Quantum Information Technologies and a Practical Module is a new course we launch at Shanghai Jiao Tong University targeting at the undergraduate students who major in a variety of engineering disciplines. We develop a holistic curriculum for quantum computing covering the quantum hardware, quantum algorithms and applications. The quantum computing approaches include the universal digital quantum computing, analog quantum computing and the hybrid quantum-classical variational quantum computing that is tailored to the noisy intermediate-scale quantum (NISQ) technologies nowadays. Besides, we set a practical module to bring student closer to the real industry needs. The students would form a team of three to use any quantum approach to solve a problem in fields like optimization, finance, machine learning, chemistry and biology. Further, this course is selected into the Jiao Tong Global Virtual Classroom Initiative, so that it is open to global students in Association of Pacific Rim Universities at the same time with the offline students, in a specifically updated classroom. The efforts in curriculum development, practical module setting and blended learning make this course a good case study for education on quantum sciences and technologies.
Quantum Information Technologies and a Practical Module is a new course we launch at Shanghai Jiao Tong University targeting at the undergraduate students who major in a variety of engineering disciplines. We develop a holistic curriculum for quantum computing covering the quantum hardware, quantum algorithms and applications. The quantum computing approaches include the universal digital quantum computing, analog quantum computing and the hybrid quantum-classical variational quantum computing that is tailored to the noisy intermediate-scale quantum (NISQ) technologies nowadays. Besides, we set a practical module to bring student closer to the real industry needs. The students would form a team of three to use any quantum approach to solve a problem in fields like optimization, finance, machine learning, chemistry and biology. Further, this course is selected into the Jiao Tong Global Virtual Classroom Initiative, so that it is open to global students in Association of Pacific Rim Universities at the same time with the offline students, in a specifically updated classroom. The efforts in curriculum development, practical module setting and blended learning make this course a good case study for education on quantum sciences and technologies.
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.
Quantum computing is an interdisciplinary field that spans physics, mathematics, computer engineering, and computer science. Teaching quantum computing effectively within a constrained timeframe presents a challenge, particularly for engineering students with diverse academic backgrounds. This paper presents an approach to integrating quantum computing into a broader course on Technologies of Computing Systems (TCS) through a dedicated two-week module. The course structure combines lectures, interactive problem-solving, lab exercises, and a hands-on project to ensure an engaging and practical learning experience. The curriculum covers fundamental quantum computing principles, quantum gates, circuits, algorithms, and quantum technology. Assessment includes project work, exams, and student feedback, demonstrating increased engagement and comprehension. The results indicate that this quantum computing module successfully bridges the gap between classical and quantum paradigms, fostering student interest and understanding within a short period.
Quantum information is a new discipline with the intersection of quantum physics and information technology,which has developed rapidly recently and has been on the road of industrialization.In contrast,the severe shortage of the practitioners,who can understand quantum information technology in depth,have become bottlenecks restricting the development of this technology.The lack of talent stems is from the lack of education,especially for the undergraduate students of engineering.Benefitting from the vigorous growth of quantum information in China,the fundamental of infiltrating the quantum information course in the undergraduate education of engineering can be performed,and some positive effects have been achieved.The course has carried out the teaching reforms,and practices in terms of teaching objectives,curriculum structure,practical methods,which have gained good teaching results.These teaching experiences and ideas provide a valuable reference for quantum information education in the cyberspace security discipline.
Quantum computing harnesses quantum laws of nature to enable new types of algorithms, not efficiently possible on traditional computers, that may lead to breakthroughs in crucial areas like materials science and chemistry. There is rapidly growing demand for a quantum workforce educated in the basics of quantum computing, in particular in quantum programming. However, there are few offerings for non-specialists and little information on best practices for training computer science and engineering students. In this report we describe our experience teaching an undergraduate course on quantum computing using a practical, software-driven approach. We centered our course around teaching quantum algorithms through hands-on programming, reducing the significance of traditional written assignments and relying instead on self-paced programming exercises ("Quantum Katas''), a variety of programming assignments, and a final project. We observed that the programming sections of the course helped students internalize theoretical material presented during the lectures. In the survey results, students indicated that the programming exercises and the final project contributed the most to their learning process. We describe the motivation for centering the course around quantum programming, discuss major artifacts used in this course, and present our lessons learned and best practices for a future improved course offering. We hope that our experience will help guide instructors who want to adopt a practical approach to teaching quantum computing and will enable more undergraduate programs to offer quantum programming as an elective.
There is a growing need for scientists and engineers with Quantum Information Science and Technology (QIST) skills.To address this need for 'quantum aware' graduates we describe a two-course sequence in quantum computing suitable for undergraduate students studying electrical engineering, physics, and computer science.Our approach is unique in that it aims to take full advantage of the diverse backgrounds of second and third year undergraduate students from these three STEM disciplines.Students will work in interdisciplinary teams to (1) understand the physics and the computational theory relevant to quantum computing, (2) develop computer code that simulates a quantum computer, (3) understand the relevance and importance of existing quantum computing algorithms, and (4) appreciate the need for future research in quantum computing.Our approach is informed in part by our experience working with a pair of undergraduate students this past summer on the development of a Python-based quantum computer simulator.This experience showed that building a simulator was an effective way to teach the theory underlying quantum computing.Building a simulator also provides an excellent foundation upon which to explore student-accessible research projects in quantum computing, which is a high-impact educational practice.
Quantum computing promises solutions to problems that are beyond the reach of classical machines; however, current noisy intermediate-scale quantum (NISQ) devices require both theoretical insight and hardware expertise.This paper presents a six-module curriculum designed to bridge that gap for undergraduates from diverse disciplines.The modules progress from Python programming to electronics and circuits, vacuum technology, cryogenic measurements, microwave and RF systems, and culminate with quantum simulations and computations.Implemented at Winston-Salem State University with thirty students across computer science, information technology, mathematics, chemistry, physics, and biology, the program combined lectures, group projects, and presentations.Hands-on activities included resistor network analysis, magnetic levitation, vacuum chamber assembly, cryogenics measurements, RF component analysis, and entanglement experiments, enabling students to connect abstract principles with laboratory practice.Outcomes showed increased confidence, collaboration, critical thinking, and skill set building, even among those with no prior background.Students advanced to research-oriented projects like secure quantum communication protocols and the Quantum Mini Tennis game, which explored gate operations and qubit transformations, demonstrating that hardware-aware quantum education lowers barriers, fosters interdisciplinary participation, and prepares students for NISQ-era challenges.