Building Quantum Solutions: Communication, Algorithms and AI
Overview
Course Date:
14 Dec 2026 to 15 Dec 2026
Registration Period:
14 Oct 2026 to 23 Nov 2026
Duration/Frequency:
16 Hours
Mode of Training:
Face-to-Face (Classroom Teaching)
What You Will Learn
This introductory course presents the basic concepts on quantum computing including some of the necessary mathematical foundations (matrix algebra, simple probability, complex numbers). It also discusses some key uses of quantum computing such as quantum entanglement for quantum communication and Grover search algorithm. These examples provide clear demonstrations of quantum supremacy over classical computing, i.e. the use of quantum computers clearly outperform classical computers in such problems.
Learn about applications of quantum computing in Artificial intelligence (AI)/machine learning, as well as making use of vibe coding to familiarise with some simple quantum circuits which concretely implement the quantum algorithms for quantum computing.
If you have a strong interest in physics and mathematics and are keen to learn about the ideas behind quantum computing and how it is clearly better than classical computing in certain areas, this course is for you. This course is also ideal for those who are interested in AI/machine learning, and the implications on cybersecurity.
By the end of the course, you will be able to:
Implement some quantum protocols for communications which are superior to classical ones.
Implement some quantum algorithms such as the Grover search algorithm to find the desired result which is superior to classical search algorithms.
Build quantum circuits through vibe coding with AI tools.
Topics to be covered
Introduction on quantum computing.
Introduction on the mathematical preliminaries (matrix algebra, probability theory, complex numbers, Dirac notation).
Quantum communication (entanglement, teleportation, superdense coding, CHSH game).