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 Duration 14 hours

Course Outline

Introduction to Edge AI Optimisation

  • Overview of edge AI and its challenges
  • The importance of model optimisation for edge devices
  • Case studies of optimised AI models in edge applications

Model Compression Techniques

  • Introduction to model compression
  • Techniques for reducing model size
  • Hands-on exercises for model compression

Quantisation Methods

  • Overview of quantisation and its benefits
  • Types of quantisation (post-training, quantisation-aware training)
  • Hands-on exercises for model quantisation

Pruning and Other Optimisation Techniques

  • Introduction to pruning
  • Methods for pruning AI models
  • Other optimisation techniques (e.g., knowledge distillation)
  • Hands-on exercises for model pruning and optimisation

Deploying Optimised Models on Edge Devices

  • Preparing the edge device environment
  • Deploying and testing optimised models
  • Troubleshooting deployment issues
  • Hands-on exercises for model deployment

Tools and Frameworks for Optimisation

  • Overview of tools and frameworks (e.g., TensorFlow Lite, ONNX)
  • Using TensorFlow Lite for model optimisation
  • Hands-on exercises with optimisation tools

Real-World Applications and Case Studies

  • Review of successful edge AI optimisation projects
  • Discussion of industry-specific use cases
  • Hands-on project for building and optimising a real-world application

Summary and Next Steps

Requirements

  • A solid understanding of AI and machine learning concepts
  • Experience in AI model development
  • Basic programming proficiency (Python is recommended)

Target Audience

  • AI developers
  • Machine learning engineers
  • System architects

Number of participants


Price per participant

Open Training Courses require 5+ participants.

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

Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking

Provisional Upcoming Courses (Require 5+ participants)

Optimizing AI Models for Edge Devices

2026-11-23 09:30
14 hours
Melbourne 385 Bourke Street
7000 AUD (Online)
13600 AUD (Classroom)

Optimizing AI Models for Edge Devices

2026-12-07 09:30
14 hours
Cliftons Perth
7000 AUD (Online)
14200 AUD (Classroom)

Optimizing AI Models for Edge Devices

2026-12-21 09:30
14 hours
Sydney King Street
7000 AUD (Online)
13600 AUD (Classroom)

Optimizing AI Models for Edge Devices

2027-01-04 09:30
14 hours
London Circuit
7000 AUD (Online)
13600 AUD (Classroom)

Optimizing AI Models for Edge Devices

2027-01-18 09:30
14 hours
200 Mary Street, Brisbane
7000 AUD (Online)
13600 AUD (Classroom)

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Edge AI