• Understand the concept of Green AI and its importance.

• Learn how energy consumption impacts AI model training.

• Apply energy-efficient algorithms and model compression techniques.

• Use cloud-based sustainability tools and APIs.

• Analyse and reduce carbon footprints of AI workflows.

• Explore hardware-level sustainability in GPUs, TPUs, and edge devices.

• Design lightweight, low-power neural networks.

• Implement monitoring for energy and carbon metrics.

• Align AI projects with global sustainability goals (SDGs, ESG).

• Prepare for leadership roles in sustainable AI and ethical computing.

Course Syllabus

Module 1: Introduction to Green AI and Sustainable Computing
Module 2: Environmental Impact of AI and Data Centres
Module 3: Algorithmic Efficiency and Model Compression
Module 4: Energy-Aware Hardware – GPUs, TPUs, and Edge Devices
Module 5: Sustainable Data Practices and Cloud Management
Module 6: Carbon-Aware Scheduling and Workload Optimisation
Module 7: Green AI Frameworks – TensorFlow Lite, ONNX, PyTorch Mobile
Module 8: ESG, SDG, and Ethical AI Governance
Module 9: Case Studies – Climate Tech, Smart Grids, and Energy AI
Module 10: Capstone Project – Build a Carbon-Aware AI Model

Upon successful completion, learners receive a Certificate of Completion from Uplatz, validating their expertise in Green AI and Sustainable Computing. This Uplatz certification demonstrates your ability to design, evaluate, and implement energy-efficient AI systems that adhere to sustainability principles.

The certification aligns with global goals such as the UN Sustainable Development Goals (SDGs) and corporate ESG frameworks, making it highly relevant for professionals in AI engineering, sustainability strategy, and ethical technology innovation.

Holding this certificate establishes your commitment to responsible innovation — ensuring that your AI projects contribute positively to both society and the planet.

Sustainability has become a top priority across all technology sectors. Completing this course from Uplatz prepares you for impactful roles such as:

• Sustainable AI Engineer

• Green Computing Specialist

• AI Ethics and Sustainability Consultant

• Cloud Sustainability Architect

• Data Centre Efficiency Analyst

Professionals in this domain typically earn between $100,000 and $185,000 per year, with roles available in tech companies, climate tech startups, research institutions, and ESG-focused consultancies.

This course equips you to lead the transition toward energy-efficient, transparent, and carbon-aware AI systems, contributing to global sustainability and ethical innovation.

1. What is Green AI?
   It’s an approach to AI that prioritises efficiency, transparency, and reduced environmental impact.

2. How does AI impact the environment?
   Through large-scale energy use in training and running ML models, leading to carbon emissions.

3. What is model compression?
   Techniques like pruning and quantisation that reduce model size and energy use.

4. What are examples of Green AI frameworks?
   TensorFlow Lite, PyTorch Mobile, and ONNX Runtime.

5. What is carbon-aware scheduling?
   Allocating workloads based on real-time grid carbon intensity to lower emissions.

6. How can data centres become more sustainable?
   By using renewable energy, efficient cooling, and smart workload management.

7. What are SDGs and ESGs in AI?
   Frameworks promoting sustainability, ethics, and governance in technology development.

8. How can AI help fight climate change?
   By optimising energy use, predicting environmental risks, and managing renewable systems.

9. What are major challenges in sustainable computing?
   Balancing accuracy with energy efficiency and tracking emissions transparently.

10. What is the future of Green AI?
    AI systems will be designed with carbon budgets, efficiency metrics, and environmental accountability.