This course builds upon the foundational principles of quantum computation to explore advanced topics and applications. It introduces key methods in quantum optimization, cryptography, and machine learning, while also covering practical aspects of quantum programming such as circuit transpilation, noise modeling, and error mitigation. The course emphasizes hands-on programming and implementation of quantum algorithms to demonstrate how these methods leverage quantum phenomena to solve complex computational, optimization, and security challenges, providing both practical experience and algorithmic insight for real-world applications.

This course aims to equip students with advanced knowledge and practical skills in quantum programming, focusing on optimization, cryptography, and quantum machine learning algorithms. Students will learn to design, implement, and evaluate real-world quantum algorithms while addressing practical challenges such as noise, transpilation, and error mitigation.

Lectures will be delivered using Jupyter notebooks that combine theoretical content with quantum programming tasks. These materials are based on QWorld’s educational notebooks.

Students should have their own laptops and perform necessary installations.