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Quantum Systems: Working with Noisy Systems
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Quantum Systems: Working with Noisy Systems

This course is part of Quantum Computer Systems Design.

Course Cost

₹ 17,231

Advanced

Skill Level

4 Weeks

Self-paced lessons

This comprehensive course explores the fundamental design principles of modern quantum computer systems, focusing on practical skills for quantum software development. Students will learn to use IBM Qiskit software tools to write Python-based quantum programs and execute them on actual cloud-accessible quantum hardware. The curriculum covers critical topics including systems research in quantum computing, Bloch Sphere representation, sequential and parallel execution of quantum gates, EPR pairs, the no-cloning theorem, and quantum teleportation. The course places special emphasis on medium-size algorithms for NISQ (near-term intermediate scale quantum) computers, quantum processor microarchitecture with classical and quantum control elements, quantum program compilation techniques, and effective qubit memory management strategies. By completing this course, students will develop unique skills in quantum software development, understand software-hardware integration principles for quantum systems, and learn specialized techniques to improve quantum hardware reliability and performance.

Fred Chong

Fred Chong

Jonathan Baker

Jonathan Baker

English

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English

Fred Chong

Fred Chong

Jonathan Baker

Jonathan Baker

What you'll learn

  • Understand the design principles of full-stack quantum software systems

  • Master techniques to improve quantum hardware reliability and performance

  • Apply classical software techniques to make quantum systems more reliable

  • Design quantum systems with integrated software and hardware components

  • Write quantum programs using IBM Qiskit and execute them on cloud hardware

  • Work with NISQ (near-term intermediate scale quantum) algorithms

  • Implement quantum program compilation and qubit memory management

  • Develop specialized skills for a competitive edge in quantum software development

Skills you'll gain

Quantum Computing
Qiskit
Python Programming
Quantum Gates
Linear Algebra
Computer Science
Microarchitecture
Quantum Technology
Algorithms
Systems Theories

This course includes:

PreRecorded video

Graded assignments, exams

Access on Desktop, Mobile, Tablet

Limited Access access

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There are 3 modules in this course

This course provides a comprehensive exploration of quantum computing systems with a focus on working with noisy quantum hardware. Students will learn how to use IBM's Qiskit framework to program quantum computers and execute their code on cloud-based quantum processors. The course covers fundamental quantum computing concepts like the Bloch Sphere, Feynman Path Sum, EPR pairs, and quantum teleportation. Students will explore quantum processor microarchitecture, including both classical and quantum control elements. Special attention is given to medium-size algorithms suitable for NISQ (near-term intermediate scale quantum) computers. The course also covers critical software aspects such as quantum program compilation, circuit optimization techniques, and qubit memory management strategies. Throughout the course, students will develop practical skills to address real-world challenges in quantum computing, including techniques to improve reliability and performance of noisy quantum systems.

Intro to Quantum Computation and Programming

Module 1

Principles of Quantum Architecture

Module 2

Working with Noisy Systems

Module 3

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Quantum Computer Systems Design

Payment options

Financial Aid

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Fred Chong

4

Courses

Fred Chong is the Seymour Goodman Professor of Computer Architecture at the University of Chicago and Chief Scientist at Super.tech. He leads the EPiQC Project, an NSF Expedition in Computing focused on enabling practical-scale quantum computing. Chong has a Ph.D. from MIT and extensive experience in computer architecture, quantum computing, and sustainable computing. He has received numerous awards, including the Intel Outstanding Researcher Award, NSF CAREER award, and recognition as an ACM and IEEE Fellow. His research spans emerging technologies for computing, multicore architectures, computer security, and quantum systems design.
Jonathan Baker

4

Courses

Jonathan Baker is a Ph.D. candidate at the University of Chicago, advised by Prof. Fred Chong. He holds dual B.S. degrees in Chemistry, Mathematics, and Computer Science from the University of Notre Dame. His research focuses on quantum compilation, logic synthesis, and architectural design for fault-tolerant and near-term quantum computers. Recognized with two IEEE Micro Top Picks awards, Baker has contributed significantly to advancing quantum systems and has been supported by the McCormick Fellowship.
Yongshan Ding

4

Courses

Yongshan Ding is an Assistant Professor of Computer Science at Yale University, leading the Quantum Systems Lab and affiliated with the Yale Quantum Institute. He holds a Ph.D. from the University of Chicago and a B.Sc. from Carnegie Mellon University. Ding's research focuses on quantum computer architecture, algorithms, error correction, and memory management, aiming to advance next-generation quantum systems. His work has earned prestigious awards, including the NSF CAREER Award and Best Paper recognitions from IBM Q and QCE'20. He is also the lead author of Quantum Computer Systems, a textbook on quantum computing architecture.
Casey Duckering

4

Courses

Casey Duckering is a Ph.D. student at the University of Chicago, advised by Prof. Fred Chong. He holds B.S. degrees in Electrical Engineering and Computer Science (EECS) and Mechanical Engineering from UC Berkeley, as well as an M.S. in Computer Science from UChicago. His research focuses on quantum algorithms, error correction, and hardware implementations for NISQ quantum computers, with additional work on multi-valued qubits (qudits). His contributions have been recognized with a Best Paper Runner-Up at MICRO'20 and two IEEE Micro Top Picks awards.
Quantum Systems: Working with Noisy Systems

Advanced

Skill Level

4 Weeks

Self-paced lessons

Course Cost

₹ 17,231

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.