Master of Arts in Computer Science
The study of computer science at Queens College is a springboard to any field that uses computers and computation for data analysis (Big Data) and for scientific discovery—from financial services to health care.
- Get credentialed in the field of the future—computer science has a projected 10-year job-growth rate of 36.5 percent
- Queens College Computer Science faculty have won more National Science Foundation Faculty Early Career Development Awards than faculty from any other department in the CUNY system
Our Center for Computational Infrastructure for the Sciences (CCiS) will show you how to take your computer science career in any direction. CCiS brings together the knowledge and faculty of numerous departments in the natural and social sciences and offers opportunities for cross-disciplinary collaborations on real-world problems and projects.
Why pursue Computer Science at Queens College?
- The field has been ranked #1 by Kiplinger’s for “Best Majors for a Lucrative Career”
- In support of their cutting-edge research projects, our accomplished faculty have won over $6 million in recent years from such organizations as the National Science Foundation, the National Institutes of Health, DARPA, the Air Force Office of Scientific Research, the Army Research Lab, Google, and IBM
- Our students complete internships in a host of organizations and have gone on to positions at Morgan Stanley, Citigroup, Ernst & Young, Estee Lauder, Etsy, CA Technologies, McGraw-Hill—the list is long, varied, and impressive
The dynamic and growing field of computer science provides opportunities for intellectual activity, research, and future employment. The aim of the master’s program is to prepare students for professional careers in private industry, government, and academe. For those who seek academic careers and opportunities for more advanced research, the master’s program may constitute a significant portion of the PhD program offered by the CUNY Graduate Center.
The Master of Arts in computer science includes courses in four areas of study: software, theoretical foundations, hardware, and mathematical applications and algorithms.
The software area is the primary focus of the program, and includes courses in fundamental algorithms, software design, database systems, distributed software systems, operating systems, compiler design, graphics, information organization and retrieval, and artificial intelligence. The Theoretical Foundations courses include the mathematical treatment of such topics as formal language theory, automata theory, and computability theory. The Hardware area course offerings cover topics including computer systems design, networking principles, and distributed hardware systems. The Mathematical Applications and Algorithms area includes courses covering sequential and parallel numerical algorithms, applications of probability and statistics to the study of hardware and software systems, and principles of simulation and modeling.
Requirements for Matriculation
These requirements are in addition to the general requirements for matriculation.
- Matriculation is based on merit as judged by the Graduate Admissions Committee of the department. The committee will expect each candidate for matriculation to have an adequate mathematics background, including integral calculus, probability and statistics, and discrete mathematical structures.
- Matriculation requirements also include a working knowledge of at least one high-level, object-oriented programming language (some courses, including core courses, require knowledge of specific languages; consult the department for current requirements), assembly language programming, data structures, principles of programming languages, operating systems, computer organization, and theory of computation. A candidate who is partially deficient in the above requirements may, at the discretion of the Admissions Committee, be admitted subject to the requirement that the deficiencies be rectified. Appropriate means to fulfill this requirement are provided by the department. Courses taken to meet admissions deficiencies do not count toward the credit requirements for the degree; the average (mean) grade in these courses must be at least B (3.0), and each one of these courses must be completed with a grade of B– or better.