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Artificial Intelligence
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Maven

Sustainable AI - Reducing Carbon Footprint and Optimizing Performance

  • up to 4 weeks
  • Intermediate
  • Cohort-based

This course empowers you to reduce the carbon footprint of AI applications in the cloud while optimizing performance and cost. Learn to monitor and optimize AI workloads, minimizing energy consumption and increasing efficiency.

  • Environmental Impact of AI
  • AI Application Design
  • Energy Efficiency
  • Sustainable Practices in AI

Overview

In this course, you will delve into the environmental impact of AI applications and learn how to architect and design sustainable AI solutions. Explore best practices for optimizing AI workloads, reducing energy consumption, and demonstrating ROI to management. Engage with real-life case studies and industry trends to understand how leaders implement sustainable AI practices.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Professional Certification
    upon course completion
  • Full-time / Part-time
    schedule flexibility
  • Live classes
    delivered online

Who is this course for?

Career Transitioners in Climate Tech

Gain valuable background on top of mind topics in the climate tech field.

CTOs, CIOs, and Technology Leaders

Shape an organization's technology strategy and investments with sustainable AI practices.

IT Consultants

Advise clients on sustainable AI/ML strategies and implementation.

This course offers key insights into reducing the environmental impact of AI while optimizing performance and cost. Ideal for professionals in climate tech, IT consulting, and technology leadership, it provides the tools to integrate sustainability into AI development and deployment.

Pre-Requisites

1 / 2

  • Cloud infrastructure foundation

  • General knowledge about AI

What will you learn?

Environmental Impact of AI
Understand the large impact of AI on datacenter usage, server energy consumption, GPUs, and data storage. Learn how to measure and mitigate these effects.
Energy Efficient Model Training and Inference
Explore techniques for training and inference that minimize energy consumption while maintaining performance.
Green Software Development and Implementation for AI/LLM Applications
Learn best practices for developing and implementing AI applications with a focus on sustainability.
Industry Trends in Sustainable AI
Discover the most promising trends to limit the environmental impact of AI and make its growth more sustainable.
End to End Case Study
Analyze real-life examples to understand how leaders in the field have implemented sustainable AI practices.

What learners say about this course

  • “I gained a lot of readily applicable knowledge on sustainable AI. Good for performance, good for climate.”

    Nolwenn

    Cohort 2

  • “Good course for beginners to understand the building blocks of an application.”

    Writam

    Product Manager

  • “The course provides a foundational understanding of what does and doesn’t make the use of AI sustainable. It’s great for folks who are battling the dichotomy of using AI tools to stay on top of the revolution and the fact that they often come with the baggage of huge energy loads.”

    Akhila

    Co-founder

Meet your instructor

  • Pascal Joly

    Sustainability Consultant, IT Climate Ed

    With over 25 years of IT experience and a deep passion for environmental sustainability, Pascal is a renowned consultant dedicated to helping organizations drive meaningful progress towards a greener future.

Upcoming cohorts

  • Dates

    Feb 4 — Feb 25, 2026

  • Dates

    Feb 4 — Feb 25, 2026

$899