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Environmental Systems Data Science
Last Updated: 2026-02-05 15:34:28
Abstract
Students are introduced to a typical data science workflow using various examples from environmental systems. They learn common methods and key aspects for each step through practical application. The course enables students to plan their own data science project in their specialization and to acquire more domain-specific methods independently or in further courses.
Objective
The students are able to ● frame a data science problem and build a hypothesis ● describe the steps of a typical data science project workflow ● conduct selected steps of a workflow on specifically prepared datasets, with a focus on choosing, fitting and evaluating appropriate algorithms and models ● critically think about the limits and implications of a method ● visualise data and results throughout the workflow ● access online resources to keep up with the latest data science methodology and deepen their understanding
Content
● The data science workflow ● Access and handle (large) datasets ● Prepare and clean data ● Analysis: data exploratory steps ● Analysis: machine learning and computational methods ● Evaluate results and analyse uncertainty ● Visualisation and communication
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
- Max Places
- 70
- Signup Start
- 07.09.2020
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Environmental Systems Data Science
The lecturers will communicate the exact lesson times of ONLINE courses.
|
|
2 h weekly |
Offered In
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Electives Courses (Elective courses can be chosen from the entire course programme of the ETH Zurich as well as from the course programme of the University of Zurich.)
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