Objective 1: Knowledge and understanding. The course aims to provide students with robust theoretical knowledge on large chemical data analysis using machine-learning, computational chemistry and chemoinformatics methods.
Objective 2: Applied knowledge and understanding. The student will be able to apply the acquired theoretical knowledge to the resolution of practical problems of industrial interest, using an adequate lexicon in English. In particular, the student will develop knowledge and ability to apply big data and machine learning approaches in large companies and SMEs, which generate and analyze large chemical data. They will know the basic principles necessary to face large chemical data analysis.
Objective 3: Independent judgment. The student will acquire the ability to compare and evaluate the sustainability of different processes and the problems related to big data analysis in chemistry. The acquired knowledge will allow the student to orient himself in the problems related to the discovery of molecular materials, synthesis prediction of new compounds, structure-property relationships, computer-aided drug design, new solutions to chemical toxicity evaluations.
Objective 4: communication skills. The student will be able to discuss the problems related to analyze large chemical data, with an advanced technical language.
Objective 5: Ability to learn. At the end of the lessons the student will be able to recover the main on-line resources, of a scientific and institutional nature, useful to stay updated on the evolution of the scientific debate and to face various research problems.