Short Course on Artificial Intelligence for Environmental Data
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Two-day short course exploring how artificial intelligence (AI) can be used to process and interpret environmental data. This course is aimed at early-career researchers and professionals with an interest in AI tools and methods for climate-related analysis and earth observation.
Participants will gain a foundational understanding of key AI techniques—including Large Language Models (LLMs)—and get hands-on experience with practical tools through guided exercises.
Application
- Application Deadline: 19 June 2026
- Course Dates: 08–09 October 2026 (New dates!)
The course is free to attend and held solely in person.
Climes-affiliated researchers will be given priority in the selection process. - Please note: Once you are attendance is confirmed, if you do not attend and fail to unregister via email at least 3 weeks prior to the course start, a no-show fee of 1000 SEK will be invoiced to your home institution
- Who can apply:
Doctoral students, postdocs, and early-career professionals with basic programming skills.
No prior AI experience is required. - Credits:
Ce can provide a certificate stating the full-time equivalent work that went into the course, and then it is up to individual study directors or supervisors at the home institutions to determine if and how the course is eligible for credits - Financial support
We do not offer any financial support for participants to attend this course. All participants are expected to cover their own costs.
Description
- The Short Course on Artificial Intelligence for Environmental Data will immerse researchers in the latest AI techniques for extracting knowledge from e.g. texts, satellite imagery and in-situ measurements.
- Building on the complementary work of Olof Mogren—deep-learning methods for biodiversity monitoring, remote-sensing and soundscape analysis—and Murathan Kurfalı—multilingual large-language-model (LLM) pipelines for analysing textual data—the course blends theory with hands-on coding labs, giving participants practical skills they can transfer directly to their own projects.
Prel.Schedule
Day 1
10:00–12:00
- Introduction to AI and Machine Learning — Olof Mogren
- Introduction and Brief History of Natural Language Processing (NLP) — Murathan Kurfalı
12:00–13:00
- Lunch
13:00–14:00
- AI for Climate Adaptation and Mitigation — Olof Mogren
14:00–17:00
- Introduction to Exercise (potentially “Greenwashing Classification”) — Murathan Kurfalı
Day 2
10:00–12:00
- AI for Environmental Monitoring — Olof Mogren
- AI for Prediction and Earth System Modelling — Olof Mogren
12:00–13:00
- Lunch
13:00–14:00
- Using NLP and Large Language Models: General Concepts and Climate Applications — Murathan Kurfalı
14:00–17:00
- Exercises: The planned exercises, subject to final confirmation, will provide participants with practical experience across diverse AI applications for environmental data. These might include greenwashing classification using natural language processing, land use classification via computer vision, anomaly detection from satellite imagery, and information extraction from climate-related data such as weather reports.
Course Leaders
- Olof Mogren, Research Director, RISE; co-founder, Climate AI Nordics.
View bio - Murathan Kurfalı, Researcher, RISE/Stockholm University; developer of multilingual discourse models and co-creator of the Wikimpacts climate-impact database.
View bio
Contact
- For more information about the application process, schedule, or any other inquiries, please contact:
sakip_murat.yalcin@geo.uu.se (Climes Project Coordinator)