Master of Science in Computer Science
The Master of Science in Computer Science (MSCS) program aims to provide both breadth and depth of knowledge in the concepts and techniques related to the theory, design, implementation, and applications of computer systems. Students are required to take courses which cover advanced topics in theoretical computer science and computer systems. Students of the MSCS program are expected to write a thesis under the guidance of a faculty adviser. Full-time students should be able to complete the program in two years.
Curriculum Checklist
Last Updated: May 8, 2025
| Code | Title | Description |
|---|---|---|
| CS 204 | Theory of Computation | Formal models of computation; recursive function theory; undecidability. Resourcebounded computational complexity, non-determinism, NPcompleteness. |
| CS 208 | Complexity Theory | Computational models, measures of complexity, complexity classes: nondeterministic, alternating, probabilistic, parallel. Boolean circuits. Complete problems. |
| CS 210 | Advanced Algorithms and Data Structures | Advanced data structures; algorithm design techniques; mathematical techniques in the analysis of algorithms. |
| CS 211 | Combinatorial Optimization | Design and analysis of algorithms for combinatorial optimization problems, worst-case complexity, NP- Completeness proofs, heuristics. Open problems. |
| CS 213 | Communication Theory | Mathematical theory of communication. Information Theory, Communication Channels. Coding. Cryptography. |
| CS 214 | Parallel Algorithms | Models of parallel computation. Performance measures, scalability, pipelining, techniques for analyzing parallel algorithms. Interconnection network topologies. Applications. |
| CS 216 | Randomized Algorithms | Construction and analysis of randomized algorithms. Expected performance of randomized algorithms, fundamental limitations on probabilistic computations, complexity issues, applications. |
| CS 220 | Survey of Programming Languages | Comparative study of different types of modern programming languages; imperative, functional, logic-based and object-oriented. Syntax, semantics and implementation of programming languages. |
| CS 222 | Programming Language Theory | Fundamental concepts underlying all programming languages. Semantic aspects including binding times, visibility, retention, storage management, abstraction mechanisms and extensibility. Operational and denotational semantic specifications. |
| CS 225 | Compiler Design and Construction | Theory of compiler design and construction: techniques in error correction and recovery; code generation and optimization. |
| CS 231 | Numerical Computing | Algorithm design for numerical computation. Error analysis. Performance evaluation of numerical software. |
| CS 233 | Probabilistic Methods in Computer Science | Random combinatorial structures and their applications to computer science. |
| CS 236 | Scientific Computing | Problems and methods in scientific computing. Applications from science and engineering. |
| CS 239 | Parallel Computing | Parallel computer architectures. Programming for parallel architectures. Representation, program dependence, control structures. |
| CS 240 | Computer Graphics | Solid modeling: Euler operators, finite element methods. Rendering: filling, shading, ray tracing. Natural modeling: L-systems, fractals. Image processing: filtering, antialiasing, enhancement. |
| CS 242 | Data Visualization | Visualization techniques for data from science, business, social science, demographics, and information management. |
| CS 245 | Network Optimization | Algorithms for network optimization problems; shortest paths, maximum flows, minimum-cost flows, multicommodity flows, dynamic flows, minimum cuts, matching, and assignment problem |
| CS 247 | Cryptography | Primality testing, finite fields, elliptic curves. Protocols: public key cryptography, digital signatures, zero knowledge proofs, and other cryptographic protocols. |
| CS 248 | Computational Mathematics | Overview of computational mathematics. Algorithms for computing with algebraic structures. Computer algebra systems. |
| CS 250 | Advanced Operating Systems | Synchronization and communication mechanisms, virtual memory management,file systems, deadlock control, resource allocation, protection and access control. Case study of specialized systemsother cryptographic protocols. |
| CS 252 | Advanced Computer Architecture | |
| CS 253 | Computer Security | Encryption, digital signatures,authentication, key management. Secure electronic commerce. Network Security. File security. |
| CS 255 | Advanced Computer Networks | The OSI Reference Model and layers. Distributed computing. Networked multimedia systems. Clint-server computing. Communication and internet working. |
| CS 256 | Computer Systems Performance Analysis | Overview of performance evaluation. Measurement techniques and tools. Applications of probability theory and techniques. Experimental design and analysis. Simulation and queuing models |
| CS 257 | Distributed Systems | Computer communications networks and their protocols. Event ordering and synchronization. Deadlocks. Network operating systems and languages for distributed computing. Distributed databases. Fault tolerance and recovery strategies. Applications. |
| CS 258 | Mobile Computing | Mobile computing systems. Data management, packet transmission, mobile IP, routing protocols, reliability and issues in mobile wireless networks. |
| CS 259 | Network Performance, Modeling and Monitoring | Network performance evaluation. Measurement techniques and tools. Simulation, queuing models, case studies, practicals. |
| CS 260 | Advanced Software Engineering | Structured approach to requirements analysis, system design, implementation and maintenance of software systems. Formal description and documentation techniques. |
| CS 262 | Methods of Software Development | Modern approaches to software development. Prototyping and automated tools. Computer Aided Systems Engineering (CASE) methods and tools. Object-oriented Programming Systems (OOPS). |
| CS 265 | Software Quality Assurance | Quality Management, Quality Assurance, Quality Control. Measurement and Analysis. Maturity Model. |
| CS 266 | IT Project Management | Detailed discussions of project management knowledge areas and processes. Case studies. Simulations and walk through of real-world IT projects from initiation and planning to evaluation and closing. |
| CS 267 | Software Engineering for the Web | Software process and requirements analysis, design, development and testing for web-based systems, software development tools, configuration management systems, case studies. |
| CS 268 | Web Science | The Web as a full communications medium that fosters full collaboration, social interaction, and commerce. Case studies. |
| CS 270 | Advanced Database Systems | Data models and their underlying mathematical foundations; database manipulation and query languages; functional dependencies; physical data organization and indexing methods; concurrency control; crash recovery; database security; distributed databases. |
| CS 271 | Database Theory | Data models and their underlying mathematical foundations; database manipulation and query languages; functional dependencies; physical data organization and indexing methods; concurrency control; crash recovery; database security; distributed databases. |
| CS 280 | Intelligent Systems | Fundamental issues in Intelligent Systems. Intelligent search and optimization methods. Knowledge representation and reasoning. Learning, natural language understanding, pattern recognition, knowledge-based systems and other methods in intelligent Systems |
| CS 281 | Robotic Systems | Biologically-motivated robotic systems. Reactive, deliberative, and hybrid architectures. Knowledge representation for robotics systems. Sensor fusion and perceptual strategies. Adaptation and social behavior. Knowledge representation and reasoning. Learn |
| CS 282 | Computer Vision | Image formation; early vision; segmentation from texture and motion; object representation; matching and inference; knowledge-based vision. |
| CS 283 | Data Mining | Decision trees, association rules, clustering. Intrusion detection. Design and use of serial, distributed and parallel data mining algorithms. |
| CS 284 | Machine Learning | Pattern recognition, parametric and nonparametric learning, decision trees, Bayesian and neural networks, reinforcement learning, genetic algorithms, computational learning theory. |
| CS 286 | Natural Language Understanding | Computational properties of natural languages. Morphological, syntactic and semantic processing from an algorithmic perspective. Models of acquisition and parsing. |
| CS 287 | Speech Processing | Models of speech processing, speech recognition and synthesis. Speech recognition systems. Text-to-speech systems. Applications. |
| CS 289 | Digital Image Processing | |
| CS 290 | Advanced Topics in Theoretical Computer Science | |
| CS 291 | Advanced Topics in Net-Centric Computing | |
| CS 292 | Advanced Topics in Software Technology | |
| CS 293 | Advanced Topics in Computer Systems | |
| CS 294 | Advanced Topics in Computational Science | |
| CS 295 | Advanced Topics in Intelligent Systems | |
| CS 296 | Graduate Seminar | |
| CS 297 | Special Topics | |
| CS 298 | Special Problem |