Graduate Certificate Quantum Computing Courses
QCI400 Overview of Quantum Computing (3 credits)
This course offers a high-level overview of quantum computing, covering its history, advantages, challenges, future directions, fundamental principles, and applications. Students will gain hands-on experience solving basic problems using quantum simulators and real quantum computers accessible via the cloud.
QCI401 Foundational Linear Algebra and Probability (3 credits)
This course covers essential mathematical concepts in linear algebra and probability theory, providing the foundational tools necessary for understanding quantum computing.
QCI402 Mathematical Foundations of Quantum Computing (3 credits)
This course provides a rigorous introduction to the mathematical foundations of quantum mechanics and quantum computing, which form the basis for understanding and designing quantum algorithms and quantum information protocols. Students proficient in linear algebra can test out of this course.
QCI501 Qubits, Quantum Gates and Quantum Circuits (3 credits)
This course introduces the foundational principles of quantum computing, focusing on qubits, quantum gates, and quantum circuits. Students will explore key quantum mechanics concepts essential for understanding quantum computation, including superposition, entanglement, and measurement, providing a solid foundation for further study in the field.
QCI502 Quantum Entanglement and Quantum Information (3 credits)
This course provides an introduction to the principles of quantum computing and the algorithms that take advantage of the unique properties of quantum mechanics to solve computational problems faster than classical algorithms. The course will cover the basic quantum algorithms, including Deutsch-Jozsa, Simon’s algorithm, and Grover’s algorithm, as well as advanced algorithms such as Shor’s and HHL. Throughout the course, students will use software tools such as Qiskit, Cirq, and Braket to design, simulate, and analyze quantum algorithms.
QCI521 Foundational Quantum Algorithms (3 credits)
This course introduces the principles of quantum computing and algorithms that leverage the unique properties of quantum mechanics to outperform classical methods in solving complex computational problems. Students will study foundational quantum algorithms, including Deutsch-Jozsa, Simon’s, Grover’s algorithms, as well as advanced algorithms like Shor’s and HHL. Through hands-on practice with tools such as Qiskit, Cirq, or Braket, students will design, simulate, and analyze quantum algorithms, gaining both theoretical knowledge and practical experience.