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651-7002-00L 8 Credits MSC D-ITET , D-MAVT , D-PHYS , D-ERDW
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Space Data

Lecturers & Examiners: Dr. Simon Christian Stähler, Dr. Katrin Bentel, Davide Staub
VVZ CR n/a

Last Updated: 2026-06-01 11:33:51

Abstract

Space missions generate vast amounts of data — not only scientific data from payloads, but also technical data collected during testing, launch, and operations. This course provides students with practical skills in analyzing such data efficiently, using methods that are broadly applicable across space science and engineering problems.

Objective

Core topics include spectral and time–frequency analysis, clustering, principal component analysis, and modern neural network approaches. Through hands-on exercises with real datasets from academia and industry, students will practice in-class analysis, complete targeted homework assignments, and produce structured reports.

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
The participants will hand in three reports during the semester. The final grade is calculated from all three graded reports each equally weighted. All reports must be submitted to pass the course.

Registration & Places

Priority: Registration for the course unit is only possible for the primary target group

Course Components

Type Title Time & Place Hours
lecture with exercise Space Data
  • Fri 10:15-13:00 (NO E 39)
  • Fri 10:15-13:00 (NO F 39)
3 h weekly

Offered In