Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

A.A. 2024/2025 A.A. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021 A.A. 2019/2020 A.A. 2018/2019 A.A. 2017/2018 A.A. 2016/2017 A.A. 2015/2016 A.A. 2014/2015 A.A. 2013/2014 A.A. 2012/2013 A.A. 2011/2012 A.A. 2010/2011 A.A. 2009/2010

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea magistrale in Banca e finanza - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
9
B
IUS/04
9
B
SECS-P/05
9
B
SECS-P/11
9
B
SECS-P/11
9
C
SECS-P/11
6
B
SECS-P/01
9
B
SECS-S/06

2° Year   activated in the A.Y. 2022/2023

ModulesCreditsTAFSSD
6
B
SECS-P/11
6
B
SECS-P/09
9
C
SECS-P/11
9
B
SECS-S/03
6
F
-
15
E
-
activated in the A.Y. 2022/2023
ModulesCreditsTAFSSD
6
B
SECS-P/11
6
B
SECS-P/09
9
C
SECS-P/11
9
B
SECS-S/03
6
F
-
15
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
9
D
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Machine learning and quantum computing with some applications in mathematical finance  (2021/2022)

Teaching code

4S011163

Teacher

Alessandro Gnoatto

Coordinator

Alessandro Gnoatto

Credits

2

Language

English en

Scientific Disciplinary Sector (SSD)

NN - -

Period

secondo semestre (lauree magistrali) dal Feb 21, 2022 al May 13, 2022.

Lessons timetable MoodleMoodle Seminars 0

Learning outcomes

Introduzione al machine learning e al quantum computing.

Program

Parte 1 sul machine learning: modelli di regressione lineare e non lineare, modelli di classificazione, deep learning, interpretabilità dei modelli. Parte 2 sul quantum computing: fondamenti matematici, algoritmi di base, confronto tra quantum computing e classical computing, framework per il quantum computing. Parte finale: applicazioni finanziarie ed esperimenti numerici.

Periodo di svolgimento: Giovedì 21 aprile (machine learning), Venerdì 22 aprile (quantum computing). Esercitazioni Sabato 23 aprile. Le lezioni saranno erogate via Zoom.

Destinatari: studenti della Laurea Magistrale in Banca e Finanza.

Bibliography

Vai alla bibliografia
Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Examination Methods

Modalità di accertamento del profitto: esame scritto con esercizi di programmazione.

Data proposta per l’appello verbalizzante: da concordare con l’università partner LMU di Monaco di Baviera.

Impegno orario richiesto: 16 ore di didattica frontale, 8 ore di esercitazioni, 26 ore di studio individuale.

CFU proposti: 2 CFU

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE