**MSQC601: The Mathematics and Methods of Quantum Computing**

This course will provide the student with the necessary physical intuition and background information on quantum physics so that to be able to understand and appreciate a variety of applications in quantum computing such as quantum currency, encryption, random number generation.

**MSQC602: Physics of Quantum Devices**

The Physics of the very small course aims to build a bridge between natural principles such as light and atoms and a variety of modern applications. This course will provide the student with the necessary physical intuition and background information on quantum physics so that to be able to understand and appreciate a variety of applications in quantum computing such as quantum currency, encryption, random number generation.

**MSQC603: Principles of Machine Learning**

A broad introduction to machine learning and statistical pattern recognition. Topics include: Supervised learning: Bayes decision theory, discriminant functions, maximum likelihood estimation, nearest neighbor rule, linear discriminant analysis, support vector machines, neural networks, deep learning networks. Unsupervised learning: clustering, dimensionality reduction, PCA, auto-encoders. The course will also discuss recent applications of machine learning, such as computer vision, data mining, autonomous navigation, and speech recognition.

**MSCQ604: Quantum Computing Architectures and Algorithms**

Quantum computing aims to utilize quantum properties of matter to solve certain kinds of problems that classical computing systems would take too long to solve. This course bridges the gap between the concepts and theory of quantum mechanics with their application to the physical realization of what we currently call quantum computers. To that end, we review the different technological implementations of the building block of quantum computing, the qubit. We then learn to interact with present day quantum computing offerings of major quantum computer manufacturers via a variety of software tools. We do an overview of current quantum computing simulators and compare their performance with actual quantum computer hardware. Finally, we demonstrate the use of these tools to the solution of concrete problems.

Prerequisite: MSQC601 and MSQC602