Climate Change AI Summer School 2026

We are excited to host the fourth Climate Change AI Virtual Summer School in 2026! This program provides participants with the opportunity to learn about different applications of artificial intelligence (AI) for climate action from expert researchers and practitioners, and to develop important skills and expertise to make an impact in this space. Through lectures and hands-on tutorials, participants will gain essential grounding in AI, climate, and their intersection; engage with important frameworks for doing responsible, ethical, and impactful work in this space; gain exposure to a diverse range of AI-for-climate applications; and gain hands-on practice in employing AI techniques for climate-relevant problems.

The program is designed for a global audience from across sectors and career stages, including researchers, practitioners, decision-makers, and students across academia, industry, entrepreneurship, civil society, and the public sector. The program content is particularly geared towards participants who have some prior engagement with either AI or climate-relevant areas and want to learn more about their intersection. If you are enthusiastic about ways to responsibly and impactfully leverage AI to tackle major climate problems and are looking to learn more about this space, we encourage you to check out the program.

Dates & Registration Info

The Virtual Summer School will take place from approximately July 19–August 22, 2026 (5 weeks). The exact schedule of sessions will be posted closer to the program start date.

Registration for the virtual program will open in May. Registration fees are $30 (USD) for participants in high-income economies and $10 (USD) for participants outside high-income economies. Fee waivers will also be available, as we are eager to ensure that program fees are not a barrier to participation for any individual.

To receive email reminders when registration opens, please fill out this expression of interest form.

Program Structure

Throughout the live program in July and August, participants will engage in various “content modules” – each consisting of pre-readings, a lecture, and often a hands-on coding tutorial – that aim to equip participants with an overview of a given area and provide hands-on practice with a particular application and/or tool. Content modules come in two forms:

Given the global range of participant time zones, different lectures will be scheduled at different times of day to ensure at least some proportion of live content is accessible in each time zone. Lectures will also be recorded for asynchronous viewing. Tutorials (presented in the form of interactive Python coding notebooks) will be completed by participants in a self-paced manner during the program.

All program participants will be onboarded to the Climate Change AI Community Platform, an online forum where they can engage in discussions with other program participants, participate in Q&A on lectures and tutorials, and engage in discussions on climate change and AI projects and topics with the broader Climate Change AI community.

In addition, self-study materials will be sent before the Summer School to help participants without prior background in AI or coding acquire relevant background necessary for completion of the hands-on coding tutorials.

To receive updates about the program and be the first to know when registration opens, please fill out this expression of interest form.

Organizers

On behalf of Climate Change AI:
Ana Maria Quintero Ossa (University College London)
Alamin Musa Magaga (Nest Africa AI Innovation Lab)
David Quispe (University of Toronto)
Mary Salami (University of California, Santa Barbara)
Priya Donti (MIT)

Frequently Asked Questions

Q: What is meant by AI?
A: Broadly speaking, artificial intelligence (AI) encompasses any computer algorithm that makes predictions, recommendations, or decisions on the basis of a defined set of objectives. Many prominent examples of AI today are from a sub-area called machine learning (ML), which refers to techniques that infer patterns from examples (e.g., data). ML is used to describe a wide variety of techniques that range in their type and complexity, including, e.g., linear regression, decision trees, and deep neural networks; discriminative models vs. generative models; and task-specific models vs. general-purpose models.

Q: What areas of climate change will be covered?
A: Topics covered in the Summer School will span climate change mitigation (reducing or preventing greenhouse gas emissions), adaptation (building resilience and robustness to the effects of a changing climate), and climate science (understanding and predicting climate change).

Q: How do I access the program?
A: When registration for the program opens, you will be prompted to join the Climate Change AI Community Platform upon completion of your registration. All information regarding accessing materials will be shared on the Community Platform.

Q: What is the deadline for registering?
A: Registration for the Virtual Summer School will remain open until the end of the program.

Q: At what times will lectures and tutorials be held?
Given the global range of participant time zones, different lectures will be scheduled at different times of day to ensure at least some proportion of live content is accessible in each time zone. Lectures will also be recorded, and be immediately made available to participants for asynchronous viewing. Coding tutorials are to be completed by participants in a self-paced manner during the program.

Q: When will the schedule for the program be posted?
A: We will aim to post the schedule about a month prior to the start of the program. See the 2024 program page for an indicative example of a past program schedule.

Q: Are there prerequisites for the program? What prior knowledge is expected?
A: The program will begin with introductory lectures on AI and on climate change. The rest of the lectures will be presented to be accessible to individuals from a broad range of backgrounds, without any assumed prerequisites beyond the content of these introductory lectures. Hands-on coding tutorials will be presented in Python, and some prior familiarity with Python programming is assumed; self-study materials will be sent before the Summer School to help participants without prior background in Python programming acquire some introductory experience. Most tutorials assume only minimal prerequisite knowledge about AI, whereas some tutorials assume more substantial prior knowledge of AI. Prerequisites for individual tutorials will be flagged prior to the start of the Summer School.

Q: What sectoral modules will be available?
A: Currently, we anticipate providing sectoral modules on the following topics, though this is subject to change: AI for Accelerated Science; AI for Agriculture and Food Security; AI for Biodiversity & Ecosystems; AI for Buildings & Cities; AI for Carbon Accounting (Monitoring, Reporting, and Verification); AI for Climate Science; AI for Economics and Finance; AI for Forestry; AI for Oceans & Marine Systems; AI for Policy and Social Sciences; AI for Power & Energy Systems; AI for Public Health; AI for Risk Assessment, Disaster Management & Relief; AI for Transportation; AI for Water Resources and Hydrology; AI for Weather; Combining AI and Indigenous Knowledge for Climate Action.

Q: Will Climate Change AI provide certificates of attendance for the program?
A: Yes. To get the certificate, participants must have completed all required foundational modules and at least four sectoral modules.

Q: What is the time commitment associated with the program?
A: We anticipate that completing the requirements associated with the certificate of attendance will take participants ~30 hours over the 5 weeks of the program (including lectures, tutorials, and asynchronous assignments). However, participants may engage in additional modules beyond those required for the certificate; all modules will be made available to all registered participants. In addition, participants may choose to engage at a lower level of commitment if they so wish; with that said, we strongly encourage participants to take advantage of as much of the curriculum as they are able.

Q: What is the age requirement for the program?
A: All participants must be at least 18 years of age.

Q: My question isn’t answered above. What should I do?
A: If you have a question not answered in the FAQs, please email summerschool+virtual@climatechange.ai. Due to the large number of inquiries, we may not be able to reply to all emails.