulse
  • Exploring deployment options with PyTorch Mobile
  • Debugging and tuning embedded ML workflows

Practical Integration and Case Studies

  • Designing edge AI perception systems for robots
  • Integrating TinyML with ROS-based robotics architectures
  • Case studies: autonomous navigation, object detection, predictive maintenance

Summary and Next Steps

Requirements

  • A solid understanding of embedded systems
  • Practical experience with Python or C++ programming
  • Basic familiarity with machine learning concepts

Audience

  • Embedded developers
  • Robotics engineers
  • System integrators focused on intelligent devices

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.
Investment

Price per private group, online live training, starting from 3900 € + VAT*

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