The last few years have seen many new ways to get hands-on with quantum computing, including publicly accessible prototype hardware and software frameworks. Such tools provide new education opportunities, not just for quantum computing specifically, but also more broadly for quantum information science and even quantum physics as a whole. In this paper we present a case study of one education resource which aims to take advantage of the opportunities: the open-source online textbook ‘Learn Quantum Computation using Qiskit’. This blends traditional text with executable code and interactive elements. We give an overview of the form taken by the textbook in 2020, summary of the topics covered and an explanation of the approach taken.
The last few years have seen many new ways to get hands-on with quantum computing, including publicly accessible prototype hardware and software frameworks. Such tools provide new education opportunities, not just for quantum computing specifically, but also more broadly for quantum information science and even quantum physics as a whole. In this paper we present a case study of one education resource which aims to take advantage of the opportunities: the open-source online textbook ‘Learn Quantum Computation using Qiskit’. This blends traditional text with executable code and interactive elements. We give an overview of the form taken by the textbook in 2020, summary of the topics covered and an explanation of the approach taken.
In the last year, quantum computing has rapidly transitioned from a purely theoretical field into applied engineering, where multiple algorithms can approach combinatorial optimization problems, machine learning, and cryptography in novel ways, often achieving speedup compared to classical solutions. In this context, there is an increasing need for educational tools that connect mathematical principles from quantum information theory with practical experimentation. Yet, most existing educational resources remain either highly theoretical or provide fragmented code examples, with limited analysis and applications to real-world use cases. As a result, students’ experiences appear restricted, with non-interactive tools for learning. This work presents a comprehensive framework for teaching quantum computing through interactive resources, developed via MATLAB Live Scripts. By combining theory, executable code, and visualization tools within a single environment, this framework enhances learners’ ability to see and reason about quantum algorithms step by step. Following the principles of Project-Based Learning in STEM education, we present a diverse collection of quantum resources, including algorithms for optimization, communication, and error correction. Each project operates as a self-contained learning unit, offering modularity, white-box implementations, and tools for visualization and analysis. Beyond its educational impact, this framework also employs and extends the MATLAB Support Package for Quantum Computing, offering an open-source, reproducible environment suitable for courses and independent study.
We present the results of two semesters of a new undergraduate course on Quantum Computing for Fundamental Sciences and Engineering students. The course was taught employing a blended learning approach, with a combination of synchronous classes, asynchronous video lessons and projects using IBM’s Qiskit framework. As the students did not need any prerequisites in order to enroll, we treated the whole course as applied linear algebra, and it turns out that quantum computing can become the gateway to quantum physics instead of the other way around.
Quantum computing is aninterdisciplinary field that lies at the intersection of mathematics, quantum physics, and computer science, and finds applications in areas including optimization, machine learning, and simulation of chemical, physical, and biological systems. It has the potential to help solve problems that so far have no satisfying method solving them, and to provide significant speedup to solutions when compared with their best classical approaches. In turn, quantum computing may allow us to solve problems for inputs that so far are deemed practically intractable. With the computational power of quantum computers and the proliferation of quantum development kits, quantum computing is anticipated to become mainstream, and the demand for a skilled workforce in quantum computing is expected to increase significantly. Therefore, quantum computing education is ramping up. This article describes our experiences in designing and delivering quantum computing workshops for youth (Grades 9–12). We introduce students to the world of quantum computing in innovative ways, such as newly designed unplugged activities for teaching basic quantum computing concepts. We also take a programmatic approach and introduce students to the IBM Quantum Experience using Qiskit and Jupyter notebooks. Our contributions are as follows. First, we present creative ways to teach quantum computing to youth with little or no experience in science, technology, engineering, and mathematics areas; second, we discuss diversity and highlight various pathways into quantum computing from quantum software to quantum hardware; and third, we discuss the design and delivery of online and in-person motivational, introductory, and advanced workshops for youth.
In this paper, we present the Quantum Information Software Developer Kit - Qiskit, for teaching quantum computing to undergraduate students, with basic knowledge of quantum mechanics postulates. We focus on presenting the construction of the programs on any common laptop or desktop computer and their execution on real quantum processors through the remote access to the quantum hardware available on the IBM Quantum Experience platform. The codes are made available throughout the text so that readers, even with little experience in scientific computing, can reproduce them and adopt the methods discussed in this paper to address their own quantum computing projects. The results presented are in agreement with theoretical predictions and show the effectiveness of the Qiskit package as a robust classroom working tool for the introduction of applied concepts of quantum computing and quantum information theory.
As the field of quantum computing rapidly advances, there is a growing demand for skilled professionals adept in quantum computing and programming. Recognizing this need, in this paper, we share our experiences teaching an introductory-level quantum computing course to students at Cleveland State University (CSU). The course integrates dedicated hands-on programming labs, allowing students to verify their experimental results with corresponding examples from the textbook. These labs cover a diverse range of topics, including fundamental elements such as quantum gates and circuits, quantum key distribution protocols, and quantum algorithms. As educators, our goal is to share teaching insights and resources with fellow instructors in the field. This article elucidates the rationale behind the design of each experiment, providing a deeper understanding of quantum computing.
Investments in quantum technologies, which are based on the effects of quantum mechanics, have escalated in recent years, with big players such as IBM, Google, and Microsoft engaging in the race for quantum supremacy. Some potential benefits of this cutting-edge technology include developing new drugs and materials through accurate molecule simulation, establishing more secure and reliable communication channels, and finding faster solutions for complex optimization problems. As quantum technologies evolve, however, the demand for new software, interfaces, and end-to-end systems to properly program and explore the advantages of quantum mechanics becomes paramount. This requires engineers, especially software engineers, and computer scientists, to have multidisciplinary knowledge and skills. Unfortunately, introductory quantum computing and technologies courses are mostly available in physics, and most engineering and computer science courses do not have modules on quantum physics, leading to a talent gap in the current job market. Therefore, this paper proposes a short teaching plan for introducing quantum computing to students with a more technology-based background, such as computer science and engineering students. This plan uses active learning methodologies, such as Challege-Based Teaching, to better engage these students and contextualize the many applications of this new technology. The initial teaching plan consists of a 3-hour seminar introducing the main quantum mechanics concepts and the technology applications, a 3-hour introduction to the math fundamentals and quantum logic gates, and a 3-hour handson workshop using the IBM Qiskit platform. Two versions of this plan were executed in two different moments: (1) a one-day event open to undergraduate students from different institutions and backgrounds, and (2) a 3-day internal training course for computer science and information technology management undergraduate students from our higher education institution. Data was collected during both events through online forms and interviews to measure the learning outcomes of the produced material and better understand the public interest in the field. The results identified key elements for better teaching quantum computing for computer scientists and engineers, providing guidelines for developing a more extensive and term-long teaching plan for undergraduate technology courses.