Sustainable AI - Reducing Carbon Footprint and Optimizing Performance
4.3
(3 ratings)
3 Weeks
·Cohort-based Course
Learn how you can reduce the Carbon Footprint of your AI applications in the Cloud and Optimize Performance and Cost.
Course overview
Optimize your AI applications for sustainability
This course will enable you to understand the environmental impact of AI applications, how to monitor and optimize your AI workloads to minimize their energy consumption, increase performance and decrease cost.
Who is this course for
01
CTOs, CIOs and Technology Leaders who shape an organization's technology strategy and investments.
02
IT consultants and AI solution architects will gain the expertise to advise clients on sustainable AI/ML strategies and implementation.
03
This course empowers AI/ML Engineers and Data Scientists to reduce the carbon footprint of their workloads while optimizing performance.
04
DevOps professionals and Cloud Engineers can use the knowledge from this class to incorporate sustainable practices into their workflows.
05
AI/ML Product Managers can differentiate their offerings by incorporating sustainable practices from the ground up.
What you will get out of this course:
Learn about the environmental impact of AI
AI has a large impact on datacenter usage, server energy consumption, GPUs and data storage. How do you measure it and what are the consequences.
Architect and Design a sustainable AI application
From LLM optimization techniques, to parameter tuning, we'll explore best practices to architect and design a sustainable AI application.
Sustainable deployment in the cloud
Learn about the tools available for deploying your AI workload in the most energy efficient way, including cloud services and GPU optimization techniques. How do you continuously monitor its carbon footprint?
Demonstrate to management the ROI of AI applications
Adopting sustainable practices also has a direct impact on lowering the costs of AI cloud usage. It can be a powerful lever to justify to your management the ROI of AI applications development and adoption.
Industry trends in the field of sustainable AI
What are the most promising trends to limit the environmental impact of AI LLM and make its growth more sustainable.
End to end case study
Discover real life examples and understand how leaders in the space have implemented these practices.
This course includes
5 interactive live sessions
Lifetime access to course materials
15 in-depth lessons
Direct access to instructor
3 projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Sustainable AI - Reducing Carbon Footprint and Optimizing Performance
Course syllabus
Week 1
Jul 16—Jul 21
Week dates are set to instructor's time zoneEvents
- Jul
16
Session 1: Environmental Impact of AI
Session 1: Environmental Impact of AI
Tue, Jul 16, 7:00 PM - 8:30 PM UTC
- Jul
18
Office Hours Week 1
Office Hours Week 1
Thu, Jul 18, 7:00 PM - 9:00 PM UTC
Modules
- Week 1: Environmental Impact of AIWeek 1: Environmental Impact of AI4 Lessons • 1 Project
Week 2
Jul 22—Jul 28
Week dates are set to instructor's time zoneEvents
- Jul
23
Session 2: Energy Efficient Model training and inference
Session 2: Energy Efficient Model training and inference
Tue, Jul 23, 7:00 PM - 8:30 PM UTC
- Jul
25
Office Hours Week 2
Office Hours Week 2
Thu, Jul 25, 7:00 PM - 9:00 PM UTC
Modules
- Energy-efficient Model Training and InferenceEnergy-efficient Model Training and Inference4 Lessons • 1 Project
Week 3
Jul 29—Jul 30
Week dates are set to instructor's time zoneEvents
- Jul
30
Session 3: Green Software Development and Implementation for AI/LLM Applications
Session 3: Green Software Development and Implementation for AI/LLM Applications
Tue, Jul 30, 7:00 PM - 8:30 PM UTC
Modules
- Green Software Development and Implementation for AI/LLM ApplicationsGreen Software Development and Implementation for AI/LLM Applications7 Lessons • 1 Project
4.3
(3 ratings)
What students are saying
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 sustainability consultant dedicated to helping organizations drive meaningful progress towards a greener future. As the instructor of this MasterClass, Pascal brings a wealth of expertise in optimizing digital transformation initiatives and mitigating the effects of climate change.
Drawing from his extensive background, Pascal offers a comprehensive suite of services - from engaging educational climate workshops to expert green IT consulting and cloud partnership strategy.
Join an upcoming cohort
Sustainable AI - Reducing Carbon Footprint and Optimizing Performance
Cohort 2
$399
Dates
Payment Deadline
Course schedule
3.5 hours per week
Tuesdays
12:00pm - 1:30pm PST
June 11,18, 25 2024
12pm-1:30pm PST
Weekly projects
2 hours per week
Homework assignments will include quiz, presentations and other research topics.
Sustainable AI: How to Get started
How can you optimize your AI application to minimize its energy consumption 💡 and cost 💰 while maintaining its performance?
In this recorded presentation, I go over the environmental impact of AI and some of the key principles to get you started with optimization in this nascent and rapidly evolving field.
You will also get a sneak preview of my 3 week course.
Get this free resource
Learning is better with cohorts
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
Frequently Asked Questions
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I work full-time, what is the expected time commitment?
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Join an upcoming cohort
Sustainable AI - Reducing Carbon Footprint and Optimizing Performance
Cohort 2
$399
Dates
Payment Deadline