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The FRB in action
Since 2025
AI for ecologists: a toolkit
Machine learning, Supervised/Unsupervised learning, Deep learning, Symbolic AI
The objective of this five-day course is 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.
This course is delivered in English and takes place in June at CESAB’s premises in Montpellier. The fee is 250 € for the week, including lunch. Travel, accommodation, and evening meal costs are the responsibility of the participants.
You must have a strong programming background. Familiarity with Python is not mandatory
List of speakers:
- Léo BLONDEL (alien.club)
- Benjamin BOUREL (INRIA, University of Montpellier, LIRMM, CNRS)
- Margot CHALLAND (Institut Agro Montpellier)
- Dimitri JUSTEAU-ALLAIRE (IRD, AMAP)
- Titouan LORIEUL (Institut Agro Montpellier)
- Maximillien SERVAJEAN (LIRMM)
- Paul TRESSON (IRD, AMAP)
Sample program
INTRODUCTION
- Presentation of the course and speakers
- Introduction to AI: historical background
- Introduction to Python environment and tools
- Data science in Python
MACHINE LEARNING 1
- Linear and general regression : from a ML perspective
- Random forest and K-means
- Practical concepts and practice
MACHINE LEARNING 2
- Dataset selection
- Supervised learning
- Unsupervised learning
- Dimensionality reduction
DEEP LEARNING
- DL concepts
- Practices with PlantNet
SYMBOLIC AI
- Introduction
- Practice: Designing protected areas in New Caledonia
- Practice: Crop rotation planning
- Feedback time and conclusion