Master of Science in Computer Science

Program Mission Statement

The mission of the Computer Science program is to provide students with the ability to integrate the theory and practice of computing in the representation, processing, and use of information while upholding tradition of the liberal arts education.

Program Educational Objectives

1. Prepare graduates for computer science related careers with advanced knowledge and expertise in the computing field.
2. Prepare graduates for postgraduate studies with the ability to conduct independent research in the computing field.

Student Learning Outcomes

Students shall have the ability to:

  1.  apply advanced concepts in algorithmic design and analysis, and in other main areas in the field.
  2.  demonstrate understanding of current technology trends as well as future disciplines and emerging research areas.
  3. search, analyse, and synthesize information from computing-related literature.
  4. identify and address research problems.
  5. effectively communicate their technical and research work orally and in writing.

Admission Requirements

In addition to the admissions requirements that are explicitly stated in the Graduate Program Academic Rules, Algorithms and Data Structures (CSC310) is a required course from all students who have finished a non-computer science degree and apply for M.S. in Computer Science at LAU.  The course may be taken as a remedial course after admission.

Curriculum Requirements

Students need 30 credits for graduation including two required courses. These are:

  1. CSC600 Graduate Seminar and
  2. CSC611 Design and Analysis of Algorithms 

Program Requirements

Core Requirements (3 credits):

The following are required/core courses:

  • CSC611 Design and Analysis of Algorithms (3 cr.); and
  • CSC600 Graduate Seminar (0 cr.) and 

Project or thesis option (3 or 6 credits):

  • CSC698 / Project Option (3 cr.)
  • CSC699 / Thesis Option (6 cr.)

Electives from four concentration areas (21 or 24 credits):

The following courses are categorized into concentration areas for advising purposes. Students can choose courses from any areas they wish.

A.     Algorithms & Theory

  • CSC612 Foundations of Computer Science [3-0, 3 cr.]
  • CSC613 Computational Methods in Biology [3-0, 3 cr.
  • CSC614 Meta-Heuristics [3-0, 3 cr.]
  • CSC615 Machine Learning [3-0, 3 cr.]
  • CSC616 Cryptography and Data Security [3-0, 3 cr.]
  • CSC660 Artificial Intelligence: Principles and Techniques [3-0, 3 cr.]
  •  CSC650 Advanced Computer Graphics [3-0, 3 cr.]
  •  CSC647 Parallel Algorithms and Programming [3-0, 3 cr.]

B.     Systems

  • CSC621 Transaction Processing Systems [3-0, 3 cr.]
  • CSC622 Distributed Systems [3-0, 3 cr.]
  • CSC623 Knowledge-Based Systems [3-0, 3 cr.]
  • CSC624 Data Mining [3-0, 3 cr.]
  • CSC625 Discrete Event Simulation [3-0, 3 cr.]

C.     Hardware and Networks

  • CSC631 High Performance Computer Architecture [3-0, 3 cr.]
  • CSC632 ULSI Testing [3-0, 3 cr.]
  • CSC633 Embedded Systems [3-0, 3 cr.]
  • CSC634 Network Programming [3-0, 3 cr.]
  • CSC636 Networks Security [3-0, 3 cr.]
  • CSC637: Pervasive Computing and Wireless Networking [3-0,  3 cr. ]

D.    Software Engineering

  • CSC691 Advanced Software Engineering [3-0, 3cr.]
  • CSC694 Software Quality Assurance and Testing [3-0, 3 cr.]
  • CSC697 Managing Software Development [3-0, 3 cr.]
  • CSC690 Search-Based Software Engineering [3-0, 3 cr.]
  • CSC696 Human-Computer Interaction [3-0, 3 cr.]

E.     Other

  • CSC688 Advanced Topics in Computer Science [3-0, 3 cr.]
  •  CSC600 Graduate Seminar [0-0, 0cr.]

Last modified: October 19, 2015