Introduction to Quantum Machine Learning (2021/2022)

Course code
cod wi: DT000081
Name of lecturer
Alessandra Di Pierro
Alessandra Di Pierro
Number of ECTS credits allocated
Academic sector
Language of instruction
A.A. 21/22 dottorato dal Oct 1, 2021 al Sep 30, 2022.

Lesson timetable

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Learning outcomes

The goal of this course is to show what benefits current and future quantum technologies can provide to machine learning, focusing on algorithms that are challenging for classical computers.
In particular, the students will be given the adequate notions and knowledge to be able to solve machine learning problems by means of quantum algorithms; to identify problems in machine learning that would benefit from using quantum resources; to implement learning algorithms on quantum computers using the available public platforms that allow us to access them.


1 Introduction and Motivation
2 Basics of Quantum Computing
3 Basics of Machine Learning (ML)
4 Quantum Machine Learning: Main Approaches
5 Quantum Kernels
6 Quantum Variational Approaches
7 Quantum Approximate Optimisation Algorithms
8 Quantum Annealing

Assessment methods and criteria

Seminar on a topic in quantum machine learning