EdX

Introduction to Quantum Computing for Everyone 2 (edX)

Offered by 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.

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

What you'll learn

  • The linear algebra concepts that are used to create useful quantum algorithms
  • Small sequences of operations that perform important QC operations
  • How to program with Qiskit, used for the IBM cloud quantum computers
  • Learn several quantum algorithms

This course is part of the Quantum Computing for Everyone Professional Certificate.

Syllabus

  • Linear Algebra
  • Toffoli Gate
  • Phase-Flip
  • EPR Pairs
  • Amplitude Amplification
  • Bernstein-Vazarani algorithm
  • Simon’s algorithm
  • Decoherence
  • Error Correction
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Emergent Phenomena in Science and Everyday Life (Coursera) Coursera
University of California, Irvine

Emergent Phenomena in Science and Everyday Life (Coursera)

Sci: Physical & Earth Sciences Sci: Physics

Before the advent of quantum mechanics in the early 20th century, most scientists believed that it should be possible to predict the behavior of any object in the universe simply by understanding the behavior of its constituent parts. For instance, if one could write down the equations of motion for every atom in a system, it should be possible to solve those equations (with the aid of a sufficiently large computing device) and make accurate predictions about that system’s future.

Sep 14th 2026
5-12 Weeks
Biology Systems Biology Consciousness
Details
Machine Learning (Coursera) Coursera
Stanford University

Machine Learning (Coursera)

Statistics & Data Analysis Data Science

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Sep 7th 2026
5-12 Weeks
Artificial Intelligence MATLAB Algorithms
Details
Applications of Linear Algebra Part 1 (edX) EdX
Davidson College,DavidsonX

Applications of Linear Algebra Part 1 (edX)

CS: Software Engineering Sci: Mathematics

Learn to use linear algebra in computer graphics by making images disappear in an animation or creating a mosaic or fractal and in data mining to measure similarities between movies, songs, or friends. From simulating complex phenomenon on supercomputers to storing the coordinates needed in modern 3D printing, data is a huge and growing part of our world.

No sessions available
4 Weeks
Math Linear Algebra Computer Graphics
Details
Architecture, Algorithms, and Protocols of a Quantum Computer and Quantum Internet (edX) EdX
Delft University of Technology,DelftX

Architecture, Algorithms, and Protocols of a Quantum Computer and Quantum Internet (edX)

Sci: Physics Computer Science

Learn the basics of quantum algorithms, quantum error-correction, micro-architectures, compilers, and programming languages for quantum processors, and protocols for the quantum internet. In this course we will demonstrate how a large-scale quantum processor could be built using these qubits. Among the topics that we will discuss are micro-architectures, compilers, and programming languages.

Self Paced
Self-Paced
Compilers Protocols Processors
Details
Differential Equations: Linear Algebra and NxN Systems of Differential Equations (edX) EdX
MIT,MITx

Differential Equations: Linear Algebra and NxN Systems of Differential Equations (edX)

Sci: Mathematics

Learn how to use linear algebra and MATLAB to solve large systems of differential equations. Differential equations are the mathematical language we use to describe the world around us. Most phenomena can be modeled not by single differential equations, but by systems of interacting differential equations. These systems may consist of many equations. In this course, we will learn how to use linear algebra to solve systems of more than 2 differential equations. We will also learn to use MATLAB to assist us.

Jan 11th 2023
5-12 Weeks
MATLAB Linear Algebra Differential Equations
Details
Applications of Linear Algebra Part 2 (edX) EdX
Davidson College,DavidsonX

Applications of Linear Algebra Part 2 (edX)

CS: Software Engineering Sci: Mathematics

Explore applications of linear algebra in the field of data mining by learning fundamentals of search engines, clustering movies into genres and of computer graphics by posterizing an image. Our world is in a data deluge with ever increasing sizes of datasets. Linear algebra is a tool to manage and analyze such data. This course is part 2 of a 2-part course, with this part extending smoothly from the first. Note, however, that part 1, is not a prerequisite for part 2.

No sessions available
4 Weeks
Linear Algebra Computer Graphics Data Mining
Details
Introduction to Quantum Computing (edX) EdX
The University of British Columbia,UBCx

Introduction to Quantum Computing (edX)

Engineering Sci: Mathematics

This course is an approachable introduction to the weird and complex world of quantum computing. Interested learners can develop an understanding of the physics and computer science behind this new technology. This course introduces students to the fundamentals of quantum computing and helps them understand and create quantum solutions from a computational and from a mathematical perspective.

Self Paced
Self-Paced
Computer Technology Quantum Computing
Details
Machine Learning for Semiconductor Quantum Devices (edX) EdX
Delft University of Technology,DelftX

Machine Learning for Semiconductor Quantum Devices (edX)

Sci: Physics Data Science

Learn how to deploy artificial intelligence to control and calibrate semiconductor quantum computing chips. Quantum computing is a fast-growing technology and semiconductor chips are one of the most promising platforms for quantum devices. The current bottleneck for scaling is the ability to control semiconductor computing chips quickly and efficiently.

Self Paced
Self-Paced
Machine Learning Quantum Neural Networks
Details
Advanced Linear Algebra: Foundations to Frontiers (edX) EdX
University of Texas at Austin,UTAustinX

Advanced Linear Algebra: Foundations to Frontiers (edX)

Sci: Mathematics Computer Science

Learn advanced linear algebra for computing. Linear algebra is one of the fundamental tools for computational and data scientists. In Advanced Linear Algebra: Foundations to Frontiers (ALAFF), you will build your knowledge, understanding, and skills in linear algebra, practical algorithms for matrix computations, and the analysis of the effects of floating-point arithmetic as performed by computers.

Self Paced
Self-Paced
Math Computing Algorithms
Details