EdX

Quantum Computer Systems Design II: Principles of Quantum Architecture (edX)

Quantum Computer Systems Design II: Principles of Quantum Architecture (edX)

This course explores the basic design principles of today's quantum computer systems. In this course, students will learn to work with the IBM Qiskit software tools to write simple quantum programs and execute them on cloud-accessible quantum hardware.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

This quantum computing course explores the basic design principles of today's quantum computer systems. In this course, students will learn to work with the IBM Qiskit software tools to write simple programs in Python and execute them on cloud-accessible quantum hardware. Topics covered in this course include:

  • Introduction to systems research in quantum computing
  • Fundamental rules in quantum computing, Bloch Sphere, Feynman Path Sum
  • Sequential and parallel execution of quantum gates, EPR pair, no-cloning theorem, quantum teleportation
  • Medium-size algorithms for NISQ (near-term intermediate scale quantum) computers
  • Quantum processor microarchitecture: classical and quantum control
  • Quantum program compilation and qubit memory management

Keywords: quantum computing, computer science, linear algebra, compiler, circuit optimization, python, qiskit, quantum algorithms, quantum technology, superposition, entanglement, qubit technology, superconducting qubit, transmon qubit, ion-trap qubit, photonic qubit, real quantum computers

What you'll learn

  1. Understand design principles of full-stack quantum software design
  2. Understand several examples of quantum system inefficiencies
  3. Learn how to apply several classical software techniques to improve quantum hardware reliability and performance
  4. Learn examples of how classical software techniques can be applied to make quantum systems more reliable and efficient
  5. Learn how to think about the overall design of a quantum system and how the software and hardware work together
  6. Develop unique skills to be more competitive in seeking a position in quantum software development

This course is part of the Quantum Computer Systems Design Professional Certificate.

Syllabus

Module 1 (Intro to Quantum Computation and Programming)

  • Lec 00 - Quantum Computing Systems – Current State-of-Play
  • Lec 01 - From bits to qubits
  • Lec 02 - QASM and logic gate decomposition
  • Lec 03 - Basic quantum programs

Module 2 (Principles of Quantum Architecture)

  • Lec 04 - Program compilation and synthesis
  • Lec 05 - Program compilation and synthesis II
  • Lec 06 - Gate scheduling and parallelism
  • Lec 07 - Qubit mapping and memory management

Module 3 (Working with Noisy Systems)

  • Lec 08 - NISQ algorithms
  • Lec 19 - Noisy quantum systems
  • Lec 10 - Noise-aware quantum compiling

Prerequisites:
Introduction to Quantum Computing for Everyone (Part 1 and Part 2)
Module I (Intro to Quantum Computation and Programming)

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Applied Quantum Computing II: Hardware (edX) EdX
Purdue University,PurdueX

Applied Quantum Computing II: Hardware (edX)

Learn how present-day material platforms are built to perform quantum information processing tasks. This course is part 2 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 2 is to provide the essential understanding of how the fundamental quantum phenomena discussed in part 1 can be realized in various material platforms and the underlying challenges faced by each platform.

Feb 12th 2024
5-12 Weeks
Quantum Machine Learning (with IBM Quantum Research) (openHPI) OpenHPI
Hasso-Plattner-Institut

Quantum Machine Learning (with IBM Quantum Research) (openHPI)

Whether we stream our favorite series, develop new drugs or have us being chauffeured by a self-driving car -- machine learning is an essential part of our modern life, and of our future. But the growing amount of data and our increasing demands pose difficulties for today's classical computers. Can quantum computing overcome these challenges? What potentials does the emerging field of quantum machine learning have? In this course, we will not only learn about quantum machine learning and its prospects, but we will also solve concrete tasks with both classical and quantum models.

Jan 11th 2023
2 Weeks
Quantum Optics 1 : Single Photons (Coursera) Coursera
École Polytechnique

Quantum Optics 1 : Single Photons (Coursera)

This course gives you access to basic tools and concepts to understand research articles and books on modern quantum optics. You will learn about quantization of light, formalism to describe quantum states of light without any classical analogue, and observables allowing one to demonstrate typical quantum properties of these states. These tools will be applied to the emblematic case of a one-photon wave packet, which behaves both as a particle and a wave.

Sep 21st 2026
5-12 Weeks
Understanding Quantum Computers (FutureLearn) FutureLearn
Keio University

Understanding Quantum Computers (FutureLearn)

Explore the key concepts of quantum computing and find out how it’s changing computer science with this introductory course. In this course, we will discuss the motivation for building quantum computers, cover the important principles in quantum computing, and take a look at some of the important quantum computing algorithms.

Self Paced
3 Weeks
Physical Basics of Quantum Computing (Coursera) Coursera
Saint Petersburg State University

Physical Basics of Quantum Computing (Coursera)

Quantum information and quantum computations is a new, rapidly developing branch of physics that has arisen from quantum mechanics, mathematical physics and classical information theory. Significant interest in this area is explained by the great prospects that will open upon the implementation of its ideas, capturing almost all areas of human activity related to the transfer, storage and processing of information.

Jul 25th 2022
5-12 Weeks
Introduction to Quantum Computing for Everyone 2 (edX) EdX
University of Chicago,UChicagoX

Introduction to Quantum Computing for Everyone 2 (edX)

This course focuses on the mathematics, programming, operations, and algorithms of quantum computing. A follow-on to Intro to QC for Everyone 1, this course delves deeper into the mathematical basis for quantum computing and the programming that makes it a reality. Students will be taught all of the mathematical concepts they need to know, build up confidence and experience with individual and small groups of operations, then learn a sequence of important algorithms.

Self Paced
Self-Paced
Density Functional Theory (Coursera) Coursera
École Polytechnique

Density Functional Theory (Coursera)

The aim of this course is to give a thorough introduction to Density Functional Theory (DFT). DFT is today the most widely used method to study interacting electrons, and its applicability ranges from atoms to solid systems, from nuclei to quantum fluids. In this course, we introduce the most important concepts underlying DFT, its foundation, and basic ideas. We will in particular stress the features and reasons that lead DFT to become the dominant method for simulating quantum mechanical systems.

Aug 24th 2026
3 Weeks
Quantum Computing for Your Classroom 10-12 (edX) EdX
The University of British Columbia,UBCx

Quantum Computing for Your Classroom 10-12 (edX)

Quantum Computing for Your Classroom is an activity focused, self-paced course designed to help educators integrate an exciting new field into their physics and computer science classrooms. This course seeks to help bridge that gap by providing activities and knowledge of quantum computing that high school educators can integrate into their existing classrooms, providing the children of today with the future proof skills needed for tomorrow.

Self Paced
Self-Paced