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• CSC 490: Selected Topics in Computer Science

  3.00 Credits

  Shippensburg University of Pennsylvania

  
  Opportunity to offer courses in areas of departmental major interest not covered by the regular courses. This class is available for graduate credit.
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• CSC 491: Selected Topics in Computer Science

  3.00 Credits

  Shippensburg University of Pennsylvania

  
  Opportunity to offer courses in areas of departmental major interest not covered by the regular courses. This class is available for graduate credit.
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• CSC 492: Selected Topics in Computer Science

  3.00 Credits

  Shippensburg University of Pennsylvania

  
  Opportunity to offer courses in areas of departmental major interest not covered by the regular courses. This class is available for graduate credit.
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• CSC 493: Selected Topics In Computer Science

  4.00 Credits

  Shippensburg University of Pennsylvania

  
  Presents topics that will vary according to need. Topics such as languages are appropriate. This class is available for graduate credit. Prerequisite:    CSC 111 FOR LEVEL U WITH MIN. GRADE OF D AND MAT 211 FOR LEVEL U WITH MIN. GRADE OF D AND MAT 318 FOR LEVEL U WITH MIN. GRADE OF D
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• CSC 494: Selected Topics in Computer Science

  4.00 Credits

  Shippensburg University of Pennsylvania

  
  Opportunity to offer courses in areas of departmental major interest not covered by the regular courses. This class is available for graduate credit.
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• CSC 495: Selected Topics in Computer Science

  4.00 Credits

  Shippensburg University of Pennsylvania

  
  Opportunity to offer courses in areas of departmental major interest not covered by the regular courses. This class is available for graduate credit.
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• CSC 498: Senior Research Methods

  2.00 Credits

  Shippensburg University of Pennsylvania

  
  Students will learn basic research strategies including conducting literature reviews, designing experiments, defining hypotheses, and writing proposals. Topics include finding and evaluating sources of information, defining topics, developing and supporting a hypotheses, and acceptable research and experimental practices. Prerequisite: Computer science major with junior status and a C or better in any combination of five computer science and computer engineering courses. Graduate students are not permitted to take this course. This class is not available for graduate credit.
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• CSC 499: Senior Research and Development

  2.00 Credits

  Shippensburg University of Pennsylvania

  
  Students will independently, but under the direction of the instructor, execute the proposal developed in CSC498. Students will conduct the experiments outlined in their testing / implementation plan. Students will then analyze the results and determine if their hypothesis was supported or not. The goal is to gain experience with a formal development process and understand how the scientific method, mathematical reasoning, logic, and algorithmic thinking will generate concrete answers to problems. Graduate students are not permitted to take this course. This class is not available for graduate credit. Prerequisite:    CSC 498 FOR LEVEL U WITH MIN. GRADE OF C
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• CSC 503: Computer Science and Engineering Fundamentals

  4.00 Credits

  Shippensburg University of Pennsylvania

  
  In computer science and engineering, it is essential to have a critical mind to solve problems and build appropriate applications using computer programming. This course is designed for graduate students who need to build a solid background in core computer science skills including: computer programming C and Java, data structures, and computer organization. It will guide students to build their foundation for success in computer science and engineering.
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• CSC 523: High Performance Computing

  3.00 Credits

  Shippensburg University of Pennsylvania

  
  Engages students in the high performance computing. In-depth coverage of techniques for the design and analysis of parallel algorithms and for programming these algorithms on parallel platforms. Covers the principles of parallel algorithm design and different parallel programming models. A broad and balanced coverage of various core topics such as graph algorithms, data-mining algorithms, and a number of algorithms used in numerical and scientific computing applications. Hands-on programming experience using MPI on parallel computers. Real-world applications in this area will be discussed.
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