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.

Based on last year’s feedback, we will be spending less time introducing the Python environment and tools, and trust that you do that on your own using the scrpits we made last year – see the Prerequisites section below.

Program

Monday June 1st 2026 – 9:00 am: Introduction and Machine learning

Presentation of the course and speakers

Introduction to AI: historical background

Linear and general regression : from a ML perspective

Practical concepts and practice

Tuesday June 2nd 2026 – Machine learning 2

Dataset selection

Supervised learning : classification, regression, random forest

Dimensionality reduction

Unsupervised learning : clustering

Wednesday June 3rd 2026 – Practice ML, introduction to Deep Learning

Hands on: practice

Deep learning: a history

Deep learning: main concepts

Thursday June 4th 2026 – Deep learning: SDMs and LLMs

DL applied to Species Distribution Models

Practice using PlantNet data

DL applied to literature review: LLMs

Practice

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 this tutorial we made just for you <3 before attending the training course.

You don’t need to remember all of this by heart and you can go back to this at any time during the training course (and any other time too).

If you think you need a Python refresher, you can also have a look at these fun interactive tutorials:

https://www.learnpython.org/

Under the “Learn the basics”, we recommend 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 any of these tutorials, 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 and Maud Calmet 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, Justeau-Allaire D, Frelat R, Marcos D, 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.

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