EAEE E4000
Machine learning for environmental engineering and science
Aimed at understanding and testing state-of?the-art methods in machine learning applied to environmental sciences and engineering problems. Potential applications include but are not limited to remote sensing, and environmental and geophysical fluid dynamics. Includes testing "vanilla" ML algorithms, feedforward neural networks, random forests, shallow vs deep networks, and the details of machine learning techniques
Prerequisites & course information
Prerequisites: Computer language Python or Julia, some linear algebra and machine learning.
Sources
- Course catalogue ↗2026-2027
Catalogue variants
- Machine learning for environmental engineering and science · 3.00 points · University catalogue