The School of Arts & Sciences

Department of Computer Science & Mathematics

M.S. in Computer Science (Old Program)

The information below covers the M.S. in Computer Science for students enrolled prior to Fall 2015. 

The Master of Science in Computer Science aims at encouraging the discovery and transmission of knowledge, the education of students, the training of future faculty, and the general wellbeing of society. The program provides a broad foundation of study in computer science combined with in-depth study in four concentration areas.

Graduate work in computer science involves the study of the development of physical and theoretical design and understanding of computer systems, as well as the implementation of those developments into everyday life.

Graduates of the master’s program may become researchers, computer systems analysts, computer systems administrators, and take up many other careers in the industry.

The program is balanced in breadth and depth in support of the department’s research thrust areas. Recognizing different needs, LAU offers two plans—one with a thesis option and one with a project option. Both require 30 credits of course work that are offered at night.

Admission requirements

In addition to the admission requirements that are explicitly stated in the graduate admissions page, CSC310 Algorithms and Data Structures is a required course from students who have a non-computer science degree. It may be taken as a remedial course after admission.

Curriculum

The graduate curriculum requires one core course that is fundamental to the study of computer science. Students, however, will have three additional courses, one from each area. The four concentration areas are:

The remaining courses may be chosen from any of the four areas without restrictions. The graduate program also offers an advanced “Topics” course that may be taken more than once, to let students gain even more in-depth knowledge in a particular area. This course may be repeated for credits more than once.

Students need 30 credits of major courses (12 credits for the core, one course from each area, three credits for the project, or six credits for the thesis, and 12 or 15 credits of electives).

I. Core requirements (12 credits)

Four three-credit courses: one from each of the four concentration areas listed below. CSC711 Design and Analysis of Algorithms is mandatory from the first area.

II. Project or thesis option (3 or 6 credits)

Number Course Cr
CSC798 Project 3
CSC799 Thesis 6

III. Electives from four concentration areas (12 or 15 credits)

A. Algorithms, Theory and Computational Science

Number Course Cr
CSC711 Design and Analysis of Algorithms 3
CSC712 Automata Theory and Formal Languages 3
CSC713 Bioinformatics 3
CSC714 Heuristic Optimization 3
CSC715 Machine Learning 3
CSC716 Cryptography and Data Security 3

B. Systems

Number Course Cr
CSC721 Transaction Processing Systems 3
CSC722 Distributed Systems 3
CSC723 Knowledge-Based Systems 3
CSC724 Data Mining 3
CSC725 System Simulation 3
CSC726 Compilers 3

C. Hardware and Networks

Number Course Cr
CSC731 High Performance Computer Architecture 3
CSC732 ULSI Testing 3
CSC733 Embedded Systems 3
CSC734 Advanced Computer Networks 3
CSC736 Networks Security 3
CSC737 Pervasive Computing and Wireless Networking 3

D. Software Engineering

Number Course Cr
CSC791 Advanced Software Engineering 3
CSC792 Object-Oriented Software Engineering 3
CSC793 Software Testing and Analysis 3
CSC794 Software Quality Assurance 3
CSC795 Safety-Critical Systems 3
CSC796 Human-Computer Interaction 3
CSC788 Advanced Topics in Computer Science (in any of the four concentration areas). May be repeated.  

 


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