Join the 2025 edition of the master course
Title: Artificial Intelligence and Machine Learning Methods for Environmental Applications (AIENV)
Date: 03 ‐ 14 November 2025 (2 weeks, 30 hours/week)
Teachers: SALAS Aaron, SALUCCI Marco
Website: https://www.eledia.org/eledia-unitn/course/aienv
Leverage machine learning to optimize soil health, predict yields, and drive more informed decisions.
The Master Course is taught in 🇬🇧️ ENGLISH and is offered
- On-site
- On-line (synchronous and asynchronous)
Video recordings, hand-outs, etc. of the lectures will be available off-line!
What you will learn:
- Core principles of Machine Learning and AI
- The “Three-Steps Learning-by-Examples” (LBE) framework
- Interpolation, dimensionality reduction & sampling techniques
- Classification and regression methodologies
- AI-based forecasting and data-driven modeling
Applications in Environmental Engineering:
- Monitoring soil moisture and nutrient levels
- Crop yield forecasting under varying environmental and climatic conditions
With case studies and lab simulations, you’ll build the skills to apply AI and ML to real-world environmental challenges.
Teaching Activities:
- Theoretical Lessons
- e-Xam Self Assessment (each teaching class or periodically)
- MATLAB Hands-On
- e-Xam Final Assessment
Fees:
UniTN Students: FREE
EXTERNAL Students:
- 216€ : First course
- 180€ : Every course from the second one
The fees include the course teaching, slides/material, and video recordings.
Discover our didactic offer at:
https://www.eledia.org/eledia-unitn/course_degree/degree-master/
Questions? Reach us at: didattica@eledia.org
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