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Computer Science is the science of computation using a programmable computing machine, of developing the programs for the computation, developing algorithms for solving computational problems, of acquiring, storing, managing data and information needed in those computations, and of estimating or predicting the feasibility and time constraints of arriving at solutions.



Graduate programs in Computer Science (CS) differ from undergraduate programs not so much in the topics they cover but in the depth in which the topics are covered. The student has to master deep knowledge of algorithms, operating systems, compilers, internals of databases, visual and sound recognition, robotics, and - in general – has to acquire sufficiently well-founded theoretical knowledge to contribute to computerization in fields not yet known.

students working together at desktop

The Computer Science program is concerned with the theoretical as well as the practical issues of CS. The theoretical basis must be mastered because CS has a strong relation to mathematical and algorithmic thinking. An essential portion of a computer scientist’s work consists of understanding and researching algorithms, as well as developing new ones.

This curriculum prepares the graduates for successful careers in the demanding and ever-growing job market in all fields of society that experience computerization in any form, be it web page design, IT security, software development in medicine, education, business administration, robotics, Internet of Things, and more. A solid knowledge of the computer science principles underlying all computerization and program development, augmented by training in leading-edge practical skills will enable graduates to play leadership roles in industry as well as to pursue PhD degrees. The development of this graduate curriculum has taken the recommendations of the Joint Task Force on Computing Curricula of the IEEE Computer Society and the Association for Computing Machinery of August 2004 into consideration.


Required Core Courses
Course Code Course Title Course Description
CSC 501 Discrete Structures Read Description
CSC 502 Principles of OS & Distributed Systems Read Description
CSC 620 Programming Language Theory Read Description
CSC 680 Advanced Computer Algorithms Read Description
ICS 501 Introduction to Cyber Security Read Description
Required Courses:
  • 4 Core Courses: 12 credit hours
  • 1 Capstone Course: Project or Thesis: 3 credit hours
  • 1 Internship: 1 credit hour

Elective Courses: 11-20 credit hours
  • Internship: 1-9 credit hours
  • Cross Disciplinary Course: Up to 3 credit hours (counts as Elective)
  • Transfer Credits: Up to 9 credit hours (counts as Elective)

36 Total credit hours


Computer scientists often work in organizations that develop new technologies and algorithms. Examples include: pattern recognition and signal processing for self-driving cars, artificial intelligence, and data mining. The development of new algorithms often requires a deep understanding of mathematics including knowledge in certain areas of abstract algebra for developing new encryption technologies or counteracting attempts at breaking them. They often work doing research in computer science, as well as working as information technology consultants in banking, insurance companies, and higher education.