PhD Course: Quantum Computing and its Application to Machine Learning

The course will introduce the basic elements of quantum information and quantum computation.
Starting from the physical fundaments (principle of superposition, unitary evolution, principle of measurement), the course will introduce the students first to basic quantum gates, and then to quantum algorithms and quantum circuits. The course will discuss why, how, and in which contexts, a  significant “quantum speedup” can be obtained by using quantum instead of classical computation.
The course will expose the two most renowned quantum algorithms (Grover and Shor) and then will focus on the most recent applications of quantum computing to machine learning, with an eye to the applications fields for which both public and private companies are investing a huge amount of money: e-health, finance, etc.

Seminar room - 5th floor, cube 42C

08/04/2024 (10:00-13:00)
09/04/2024  (10:00-13:00)
11/04/2024  (10:00-12:00)

8 ore 2 CFU

Team Code: enb4d2b