CS 523, Advanced Operating Systems - Study of the concepts of operating systems, including user interfaces, process management, state saving, interprocess communication, input/output, device drivers, timing services, memory management, file management, and system abstractions

CS 531, ARTIFICIAL INTELLIGENCE - Use of the computer in human problem solving. Game theory, decision trees, Markov decision problems, selected topics.

CS 555,Functional Programming - The principles and techniques of programming with functions. Purely functional programming languages; recursion; higher-order functions; reduction models; strictness; type systems; list operations; infinite data structures; program synthesis and transformation.

CS 575, DATABASE SYSTEMS II - Review of database systems with emphasis on data description and manipulation languages; data normalization; functional dependencies; database design; data integrity and security; distributed data processing; design and implementation of a comprehensive project.

CS 581, Behavior Based Robotics - This course will explore methods for controlling artificial systems. The goal for the class will be two-fold. First we will study and understand the idea of behavior- based robotics controllers and second, we will apply some of the standard algorithms to the robot that we have built and called SKIP.

CS 691, Software Architecture - This special topics course will examine concepts and techniques for design and code reuse and generic programming in the context of Java and other object-oriented technologies. The course will focus on use of design contracts, software design patterns, and application frameworks.

CS 691, Distributed Objects - This special topics course will focus on methods for the systematic development of enterprise-level, distributed computing applications and frameworks using Java 2 Enterprise Edition and related software packages. The course content will largely be driven by needs of the group programming projects selected.

CS 691, Data Mining and Knowledge Discovery in Databases (KDD) - Knowledge discovery in databases (KDD) applies techniques from artificial intelligence, statistics, and pattern recognition to detect patterns in large databases. The goal is to discover previously unknown patterns and cause and effect relationships in the data. Data mining is one step in the KDD process.

CS 693, Masters Project