Course Outline

Introduction to Energy-Efficient AI

  • The significance of sustainability in AI
  • Overview of energy consumption in machine learning
  • Case studies of energy-efficient AI implementations

Compact Model Architectures

  • Understanding model size and complexity
  • Techniques for designing small yet effective models
  • Comparing different model architectures for efficiency

Optimization and Compression Techniques

  • Model pruning and quantization
  • Knowledge distillation for smaller models
  • Efficient training methods to reduce energy usage

Hardware Considerations for AI

  • Selecting energy-efficient hardware for training and inference
  • The role of specialized processors like TPUs and FPGAs
  • Balancing performance and power consumption

Green Coding Practices

  • Writing energy-efficient code
  • Profiling and optimizing AI algorithms
  • Best practices for sustainable software development

Renewable Energy and AI

  • Integrating renewable energy sources in AI operations
  • Data center sustainability
  • The future of green AI infrastructure

Lifecycle Assessment of AI Systems

  • Measuring the carbon footprint of AI models
  • Strategies for reducing environmental impact throughout the AI lifecycle
  • Case studies on lifecycle assessment in AI

Policy and Regulation for Sustainable AI

  • Understanding global standards and regulations
  • The role of policy in promoting energy-efficient AI
  • Ethical considerations and societal impact

Project and Assessment

  • Developing a prototype using small language models in a chosen domain
  • Presentation of the energy-efficient AI system
  • Evaluation based on technical efficiency, innovation, and environmental contribution

Summary and Next Steps


  • Solid understanding of deep learning concepts
  • Proficiency in Python programming
  • Experience with model optimization techniques


  • Machine learning engineers
  • AI researchers and practitioners
  • Environmental advocates within the tech industry
 21 Hours

Number of participants

Price per participant