AI for ecologists: a toolkit
FRB-CESAB training course
Welcome
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Pre-registrations close on Jan 16th, 2026.
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This five-day training course, organized by the FRB-CESAB aims to initiate ecologists to AI concepts and tools. The course will be a mix of lectures and hands-on practice based on different data types commonly encountered in ecology. The main objective of the course is to give to the participants the autonomy that will allow them to assess which algorithms are most adapted to their own research questions, where to find them and how to adjust them to the desired question.
For the 2026 edition, Sonia Mai Tieo will join the team to expand the deep learning section a bit. The program might change a bit, more in terms of structure than in the contents listed below. Updates will come in spring 2026.
Program
Monday June 1st 2026 – 9:00 am: Introduction
Presentation of the course and speakers
Introduction to AI: historical background
Introduction to Python environment and tools
Data science in Python
Tuesday June 2nd 2026 – Machine learning 1
Linear and general regression : from a ML perspective
Random forest and K-means
Practical concepts and practice
Wednesday June 3rd 2026 – Machine learning 2
Dataset selection
Supervised learning
Unsupervised learning
Dimensionality reduction
Thursday June 4th 2026 – Deep learning
DL concepts
Practices with PlantNet
Friday June5th 2026 – Symbolic AI
Introduction
Practice: Designing protected areas in New Caledonia
Practice: Crop rotation planning
Feedback time and conclusion
Prerequisites
You must have a strong programming background, at least in R.
Familiarity with Python is preferred, but not mandatory. In fact, to make sure that we all start on similar bases, we require that you follow these tutorials before attending the training course.
Under the “Learn the basics”, please go through all the following pages:
• Hello, World!
• Variables and Types
• Lists
• Basic Operators
• String Formatting
• Basic String Operations
• Conditions
• Loops
• Functions
• Classes and Objects
• Dictionaries
• Modules and Packages
• Input and Output
Each section allows you to interact with a built-in Python console where you can copy/paste and edit the commands. The sections end with a small exercise, which we recommend you do. You may navigate from one section to the other by clicking on the “next tutorial” button (you don’t have to take the test – but are welcome to if you enjoy it)
We will not control whether you followed the tutorial, but trust that you will to collectively ensure the group has a common base to start from
Material
All the material used in this training course (slides, data, exercises) is available at: https://github.com/ai-ecol/
Acknowledgements
Thanks to Sakina Ayata for comments and advice in the set-up of this training course, to Nicolas Casajus for constant conceptual and technical support. Thanks to Maija Miikkola for all the logistical and administrative help, and to Violette Silve for the visual support on the FRB website.
Citation
Blondel L, Bourel B, Challand M, Coux C, Justea-Allaire D, Frelat R, Servajean M, Tieo S.M., Tresson P. (2026) AI for ecologists: a toolkit for beginners. An FRB-CESAB training course. URL: https://ai-ecol.github.io/
Contributions
If you see mistakes or want to suggest changes, please create an issue on the source repository.
Reuse
Text and figures are licensed under Creative Commons Attribution CC By 4.0, unless otherwise noted.
See also
Discover the other training courses provided by the FRB-CESAB and its partners: https://frbcesab.github.io/training-courses/