Introduction to Quantum Information (Coursera)

Introduction to Quantum Information (Coursera)

The course provides an introduction to quantum information at a beginning graduate level. It focuses on the fundamental understanding of how information is processed with quantum systems and how the quantum properties apply to computing and communication tasks. The course begins by presenting quantum theory as the framework of information processing. Quantum systems are introduced with single and two qubits. Axioms of quantum theory such as states, dynamics, and measurements are explained as preparation, evolution, and readout of qubits. Quantum computing and quantum communication are explained.

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

Entanglement is identified as a key resource of quantum information processing. Manipulation and quantification of entangled states are provided.
Quantum information processing opens an avenue to new information technologies beyond the current limitations but, more importantly, provides an approach to understanding information processing at the most fundamental level. What is desired is to find how Nature performs information processing with the quantum and classical systems. The ultimate power of Nature in computing and communication may be found and understood. The course provides a modest step to learn quantum information about how physical systems can be manipulated by the laws of quantum mechanics, how powerful they are in practical applications, and how the fundamental results make quantum advantages.

Syllabus

WEEK 1: Quantum Theory to Information Technologies
WEEK 2: Single qubit
WEEK 3: Bipartite quantum systems
WEEK 4: Quantum computing
WEEK 5: Quantum communication
WEEK 6: Entanglement
WEEK 7: Summary

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

Related Courses

Quantum Mechanics for Scientists and Engineers 2 (edX) EdX
StanfordOnline

Quantum Mechanics for Scientists and Engineers 2 (edX)

This course covers key topics in the use of quantum mechanics in many modern applications in science and technology, introduces core advanced concepts such as spin, identical particles, the quantum mechanics of light, the basics of quantum information, and the interpretation of quantum mechanics, and covers the major ways in which quantum mechanics is written and used in modern practice.

Self Paced
Self-Paced
Applied Quantum Computing III: Algorithm and Software (edX) EdX
Purdue University,PurdueX

Applied Quantum Computing III: Algorithm and Software (edX)

Learn domain-specific quantum algorithms and how to run them on present-day quantum hardware. 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.

Mar 25th 2024
5-12 Weeks
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.

Oct 19th 2026
3 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
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
Introduction to Quantum Computing for Everyone (edX) EdX
University of Chicago,UChicagoX

Introduction to Quantum Computing for Everyone (edX)

This first course in quantum computing is for novices and requires learners to have only basic algebra. It covers the future impacts of quantum computing, provides intuitive introductions of quantum physics phenomenon, and progresses from single operations to a complete algorithm. Quantum computing is coming closer to reality, with 80+ bit machines in active use. This course provides an intuitive introduction to the impacts, underlying phenomenon, and programming principles that underlie quantum computing.

Self Paced
Self-Paced
The Introduction to Quantum Computing (Coursera) Coursera
Saint Petersburg State University

The Introduction to Quantum Computing (Coursera)

"Quantum Computing" is among those terms that are widely discussed but often poorly understood. The reasons of this state of affairs may be numerous, but possibly the most significant among them is that it is a relatively new scientific area, and it's clear interpretations are not yet widely spread. The main obstacle here is the word "quantum", which refers to quantum mechanics - one of the most counter-intuitive ways to describe our world.

Aug 8th 2022
5-12 Weeks
Dynamic Programming, Greedy Algorithms (Coursera) Coursera
University of Colorado Boulder

Dynamic Programming, Greedy Algorithms (Coursera)

This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data structures.

Oct 12th 2026
4 Weeks
Nanotechnology and Nanosensors, Part 1 (Coursera) Coursera
Technion - Israel Institute of Technology

Nanotechnology and Nanosensors, Part 1 (Coursera)

Nanotechnology and nanosensors are broad, interdisciplinary areas that encompass (bio)chemistry, physics, biology, materials science, electrical engineering and more. The present course will provide a survey on some of the fundamental principles behind nanotechnology and nanomaterials and their vital role in novel sensing properties and applications. The course will discuss interesting interdisciplinary scientific and engineering knowledge at the nanoscale to understand fundamental physical differences at the nanosensors.

Oct 5th 2026
5-12 Weeks