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Course Criteria
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3.00 Credits
Credits: 3 Cross-Listed with IT 852 Current research in advanced computer graphics, and applications in realistic real-time simulations. Topics include physically based modeling, real-time simulation, distributed interactive simulation (DIS), network virtual environments (NVE), and virtual reality (VR). Prerequisites CS 652 or IT 875. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Current and emerging issues in human-computer intelligent interaction, and human-centered systems and their applications. Topics include video processing, visualization, virtual environments, adaptation and tutoring, image and scene modeling, analysis and synthesis, face and gesture recognition, and speech and natural language processing. Prerequisites CS 580, and 652 or 682; or permission of instructor. Notes Term project and topical review required. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with INFS 780 This course covers advanced algorithms for data management, learning, and mining large multimedia databases. Issues related to handling such data including feature selection, high dimensional indexing, interactive search and information retrieval, pattern discovery, and scalability to large datasets are discussed. Mining techniques and data types to be covered include texts/web, images, videos, DNA, temporal, spatial, spatiotemporal databases, graph mining, stream mining, and data visualization. Prerequisites INFS 755 or CS 750 or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Surveys machine learning concerning development of intelligent adaptive systems that are able to improve through learning from input data or from their own problem-solving experience. Topics provide broad coverage of developments in machine learning, including basic learning strategies and multistrategy learning. Prerequisites CS 681, 687, or 688; or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Principles and major methods of basic stages of knowledge acquisition such as systematic elicitation of expert knowledge, knowledge base refinement, and knowledge base optimization in the context of general problem-solving methods. Includes case studies of successful knowledge acquisition and problem-solving systems, and projects involving development or application of knowledge acquisition tools for knowledge-based systems. Prerequisites CS 680, 681, or 687; or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Advanced topics not occurring in regular sequence. Prerequisites Admission into computer science PhD program. Notes May be repeated for credit when subject differs. Satisfies MS breadth requirement only if explicitly stated in syllabus in given section. Only one such course should be used for breadth requirements. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Master's degree candidates undertake a project using knowledge gained in MS program. Prerequisites 18 credits applicable toward MS in computer science. Notes Topics chosen in consultation with advisor. Meets project or thesis requirement for MS in computer science. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 - 6.00 Credits
Credits: 3-6 Original or expository work evaluated by committee of three faculty members. Prerequisites 18 credits applicable toward MS in computer science. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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1.00 Credits
Credits: 1 Students are required to attend colloquia including talks by distinguished speakers, faculty candidates, and Mason faculty. Prerequisites Admission to CS PhD program. Notes This course introduces PhD students to research topics in computer science. This course can be taken twice for credit. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0 Grading Students will receive a grade of satisfactory (S) or no credit (NC).
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3.00 Credits
Credits: 3 Individualized intensive study of information technology. Notes May be repeated as needed. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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