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Machine Learning for Earth and Planetary Sciences III
Last Updated: 2026-02-05 16:38:32
Abstract
In this class you tackle an individual research problem by applying the machine learning methods you learned in Machine Learning for Earth and Planetary Science I and/or Machine Learning for Earth and Planetary Science II.
Objective
For a geoscience problem of your choice, you identify the most suitable machine learning technique(s), and apply them to the problem. You optimise and fine tune and evaluate the model, in order to find the best possible performance for the problem at hand. From this experience, you learn the intricacies and the power of a particular data science method, and to solve a data driven problem in detail.
Content
After a kick-off meeting you work independently with your supervisor, and present your project with a poster or powerpoint presentation at the end of the class. You can ask questions and get advice at weekly office hours.
General Information
- Language
- English
- Levels
- BSC , MSC , GS
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| independent project | Machine Learning for Earth and Planetary Sciences III | No time listed | 60 h semesterly |
Offered In
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Electives (The electives listed are recommended. Additional courses can be chosen from the complete offerings of the ETH Zurich and University of Zurich.)
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Electives (Courses can be chosen from the complete offerings of the ETH Zurich and University of Zurich (according to prior agreement with the MSc Committee).)
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