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This course will provide a basic introduction to quantum computing and quantum algorithms. It will cover celebrated quantum algorithms that are of interest in the long term in addition to having a particular focus on near-term quantum algorithms for specific applications (e.g., material simulation and approximate optimization) that can be readily studied on currently available hardware. Lastly, we will discuss critical techniques for managing noise in quantum systems (e.g., quantum error correction). Course attendees will also receive hands-on experience in near-term quantum algorithm implementation on the IBM Quantum Experience (IBM QE), a publicly available quantum computing platform. Recommended Background : Calculus, Python (Basic), Linear Algebra, Basic Quantum Mechanics