Master domain-specific quantum algorithms and learn to implement them on current quantum hardware through hands-on cloud-based programming
Master domain-specific quantum algorithms and learn to implement them on current quantum hardware through hands-on cloud-based programming
This advanced course explores key domain-specific quantum algorithms and their implementation on present-day quantum computers. Students learn about quantum Fourier transform, Shor's algorithm, and modern applications in optimization, simulation, and machine learning. The course emphasizes hands-on experience with cloud-based quantum computers and NISQ-era development, providing practical training in quantum software implementation.
Instructors:
English
English
What you'll learn
Master quantum Fourier transform and search algorithms
Develop hybrid quantum-classical algorithms
Implement quantum simulation and optimization techniques
Create quantum machine learning applications
Use cloud-based quantum programming platforms
Understand NISQ-era algorithm development
Skills you'll gain
This course includes:
Live video
Graded assignments,Exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
Closed caption
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by

Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.





Module Description
The course focuses on advanced quantum algorithms and their practical implementation. Students explore quantum Fourier transform, search algorithms, hybrid quantum-classical approaches, and applications in optimization and machine learning. The curriculum emphasizes hands-on experience with cloud-based quantum computers and modern NISQ devices. Special attention is given to real-world applications in quantum chemistry, simulation, and data science.
Fee Structure
Instructor

7 Courses
Pioneering Spintronics and Quantum Physics Researcher
Pramey Upadhyaya is a distinguished Associate Professor of Electrical and Computer Engineering at Purdue University, whose academic journey includes a B.Tech from IIT Kharagpur (2009), followed by MS (2011) and Ph.D. (2015) degrees from UCLA, where he worked as a resident theorist in Prof. Kang Wang's Device Research Laboratory. Following his doctoral studies, he completed a postdoctoral fellowship at UCLA's Physics and Astronomy Department under Prof. Yaroslav Tserkovnyak. His groundbreaking research in quantum physics and spintronics has led to pioneering demonstrations of current-induced room-temperature skyrmion manipulations, spin torque switching using topological surface states, and NV-center probing of spin-caloritronics. His work has resulted in over 30 publications in prestigious journals including Science, Physical Review Letters, and Nature Nanotechnology, achieving an H-index of 24. His exceptional contributions to the field have been recognized with several prestigious awards, including an NSF Career Award (2020), Qualcomm Innovation Fellowship (2013), and Intel Summer Fellowship (2011), while his current research at Purdue focuses on advancing quantum phenomena and material science for next-generation computing applications.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.