University Courses - Quantum Computing and Quantum AI

Quantum Artificial Intelligence

• Cod: 146584
• Institution: Saarland Informatics Campus, Saarland University, Germany
• Duration: October 2023 - February 2024
• Information: 3 Credit Points, 26 hours, A.Y. 2023-24, Course evaluation
• Synopsis: This course adopts a computer science perspective on Quantum Artificial Intelligence and consists of two parts. The first part briefly introduces the fundamentals of quantum computation, including gate-based and adiabatic quantum computational models. The second part explores the feasibility and potential advantages of using quantum computational methods to address specific AI problems, emphasizing machine learning and optimization.

Please refer to the official webpage for further information.

Quantum Computing for NP-hard Problems and AI

• Department: Dept. of Computer Science and Engineering, University of Bologna, Italy
• Duration: October 3-11, 2023
• Information: 3 Credit Points, 15 hours, A.Y. 2023-24, Syllabus
• Synopsis: This course is designed for Ph.D. students with no prior knowledge of quantum computing. It provides a computer science perspective on the quantum algorithms for solving traditional NP-hard problems with a particular focus on AI applications. The course is divided into three parts. Part I introduces the fundamental concepts of gate-based and adiabatic quantum computational models. Part II describes hybrid quantum-classical algorithms, with a focus on machine learning and combinatorial optimization. In part III, the course explores the advantages of utilizing quantum computational methods to address computationally hard AI problems.

Please refer to the official webpage for further information.

Quantum Artificial Intelligence

• Cod: 139530
• Institution: Saarland Informatics Campus, Saarland University, Germany
• Duration: October 2022 - February 2023
• Information: 3 Credit Points, 26 hours, A.Y. 2022-23, Course evaluation
• Synopsis: This course adopts a computer science perspective on Quantum Artificial Intelligence and consists of two parts. The first part briefly introduces the fundamentals of quantum computation, including gate-based and adiabatic quantum computational models. The second part explores the feasibility and potential advantages of using quantum computational methods to address specific AI problems, emphasizing machine learning and optimization.

Please refer to the official webpage for further information.

Quantum Machine Learning Seminar

• Cod: 136315
• Institution: Saarland Informatics Campus, Saarland University, Germany
• Duration: April 2022 - July 2022
• Information: 7 Credit Points, 16 hours, A.Y. 2023-24
• Synopsis: This course on Quantum Machine Learning aims to show what benefits quantum technologies can provide to the area of machine learning. While machine learning algorithms are used to compute massive amounts of data, quantum machine learning employs qubits and quantum operations to improve computational speed and data storage. A closer look at selected methods in the context of quantum machine learning will be taken with a particular focus on hybrid quantum-classical algorithms for supervised learning and reinforcement learning.

Please refer to the official webpage for further information.

Quantum Computing

• Provider: Deep Learning Italia, Italy (e-learning platform)
• Duration: June 2021

Course Synopsis: This course offers a comprehensive introduction to the fundamentals of quantum computation, structured into three main segments. The initial part explores basic mathematical concepts and highlights the distinctions between classical and quantum computing. The second segment delves into the core principles of quantum computing, commencing with the foundational postulates of quantum mechanics and progressing to the formal and technical definition of algorithms. The third section is dedicated to describing and implementing quantum algorithms. It introduces two influential quantum algorithms utilizing IBM’s qiskit framework.

Platform Information: e-learning platform for academic and industrial training programs with approximately 3000 users and 70+ instructors from academia and industry. Recognized by Fondazione Bruno Kessler and University of Macerata.

Please refer to the official webpage for further information.