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Course Criteria
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3.00 Credits
This course is an introduction to knowledge-based systems. Basic concepts, characteristics, architectures, and tools will be studied. Major paradigms for synthesis and analysis class systems, and exact and inexact reasoning systems will be discussed. Computational and knowledge engineering issues will be treated by case studies and there will be programming practice.
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3.00 Credits
This course is an introduction to robotics on a technical level. The history of robotics, computer-aided manufacturing, robot components, sensors, programming systems, applications, and future implications of robotics technology will be studied. There will be hands-on experience with a robot.
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3.00 Credits
This course is an introduction to artificial intelligence and heuristic programming techniques. Search strategies, games, heuristic mechanisms, and automated deduction will be studied. There will be programming practice. For graduate credit, a student will be required to write a term paper or execute a project which reflects deeper investigation of the topics covered in the course.
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3.00 Credits
This course provides students with a broad introduction to machine learning, datamining, and statistical patter recognition. Students will study data exploration, decision-tree, K-nearest, neighborhoods, linear regression, logistic regression, support vector machines, neural networks, ensemble learning, clustering, dimensionality reduction evaluations. Students will be required to build predictive models based on machine algorithms. For graduate credit a student will be required to write a term paper or execute a project which reflects deeper investigation of the topics covered in the course.
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3.00 Credits
This course is a study of the principles of software engineering and various programming methodologies as applied to the development of large, complex software systems. Top-down, structured design and programming will be emphasized. There will be practice in the construction of a large software system. This course is usually offered in the Fall. This is a programming intensive course.
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3.00 Credits
This course will introduce the students to the current theoretical models and approaches used in the design, construction, and management of large, complex systems with long life cycles. Topic areas include requirements specification, design, configuration management, technical reviews, quality assurance, testing, and metrics. Case studies will be undertaken to compare the various approaches.
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3.00 Credits
This course is an introduction to natural language processing in Computer Science. There will be a review of elementary text, tree, and graph processing, and an introduction to syntactic and semantic processing. For syntax, Backus-Naur form grammars, sentence generation/recognition, augmented transition networks, and parsing strategies will be studied. For semantics, case grammar theory, and parsing strategies will be studied. There will be case studies of current systems as well as programming practice. For graduate credit, a student will be required to write a term paper or execute a project.
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3.00 Credits
This course is an introduction to the methods and techniques involved in translating high-level languages, such as "C," into executable machine code. Lexical scanning, parsing, symbol table construction, object code generation, and optimization will be studied and a compiler will be written. For graduate credit, a student will be required to write a term paper or execute a project which reflects deeper investigation of the topics covered in the course.
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3.00 Credits
This course is an introduction to the methods and techniques involved in translating high-level languages, such as "C," into executable machine code. Lexical scanning, parsing, symbol table construction, object code generation, and optimization will be studied and a compiler will be written. For graduate credit, a student will be required to write a term paper or execute a project which reflects deeper investigation of the topics covered in the course.
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3.00 Credits
This course is an introduction to parallel computing, a rapidly growing area of computer science. Principles of parallel computer architecture and parallel algorithms for various applications will be studied. There will be practice in parallel programming.
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