The course aims to introduce students to chemometrics tools that can be useful in studying and interpreting complex systems.
The course will start with the description of the multivariate structure of data for the characterization of a chemical/environmental system. The main methods covered in the course will be: Pattern Recognition, with particular reference to Cluster Analysis, Principal Component Analysis (PCA) and the development of predictive multivariate models (PCR and PLS) by means of QSAR (Quantitative Structure-Activity Relationship) strategy and Experimental Design.
Particular emphasis will be given to the development and the validation of multivariate calibration models, and to the study and the understanding of practical problems concerning environmental systems. Different cases of study will be discussed in-depth.
These knowledge are extremely important inside the Degree’s program, because the students will acquire the necessary skills for interpreting environmental data and understanding the mechanisms and the dynamics of environmental processes in chemical, ecological, geological, hydrogeological and biological field. That is the starting point for implementing strategies of remediation, monitoring and evaluation of environmental biodiversity, as well as defense of natural resources.
The course has a predominant experimental approach and is focused on the understanding and the practical use of the main methods of Pattern Recognition.