Register Now for the 2026 Edition of the AIENV Master Course!

๐ŸŒ How can we make smarter decisions for complex environmental challenges?
๐Ÿ‘‰ Through Artificial Intelligence and Machine Learning, powerful tools to analyze environmental data, predict risks, optimize resources, and support sustainable solutions.

๐ŸŽ“ Register now for the 2026 edition!

Course: Artificial Intelligence and Machine Learning Methods for Environmental Applications (AIENV)
Dates: 02 โ€“ 13 November 2026 (2 weeks, 30 hours/week)
Teacher: POLO Alessandro
ECTS: 6
Website: https://www.eledia.org/eledia-unitn/course/2026-2027.LM.AIENV.UniTN.TRENTO.IT/

๐Ÿš€ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ ๐˜๐—ฎ๐˜‚๐—ด๐—ต๐˜ ๐—ถ๐—ป ๐—˜๐—ป๐—ด๐—น๐—ถ๐˜€๐—ต ๐—ฎ๐—ป๐—ฑ ๐—ผ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ฑ ๐—ผ๐—ป-๐˜€๐—ถ๐˜๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐—ผ๐—ป-๐—น๐—ถ๐—ป๐—ฒ (๐˜€๐˜†๐—ป๐—ฐ๐—ต๐—ฟ๐—ผ๐—ป๐—ผ๐˜‚๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—ฎ๐˜€๐˜†๐—ป๐—ฐ๐—ต๐—ฟ๐—ผ๐—ป๐—ผ๐˜‚๐˜€) ๐˜„๐—ถ๐˜๐—ต ๐˜ƒ๐—ถ๐—ฑ๐—ฒ๐—ผ ๐—ฟ๐—ฒ๐—ฐ๐—ผ๐—ฟ๐—ฑ๐—ถ๐—ป๐—ด๐˜€, ๐—ต๐—ฎ๐—ป๐—ฑ-๐—ผ๐˜‚๐˜๐˜€, ๐—ฒ๐˜๐—ฐ. ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—น๐—ฒ๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ๐˜€ ๐—ฎ๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—น๐—ฒ ๐—ผ๐—ณ๐—ณ-๐—น๐—ถ๐—ป๐—ฒ.

In this course, you’ll explore:

  • The main concepts, methodologies, and taxonomy of Artificial Intelligence and Machine Learning
  • Interpolation techniques and dimensionality reduction methods for complex environmental datasets
  • Space exploration, sampling, classification, and regression methodologies
  • AI and ML applications for water quality detection and the prediction and optimization of water resource availability
  • Environmental applications including lake surface temperature prediction, remote sensing, soil science, and agriculture
  • Whether you’re interested in environmental monitoring, data-driven prediction, resource optimization, or sustainable engineering, this course provides theoretical foundations and practical tools 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:

  • 216โ‚ฌ : First course
  • 180โ‚ฌ : Every course from the second one

The fees include the course teaching, slides/material, and video recordings.

๐Ÿ“Œ Register here.

Discover our didactic offer at:
https://www.eledia.org/eledia-unitn/course_degree/degree-master/

Questions? Reach us at: didattica@eledia.org

Read the news on: