About this courseSkip About this course
This course is part III of the series of Quantum computing courses, which covers aspects from fundamentals to present-day hardware platforms to quantum software and programming.
The goal of part III is to discuss some of the key domain-specific algorithms that are developed by exploiting the fundamental quantum phenomena (e.g. entanglement)and computing models discussed in part I. We will begin by discussing classic examples of quantum Fourier transform and search algorithms, along with its application for factorization (the famous Shor’s algorithm). Next, we will focus on the more recently developed algorithms focusing on applications to optimization, quantum simulation, quantum chemistry, machine learning, and data science.
A particularly exciting recent development has been the emergence of near-intermediate scale quantum (NISQ) computers. We will also discuss how these machines are driving new algorithmic development. A key aspect of the course is to provide hands-on training for running (few qubit instances of) the quantum algorithms on present-day quantum hardware. For this purpose, we will take advantage of the availability of cloud-based access to quantum computers and quantum software.
The material will appeal to engineering students, natural sciences students, and professionals whose interests are in using as well as developing quantum technologies.
Quantum Computing I: Fundamentals is an essential prerequisite to Quantum Computing II: Hardware and Quantum Computing III: Algorithm and Software. Learners should plan to complete Fundamentals before enrolling in the Hardware or the Algorithm and Software courses.
What you'll learnSkip What you'll learn
Quantum Fourier transform and search algorithms
Hybrid quantum-classical algorithms
Quantum annealing, simulation, and optimization algorithms
Quantum machine-learning algorithms
Cloud-based quantum programming
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