Preliminary data treatment, clustering and classification methods: K-NN, Cluster Analysis.
Principal Component Analysis (PCA): theory, use, applications; the SIMCA method.
Experimental Design: Factorial Design, D-efficiency and D-optimal design. Practical use of chemometrics software. A part of the course will be dedicated to the study of real cases from the relevant literature.