The curriculum in Quantum Computing trains graduates who are experts in quantum computing and its applications.
| Courses | ECTS | |
|---|---|---|
| I year (60 ECTS) | ||
| I semester | ||
| Probability and Statistics for Scientific Computing | 6 | |
| Introduction to Quantum Mechanics and Computing | 6 | |
| High Performance Computing (+) | 6 | |
| Cloud Computing (+) | 6 | |
| One course from Core Group A (+) | 18 | |
| One course from Core Group B | 6 | |
| #colspan# | ||
| II semester | ||
| Deep Learning | 6 | |
| One course from Core Group C | 6 | |
| Introduction to Quantum Information Theory | 6 | |
| One course from Core Group D | 6 | |
| #colspan# | ||
| II year (60 ECTS) | ||
| Two courses from Complementary Group | 12 | |
| Elective courses | 12 | |
| Internship | 12 | |
| Thesis | 24 | |
(+): Integrated courses (modules combined in a single course)
| Core Group A Courses | ECTS |
|---|---|
| Advanced programming (*) | 6 |
| Software Development Methods | 6 |
| Core Group B Courses | ECTS |
|---|---|
| Introduction to Machine Learning (*) | 6 |
| Information Theory | 6 |
| Core Group C Courses | ECTS |
|---|---|
| Probabilistic Machine Learning | 6 |
| Stochastic Modelling and Simulation | 6 |
| Core Group D Courses | ECTS |
|---|---|
| Algorithms for Scientific Computing (*) | 6 |
| Advanced Algorithms for Scientific Computing | 6 |
(*) These courses contain introductory material and they cannot be inserted in the study plan if a course with a corresponding content has been attended during the bachelor or in other educational programs. Please ask the program coordinator if you are unsure.
You can add complementary courses from the following groups:
| Complementary Group Courses | ECTS |
|---|---|
| Information Theory | 6 |
| Quantum Algorithms | 6 |
| Quantum Machine Learning | 6 |
You have to add in the study plan elective courses from the following group:
| Elective Courses | ECTS | |
|---|---|---|
| All the courses in the previous tables | ||
| Quantum Informatics and Software | 6 | |
| Advanced Deep Learning and Kernel Methods | 6 | |
| Data Management | 6 | |
| Advanced Deep Learning and Kernel Methods | 6 | |
| Artificial Intelligence for Cyber-Physical Systems | 6 | |
| Bayesian Statistics | 6 | |
| Explainable and Reliable Artificial Intelligence | 6 | |
| Software Development Methods | 6 | |
| Other courses (****) | ||
(****) Other courses can belong to any field of studies and any program of the university, provided they are coherent with the training path of the student.