Master's Computer Science

Master’s in Computer Science degree program caters to the development of strong computer and information technology skills that can be applied in different professional pursuits. The course curriculum of this degree program allows the students to become experts in information system analysis, programming and hardware installation, server management and networking, system analysis, computer architecture organization, data analysis and software technology that is used in leading global organizations. After completing this degree programs, students become eligible to acquire employment at not only big multi nationals but also government and state agencies as well.

As a result of completing this program, students should be able to:


WHAT YOU'LL LEARN

As a result of completing this program, students should be able to:

  • Exploring business and technology development and understand how IT add value to businesses
  • Gaining a comprehensive and effective understanding of information systems design and programming as well as fundamental management areas.
  • Develop strong analytical and theoretical skills that can be applied to many different professional pursuits, from engineering to medicine to financial analysis.
  • Gaining an effective, comprehensive understanding of information systems design and programming as well as fundamental management areas.
  • Providing knowledge and skills vital for all organizations
  • Discover business and technology trends and understand how IT add value to businesses
General studies
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Information Research Strategies 2 Introduction to information research including electronic resources. This course is designed to help researchers locate, evaluate, and use information. It includes exploration of the research process, search strategies, locating resources, source documentation, and organization of research.
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Compiler Design, Theory, and Optimization 2 Design and theory of programming language translators and the theory and implementation of optimizers. Topics include: intermediate representations, advanced code generation, control- and data-flow analysis, advanced compiler optimization, dynamic compilation, global register allocation and instruction scheduling.
Theory of Computation 2 Topics covered include Turing machines and their variants, the halting problem and decidability, computability, reducibility, NP-completeness, time and space complexity, and topics from recursive function theory.
Advanced Algorithms 2 Design and analysis of advanced algorithms. Topics include algorithms for complex data structures, probabilistic analysis, amortized analysis, approximation algorithms, and NP-completeness. Design and analysis of algorithms for string-matching and computational geometry are also covered.
Parallel Algorithms 2 Advanced topics in the design, analysis, and performance evaluation of parallel algorithms. Topics include advanced techniques for algorithm analysis, memory models, run time systems, parallel architectures, and program design, particularly emphasizing the interactions of these factors.
Advanced Operating Systems 2 Advanced concepts in operating systems. Topics include real-time and multiprocessor scheduling, I/O, modern file systems, and performance analysis. Also requires a substantial implementation project.
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Mobile Networks 2 Mobile network issues including routing and mobility management strategies in ad hoc networks, sensor networks, and personal area networks such as Bluetooth.
Systems Performance Analysis 2 Analysis of the performance of computer systems. Topics include: measurement techniques and tools, probability theory and statistics, experiment design and analysis, simulation, queuing models. Course includes a significant experimental component.
Software/Hardware Design of Multimedia Systems 2 A comprehensive overview of the design and implementation of the hardware and software of a platform for multimedia applications. Topics include system level design methodology, single-instruction-multiple data processor (SIMD), virtual platform implementation, development of an SIMD parallel compiler, and real-time operating systems (RTOS).
Advanced Computer Architecture 2 An in-depth study of various aspects of parallel processing, with an emphasis on parallel architectures. The course has an analytical focus and investigates models of various aspects of the design and analysis of parallel systems. Topics include simple uniprocessor/multiprocessor performance models, pipelining, instruction-level parallelism, and multiprocessor design issues.
Distributed Systems 2 Covers time and order in distributed systems; mutual exclusion, agreement, elections, and atomic transactions; Distributed File Systems, Distributed Shared Memory, Distributed System Security; and issues in programming distributed systems. Uses selected case studies.
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GPU and Multicore Programming 3 Introduction to Graphics Processing units (GPU) and multi-core systems, their architectural features and programming models, stream programming and compute unified driver architecture (CUDA), caching architectures, linear and non-linear programming, scientific computing on GPUs, sorting and search, stream mining, cryptography, and fixed and floating point operations.
Computer Graphics: Advanced Rendering and Modeling 3 Topics include polygonal objects, lighting models, shadows and textures, ray-tracing, radiosity, photon mapping, parametric curves and surfaces, meshes, and mesh modeling.
Data Visualization 3 Introduction to scientific and information visualization. Topics include methods for visualizing three-dimensional scalar and vector fields, visual data representations, tree and graph visualization, large-scale data analysis and visualization, and interface design and interaction techniques.
Immersive Virtual Environments 3 An introduction to immersive virtual environment technologies and their applications. Topics include: wall-sized displays, head-mounted displays, 3D displays, orientation and position tracking, human perception, and recent research utilizing virtual reality systems.
Human-Computer Interactions and Usability Testing 3 Current issues in human-computer interaction (HCI), evaluation of user interface (UI) design, and usability testing of UI. Course requires documenting UI design evaluation, UI testing, and writing and presenting a HCI survey, concept or topic paper.
Advanced Artificial Intelligence 3 Course topics include current topics in artificial intelligence including agent-based systems, learning, planning, use of uncertainty in problem solving, reasoning, and belief systems.
Computational Intelligence - Theory and Application 3 This course covers the four main paradigms of Computational Intelligence, viz., fuzzy systems, artificial neural networks, evolutionary computing, and swarm intelligence, and their integration to develop hybrid systems. Applications of Computational Intelligence include classification, regression, clustering, controls, robotics, etc.
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Thesis 3 An independent research and scholar reporting on a selected topic specifically selected from related subjects. The department schedules and coordinates a number of seminars to assist students selecting the topics and to fine tune their work up to reporting.