Brief course description: Chemometrics is a common name for methods dealing with multivariate data, usually acquired from different measurement techniques in analytical chemistry. Chemometrics is also used for classification and for building regression models for multivariate data. Hyperspectral NIR cameras provide interesting applications. The learning outcomes of the course will be an understanding of the most common methods used in chemometrics. The MATLAB software combined with PLS_Toolbox will be used in computer exercises and for completing home assignments. Specific software will be used in the fourth block concerning image analysis.
Teacher: Professor Paul Geladi, SLU in Umeå, Sweden.
Who can participate: PhD students or equivalent (post-docs, industry researchers)
Registration: see contact
Block 1:
Statistics, imaging, linear algebra, Matlab/Octave, PLS Toolbox, sampling
Block 2:
Classification, pre-processing of data, qualitative analysis, spectroscopy application –examples
Block 3:
quantitative analysis, - regression techniques, regression diagnostics
Block 4:
Hyperspectral, imaging, examples