Graduate Certificate in Quantum Computing
The Science Academy, housed in the College of Computer, Mathematical, and Natural Sciences (CMNS), draws on the university’s collective expertise to provide academic programs that are both rigorous and relevant. Science Academy Graduate Programs translate research into applied knowledge and provides current and future professionals with invaluable skills.
Mentoring and advising are an essential part of the program. Students meet with faculty and the academic program director to ensure that educational goals and career learning and development goals are met. Students should contact the contact the program director, Amy Chester via email: firstname.lastname@example.org.
The Graduate Certificate in Quantum Computing, In Person (Z157) has a 12-credit, 4-course curriculum that introduces students to quantum computing and provides an overview of its current state.
- Explores the application of quantum computing to optimization, encryption, information theory, and communications.
- Plan of study includes both theoretical and experiential components, offering students the opportunity of a hands-on approach to learning quantum computing fundamentals and practical knowledge.
- Students apply learning through hands-on exercises and experiential learning.
- No prior knowledge in quantum physics or quantum computing is necessary.
- Can be completed in nine months of continuous part-time enrollment. See Designation of Full-time/Part-time Status.
Quantum computing has the potential to enhance secure communications through novel encryption key distribution methods and explore solutions to problems previously deemed too hard to tackle for classical computing. Quantum computing can also revolutionize well established disciplines such as data science and machine learning making it a critical area of study in today’s market. In this program,
- Students explore machine learning and identify areas where quantum computing can impact the discipline.
- Students also explore applications of quantum computing to optimization, encryption, information theory, and communication.
- Students learn to explain the principles behind quantum computing, implement and execute applications on quantum computers or their simulators, and be ready to differentiate between the physical implementations of quantum computers and how this affects capabilities and performance.
- Students learn to make appropriate and successful business decisions when quantum technologies reach maturity.
Below is a listing of all program courses. For a detailed course description that includes pre-requisites or co-requisites, see The Graduate School Catalog, Course Listing as follows: MSQC Course Descriptions (Coming soon).
|Core||MSQC601||The Mathematics and Methods of Quantum Computing|
|Core||MSQC602||The Physics of the Very Small and its Technological Ramifications|
|Core||MSQC603||Principles of Machine Learning|
|Core||MSQC604||Quantum Computing Architectures and Algorithms|
- See the sample plan of study, below. Students should use this as a guide to develop a plan with the academic program director.
- Actual course offerings are determined by the program and may vary semester to semester. Students should note if a course has a pre-requisite or co-requisite.
- Specific class meeting information (days and time) is posted on UMD’s interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit.
- The program uses specific section codes for registration, which are listed on the sample plan of study.
|Semester||Year||Course Number||Section Code||Credits|
- Classes meet in UMD College Park campus classrooms, offering a focused, distraction-free learning environment.
- Classes held weekday evenings (e.g., after 5:00 p.m.) to accommodate the working professional’s schedule
- Uses the semester academic calendar with classes held in the fall and spring semester (16 weeks each).
- Instruction provided by University of Maryland faculty and professionals in the field. Includes instructors from several departments across campus, including Computer Science, Biology, Cell Biology and Molecular Genetics, Mathematics, and Electrical and Computer Engineering.
- Instructors present dynamic and interactive seminar-style instruction.
- Students enrolled in a program that features in-person instruction are required to submit the University’s Immunization Record Form prior to the first day of their first semester/term. See Health Requirements.