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Course Criteria
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4.00 Credits
Fundamental concepts of DBMS. Data modeling, relational models and normal forms. File organization and index structures. SQL, embedded SQL, and concurrency control. Prereq: CIS 315.
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4.00 Credits
Covers central database issues such as access methods, security, tuning, and concurrency control. Examines alternative database models. Prereq: CIS 451/551.
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4.00 Credits
Databases, machine learning, artificial intelligence, statistics, and data visualization. Examines data warehouses, data preprocessing, association and classification rule mining, and cluster analysis. Prereq: CIS 451/551.
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4.00 Credits
Introduction to bioinformatics from a computer science perspective covering algorithms for basic operations such as sequence comparison and phylogenetic inference on existing databases.
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4.00 Credits
Solving scientific problems with high-performance computers; algorithms, languages, and software used in scientific computing and visualization. Group projects on current research in physics, chemistry, biology, and other sciences. Prereq: CIS 314, 422.
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4.00 Credits
Lexical analysis, parsing, attribution, code generation. Prereq: CIS 314, 425 or 624. CIS 420/520 strongly recommended.
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4.00 Credits
Basic themes, issues, and techniques of artificial intelligence, including agent architecture, knowledge representation and reasoning, problem solving and planning, game playing, and learning. Prereq: CIS 315.
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4.00 Credits
Addresses ethical issues and social impacts of computing. Topics include crime, hacking, intellectual property, privacy, software reliability, employment, and worldwide networks. Prerequisites to graduate-level CIS courses are intended as guidelines. Students who are uncertain about eligibility for enrollment in a course are encouraged to consult the instructor.
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1.00 - 3.00 Credits
Thesis
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1.00 - 3.00 Credits
Research:[Topic
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