Measuring AI's Environmental Impact: Technical Bootcamp
2 Weeks
·Cohort-based Course
Get practical experience to measure AI products energy and carbon footprint
Measuring AI's Environmental Impact: Technical Bootcamp
2 Weeks
·Cohort-based Course
Get practical experience to measure AI products energy and carbon footprint
Worked, advised and coached
Course overview
Estimate your AI energy consumption and carbon footprint with confidence
In this 2-week technical bootcamp, you'll master the practical skills needed to measure and track AI systems' environmental impact.
You'll learn how to:
- understand the key parameters involved in measuring AI model energy consumption
- Define KPIs for AI carbon footprint
- Set up measurement infrastructure for AI workloads
- Use industry leading tools to track energy consumption
- Create comprehensive carbon footprint reports
The bootcamp includes a weekly 2hr live session. You'll also get access to office hours where we can address your specific measurement challenges and implementation questions.
Each week includes hands-on labs where you'll work with real measurement tools and datasets.
The curriculum will allow you to select and configure a measurement framework that you can immediately implement in your organization. You'll learn to use and customize tools like CodeCarbon, ML CO2 Impact Calculator, AI energy score and cloud reporting solutions.
This bootcamp focuses specifically on measurement and monitoring - while we touch on optimization strategies, our core emphasis is on end to end estimates of AI's environmental impact.
This course is technical in nature and most suitable for those with some engineering or data science background, though no specific AI expertise or development experience is required.
GenAI technology is disrupting the services and technology job market. Now is a good time to develop your learning and stay on top of this rapidly evolving trend.
If you are interested in other aspects of sustainable AI such as sufficiency and efficiency, check out my other course on this topic: Sustainable AI - Reducing Carbon Footprint and Optimizing Performance
For group rates and corporate training inquiries, contact pascal@itclimateed.com
Who is this course for
01
Sustainability Data Analysts will gain the expertise to quantify the digital carbon footprint of their organization.
02
Product Managers can design AI products based on their lower energy footprint.
03
MLOps and ITOps engineers will learn how to implement energy and carbon tracking in their AI product pipeline
What you’ll get out of this course
Understand the environmental impact of AI and its influencing parameters
You'll learn the full spectrum of environmental impact of AI beyond its energy carbon footprint. We'll also discuss what makes some AI technologies like Generative AI much more energy intensive than others.
Learn to estimate AI's energy consumption during training and inference.
We'll cover in details public cloud dashboard, open source tools and industry benchmark. You will get practical examples and challenges for each tool we cover, and the best tool based on your goals and your role.
Select a measurement framework to track, report, and analyze your AI systems' carbon footprint using real-world industry metrics
You'll have a chance to get hands on practice with what you learned through lab exercises. Select and customize a solution most relevant to your context.
This course includes
3 interactive live sessions
Lifetime access to course materials
23 in-depth lessons
Direct access to instructor
2 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.
Measuring AI's Environmental Impact: Technical Bootcamp
Course syllabus
Week 1
Jun
20
AI Energy/Carbon Footprint: Impact Assessment and Measurement tool selection
Why is this such an important topic
The environmental impact of AI
Selection criteria
Selecting the right tool for the job
Week 2
Jun
27
Implementation: Configuration, Production Systems, Automated tracking and Reporting
Production roll out
Reporting: setting up dashboards for tracking and benchmarking
Developing your own measurement tool
Capstone project
Jun
23
Office Hours
Week 3
Meet your instructor
Pascal Joly
Pascal combines deep expertise in data center operations with a focus on sustainability. As a Terra.do fellow and certified AI/ML professional, he bridges the gap between technical efficiency and environmental impact. His years of experience optimizing data centers through automation, as an engineer and product leader, gives him unique insights into measuring and reducing AI's carbon footprint. Pascal is the author of a browser extension, AIWattch, to estimate LLM carbon emissions during conversations in real time.
Join an upcoming cohort
Measuring AI's Environmental Impact: Technical Bootcamp
Cohort 1
$399
Dates
Application Deadline
Course schedule
4-6 hours per week
Tuesdays & Thursdays
8:00am - 9:30am PST or 4pm-5:30pm PST
Choose from one of 2 schedule options based on your availability to attend live sessions. Tuesday are interactive presentation and labs, Thursdays are optional office hours.
Weekly projects
2 hours per week
Schedule items can also be used to convey commitments outside of specific time slots (like weekly projects or daily office hours).
Building AIWattch: Measuring ChatGPT's Carbon Footprint in Real-Time
Discover the hidden environmental cost of your AI conversations in this practical white paper. Learn how a simple browser extension can track carbon emissions from ChatGPT interactions, and explore the development journey from AI-assisted prototyping to open-source solution.
Inside you'll find:
- The surprising truth about AI inference energy consumption
- Step-by-step explanation of real-time carbon tracking
- Practical development insights using AI as a co-developer
- Actionable strategies based on your professional role
Download this free white paper
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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Join an upcoming cohort
Measuring AI's Environmental Impact: Technical Bootcamp
Cohort 1
$399
Dates
Application Deadline