Data analyses, computing

Description

- General concepts of digital data (typing, format, precision, sampling, etc.) and metadata
- Retrieving/reading/writing data files
- Data representation (1D, 2D, 3D, nD)
- Standard statistical analysis tools
- Notions of noise and its statistical properties
- Regression / interpolation / smoothing of data
- Cross-data analysis: correlation of data sets and classification methods
- Notions of frequency analysis (Fourier spectrum and spectrogram)
Various computer tools are introduced throughout the module. The basic language used is Python but complete mastery of this language is not an objective of the module.