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

โ“How can we make smarter decisions for complex environmental challenges?

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 โ€œThree-Steps Learning-by-Examplesโ€ framework for approaching AI and Machine Learning problems
  • Interpolation techniques for estimating environmental variables from available data
  • Dimensionality reduction methodologies for simplifying complex environmental datasets
  • Space exploration and sampling strategies for efficiently collecting and processing information
  • Classification and regression methods for prediction, detection, and decision-making
  • Applications to water quality detection and the prediction and optimization of water resource availability
  • Environmental applications involving lake surface temperature, remote sensing, soil science, and agriculture
  • Hands-on numerical exercises using software-based implementations

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

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