The course will explore statistical and artificial intelligence techniques for the analysis of space-engineering data. For each technique, examples from the space sector will be presented. For selected cases, there will be practical sessions where students will perform case studies with representative datasets.
The topics will cover, among others, Treatment of random variables, Regression techniques, Classification, Dimensionality reduction, introduction to neural networks, and reinforcement learning.
Practical examples will cover, among others, orbital dynamics for trajectory prediction and collision avoidance, satellite image analysis, fault diagnosis in space systems, weather prediction with satellite data, and attitude control.