Corso di laurea magistrale in Chimica

DATA SCIENCE FOR CHEMISTS FROM MODELLING TO MACHINE LEARNING

DATA SCIENCE FOR CHEMISTS FROM MODELLING TO MACHINE LEARNING

Anno accademico 2024/2025

Sommario insegnamento

• Obiettivi formativi
• Risultati dell'apprendimento attesi
• Programma
• Modalità di insegnamento
• Modalità di verifica dell'apprendimento
• Testi consigliati e bibliografia
• Note
• Strumenti didattici
• Scheda del corso

Obiettivi formativi

The course outlines concepts of computer modelling and machine learning for the physical chemist. The student will learn about supervised and unsupervised learning algorithms for data analysis, as well as methods of classical and quantum-mechanical modelling in physical chemistry. The algorithms will be applied with hands-on sessions, employing the python programming language.

Risultati dell'apprendimento attesi

- Familiarity with the jargon and array of algorithms for machine learning and modelling in physical chemistry
- Basic knowledge of the python programming language and scientific computing
- Sensibility to the pros and cons of different modelling and machine learning strategies

Programma

Introduction (where do data come from?; what is Machine Learning?)

Modelling (What is so difficult?; The Schrodinger equation and the electron correlation problem)

Machine Learning (Models of Supervised and Unsupervised data classification and regression; Parametrizing the model: analytical solutions, the least-squares problem, gradient-based numerical optimizations)

Modalità di insegnamento

The course consists in frontal lessons, systematically complemented by hands-on sessions, where all concepts are applied by use of available Python-based tools after being formally presented and discussed. [total of 48 hours]
All classes will take place face-to-face (Lecture Hall TBD)
All didactic material will be published on the campusnet platform and available in a specific Google Drive folder (see "Note").
The course has a strong hands-on character so all students will need to bring a laptop to class.
All students are kindly asked to register for the course using the relevant item in the menu bar at the bottom of this page, in order to receive relevant communications about the course and what needs to be installed on your computer.

Modalità di verifica dell'apprendimento

Written and oral exams (both mandatory).

The exam consists in two parts:

1) Written part

The written examination will be delivered in the form of a quiz consisting of 18 multiple-choice questions to be answered in 1 hour on students laptop. The questions will cover all topics addressed during the lectures.

2) Oral part

The oral examination will consist of a presentation of 6 slides, in English, prepared by the student, choosing a topic from the following list:

The final mark will be calculated as an average of the marks for the written and oral parts.

Lecture notes and scripts by the teachers.

SHARED GOOGLE DRIVE FOLDER WITH LECTURES PDFS (prof. Corno):

link to be published

Shared folder with Lecture PDFs (Desmarais):

link to be published

Note

Students with specific learning disabilities (SLD) or disabilities are requested to review the university's support (https://www.unito.it/servizi/lo-studio/studenti-e-studentesse-con-disabilita) and accommodation (https://www.unito.it/accoglienza-studenti-con-disabilita-e-dsa) procedures, particularly the procedures required for support during exams (https://www.unito.it/servizi/lo-studio/studenti-e-studentesse-con-disturbi-specifici-di-apprendimento-dsa/supporto).

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