This course will help you understand AI's climate implications and identify practical next steps within your organization. The course begins with demystifying the connection between AI, Large Language Models (LLMs), data centers, and energy and water demand. Then you will learn about AI's environmental footprint, the related environmental and community impacts, you will evaluate real-world applications of AI across climate adaptation, energy transition, and nature conservation, and understand the business and policy landscape shaping corporate decisions.
Coursera. Date unknown. The AI, Climate, and Energy Connection. https://www.coursera.org/learn/the-ai-climate-and-energy-connection (AI & Environment Resource Hub; record atlas-1511f6455a26; collection snapshot 2026-09-15).
Classification and context
Included in the original Course collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
Availability, fees, and enrollment dates may have changed since collection. Source link reachable · checked 2026-09-15. Source identity and required metadata verified. The import date is not the original date added.
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Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Water; Biodiversity and ecosystems; Built environment and infrastructure
In the Environmental Impacts of Data Centers 101 course, you will learn to analyze the environmental impacts of data centers using a life cycle assessment (LCA) perspective that goes beyond what you see in the news. This will include energy, water, land use, carbon emissions, global supply chains, e-waste concerns, ecological impacts, and environmental justice case studies. Whether you work in tech, sustainability, policy, or are just curious about how AI systems operate behind the scenes, this course gives you the clarity and frameworks to understand these impacts from end-to-end.
Nathaniel Burola
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Biodiversity and ecosystems; Built environment and infrastructure
AI and ML optimize optoelectronic systems for sustainability by enhancing energy efficiency, renewable energy harvesting, environmental monitoring, and smart cities while also advancing ocean optics and photonics for marine ecosystem monitoring and climate change mitigation.
Library Progress International
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Water; Built environment and infrastructure
AI’s rapid growth is driving an unprecedented surge in energy and water demand, raising serious environmental justice concerns, especially in marginalized communities, while sparking debate over whether climate benefits can outweigh the harms without stronger accountability and sustainable innovation.
Climate One
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Water; Weather, hazards, and adaptation
The Environmental and Energy Study Institute (EESI) invites you to a briefing discussing the intersection of artificial intelligence (AI) and climate change in federal policy-making. While AI can aid in climate resilience and boost economic competitiveness, it is also on a trajectory to increase energy demand, greenhouse gas emissions, and water usage. This paradox presents an important opportunity for discussion on how to best minimize the negative impacts of AI on the environment and harness its powers for a sustainable future.
