Computer Science (CS)

CS 502 Computer Architecture3 Credit hours   

Design and analyze structure of major hardware components of computers including: ALU, instruction sets, memory hierarchy and caching, parallelism through multicore and many core, GPGPUs, storage systems and interfaces.

Grade Mode: Normal Grading Mode
CS 504 High Performance Computing3 Credit hours   

Learn how to develop highly optimized applications for multi-core processors and clusters using software tools, parallel algorithms, performance profilers, and programming constructs in MPI, OpenMP, MapReduce, CUDA, and OpenCL.

Grade Mode: Normal Grading Mode
CS 505 Computing for Bioinformatics3 Credit hours   

Study of computational algorithms and programming techniques for various bioinformatics tasks including parsing DNA files, sequence alignments, tree construction, clustering, species identification, principal component analysis, correlations, and gene expression arrays.

Grade Mode: Normal Grading Mode
CS 510 Advanced Database Systems3 Credit hours   

This course introduces advanced topics in database systems including distributed systems, distributed databases, Big Data, cloud service, semantic web, web services, information security & privacy, and electronic commerce.

Grade Mode: Normal Grading Mode
CS 511 Advanced Programming3 Credit hours   

The course covers advanced topics in Python programming including the use of parallel computation and GPU acceleration and investigate how to exploit frameworks such as Hadoop and Spark.

Grade Mode: Normal Grading Mode
CS 512 Embedded Systems3 Credit hours   

The design of systems containing embedded computers. Micro-controller technology, assembly language and C programming, input/output interfacing, data acquisition hardware, interrupts, and timing. Real-time operating systems and application programming. Application examples.

Grade Mode: Normal Grading Mode
CS 515 Data Mining3 Credit hours   

Covers (1) the process of knowledge discovery, (2) algorithms (association rules, classification, and clustering), and (3) real-world applications. Focuses on efficient data mining algorithms and scaling up data mining methods.

Grade Mode: Normal Grading Mode
CS 540 Digital Image Processing3 Credit hours   

Study of mathematical techniques and algorithms for image sampling, quantization, intensity transformations, spatial filtering, Fourier transforms, frequency domain filtering, restoration and reconstruction, color imaging, wavelets, morphological image processing, and segmentation.

Grade Mode: Normal Grading Mode
CS 550 Information Retrieval3 Credit hours   

Study of theory and algorithms for modeling and retrieving text. Text representation, IR models, query operations, retrieval evaluation, information extraction, text classification and clustering, enterprise and Web search, recommender systems.

Grade Mode: Normal Grading Mode
CS 552 Natural Lang Processing3 Credit hours   

Fundamental algorithms and computational models for core tasks in natural language processing: word and sentence tokenization, parsing, information and meaning extraction, spelling correction, text summarization, question answering, and sentiment analysis.

Grade Mode: Normal Grading Mode
CS 580 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 581 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 582 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 583 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 600 Advanced Web Technology3 Credit hours   

This course introduces modern web technologies and covers the concepts, practices, and technologies to design, develop, and manage scalable, reliable and secure web applications using client side and server side programming, mobile technology, web services, rest services, and cloud services that are accessible to a large number of users.

Grade Mode: Normal Grading Mode
CS 601 The Internet of Things3 Credit hours   

This course covers the Internet of Things (IoT) Technologies. The course includes advanced topics in wireless networking technologies, mobile networks, software and hardware design for IoT applications and systems. In addition, this course offers advanced topics in cybersecurity.

Grade Mode: Normal Grading Mode
CS 602 Cloud Computing3 Credit hours   

Study of emerging and advanced topics in Cloud Computing including theory and application development in cloud and understand the ways of increasing quality of services for hosted applications.

Grade Mode: Normal Grading Mode
CS 605 Software Specifications3 Credit hours   

Study of software specification and verification technologies that facilitate: semantic reasoning; and verification of development artifacts including functional models, architecture, and source-code implementations.

Grade Mode: Normal Grading Mode
CS 610 Software Design3 Credit hours   

Study of approaches to software design that meet availability, manageability, maintainability, performance, reliability, scalability, and securability goals. Emphasis is on object-oriented analysis and design, design patterns and metrics.

Grade Mode: Normal Grading Mode
CS 615 Software Testing3 Credit hours   

Study of methods and tools to design high quality tests during all phases of software development. Topics include test design, test automation, test coverage criteria, and how to test software.

Grade Mode: Normal Grading Mode
CS 620 Applied Algorithms3 Credit hours   

Study of clustering, graph-theoretic, genetic, probabilistic and randomized algorithms and their application to machine learning, data streams, data mining, computer vision, natural language processing, information retrieval, and bioinformatics.

Grade Mode: Normal Grading Mode
CS 625 AI Principles and Methods3 Credit hours   

Study of machine learning and statistical pattern recognition algorithms and their application to data mining, bioinformatics, speech recognition, natural language processing, robotic control, autonomous navigation, text and web data processing.

Grade Mode: Normal Grading Mode
CS 630 Machine Learning3 Credit hours   

Study of machine learning and statistical pattern recognition algorithms and their application to data mining, bioinformatics, speech recognition, natural language processing, robotic control, autonomous navigation, text and web processing.

Grade Mode: Normal Grading Mode
CS 645 Advanced Topics Bioinformatics3 Credit hours   

Study of advanced algorithms, data structures, and architectures required for solving complex problems in Bioinformatics. Focus is on analysis of patterns in sequences and 3D-structures. Team taught seminar course.

Grade Mode: Normal Grading Mode
CS 650 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 651 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 652 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 653 Special Topics1-4 Credit hours   

Study of emerging and advanced topics in Computer Science. Topics vary with instructor and change from one semester to another.

Grade Mode: Normal Grading Mode
CS 660 Big Data Systems3 Credit hours   

Learn high performance computing architectures and methods for developing and querying databases for Big Data.

Grade Mode: Normal Grading Mode
CS 670 Visual Analytics3 Credit hours   

Study of approaches, algorithms, and tools for Big Data exploration, analysis, and interpretation to enable novel discoveries and innovation. Integrating analytic capabilities of computers and domain knowledge of human analysts.

Grade Mode: Normal Grading Mode
CS 681 Thesis1-6 Credit hours   

Investigate a research problem of theoretical interest and practical value under mentorship of a computer science faculty.

Attributes: No Textbook Required
Grade Mode: Credit/No Credit Grade Only
CS 685 Independent Study1-4 Credit hours   

Pursue faculty supervised, individualized course of study of a topic which is not currently a part of the Computer Science graduate curriculum.

Grade Mode: Normal Grading Mode
CS 686 Independent Study1-4 Credit hours   

Pursue faculty supervised, individualized course of study of a topic which is not currently a part of the Computer Science graduate curriculum.

Grade Mode: Normal Grading Mode
CS 687 Independent Study1-4 Credit hours   

Pursue faculty supervised, individualized course of study of a topic which is not currently a part of the Computer Science graduate curriculum.

Grade Mode: Normal Grading Mode
CS 688 Independent Study1-4 Credit hours   

Pursue faculty supervised, individualized course of study of a topic which is not currently a part of the Computer Science graduate curriculum.

Grade Mode: Normal Grading Mode
CS 690 Comprehensive Project3 Credit hours   

Develop expertise in an emerging area of computer science through guided study under faculty mentorship.

Attributes: No Textbook Required
Grade Mode: Credit/No Credit Grade Only
CS 698 Internship1-3 Credit hours   

Supervised work experience in computer science or related fields.

Attributes: No Textbook Required
Grade Mode: Credit/No Credit Grade Only