Within the Master’s Degree Program in Data Science and Engineering, the Twin Track program provides the opportunity to obtain a second Master’s Degree in Mathematics Engineering.
The study path is structured as follows:
- 1st year: Data Science and Engineering
- 2nd year: Data Science and Engineering + Thesis
- 3rd year: Core courses of the Mathematics Engineering programme + Thesis
Below is the detailed list of courses:
First year (Data Science and Engineering)
| Course | CFU |
|---|
| Data management and visualization | 8 |
| Data Science Lab: process and methods | 8 |
Statistical Methods in Data Science
or
Computational linear algebra for large scale problems
| 8 |
| Data ethics and data protection | 6 |
| Distributed architectures for big data processing | 8 |
| Fundamentals of Artificial Intelligence, Machine and Deep Learning | 10 |
| Mathematical and statistical methods for Artificial Intelligence | 8 |
| Numerical Optimization for large scale problems | 8 |
Second year (Data Science and Engineering)
| Course | CFU |
|---|
| Innovation management | 6 |
| Network dynamics and learning | 8 |
| Geometric Learning, Time-Variant Data analysis, and…. | 8 |
Deep natural language processing
or
Machine learning for IoT
| 8 |
| Free choice credits | 6 |
| Thesis | 22 |
Third year (Mathematics Engineering)
| Course | CFU |
|---|
Modelli matematici per la biomedicina
or
Equazioni della fisica matematica
| 8 |
Two courses of choice among:
Metodi numerici (8 CFU)
Ricerca operativa (8 CFU)
Metodi numerici per le PDE (8 CFU)
Computational linear algebra for large scale problems (8 CFU)
| 16 |
Options MAT:
Crittografia (6 CFU)
Modelli matematici per la biomedicina (8 CFU)
Analisi tempo-frequenza e multiscala (6 CFU)
Blockchain e criptoeconomia (6 CFU)
Matematica dei sistemi e dei controlli (6 CFU)
Metodi numerici per le PDE (8 CFU)
| 12 |
| Thesis | 16 |
