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Course Criteria
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3.00 Credits
Introduces students to the principal activities involved in developing high-quality software systems. Topics include: requirements analysis, formal specification methods, process definition, software design, and risk management.
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3.00 Credits
The current best testing and analysis practices; emerging new approaches, going beyond the testing of programs to include the testing and analysis of all software artifacts across the lifecycle. Prerequisite: CMPSCI 320.
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3.00 Credits
This course examines the structure of modern computer systems. We explore hardware and technology trends that have led to current machine organizations, then consider specific features and their impact on software and performance. These may include superscalar issue, caches, pipelines, branch prediction, and parallelism. Midterm and final exams, individual projects, homework, in-class exercises. Prerequisites: CMPSCI 535 or equivalent.
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3.00 Credits
Covers topics such as the relational model, query languages, database design; storage and indexing, query processing and optimization, transaction management; XML data management; information integration; data stream systems; database security.
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3.00 Credits
Basic and advanced techniques for text-based information systems, including retrieval models, indexing and text representation, browsing and query formulation, data-intensive computing approaches, evaluation, and issues surrounding implementation. The course will include a substantial project such as implementation of major elements of search engines and applications.
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3.00 Credits
This course provides an in-depth examination of the fundamental principles of information assurance: authentication, integrity, confidentiality of distributed systems, network security, malware, privacy, intrusion detection, intellectual property, and protection. Prerequisite: CMPSCI 460 (Introduction to Computer and Network Security), or 466 (Applied Cryptography).
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3.00 Credits
An in-depth examination of principles of distributed operating systems. Topics include processes and threads, concurrent programming, distributed interprocess communication, distributed process scheduling, shared virtual memory, distributed file systems. MACH. Familiarity with an undergraduate course on operating systems (CMPSCI 377 or equivalent) is helpful.
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3.00 Credits
In-depth introduction to Artificial Intelligence concentrating on aspects of intelligent agent construction. Topics include: situated agents,advanced search and problem-solving techniques, principles of knowledge representation and reasoning, reasoning under uncertainty, perception and action, automated planning, and learning.
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3.00 Credits
This course will cover Bayesian and Markov networks and their dynamic and relational extensions; exact and approximate inference methods; estimation of both the parameters and structure of graphical models.
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3.00 Credits
Introduces and explores methods that permit programs to learn. Topics include: knowledge acquisition, learning from examples, generalization and specialization, discovery systems, theory formation, connectionist learning, genetic algorithms, macro learning, language learning, explanation-based learning, and computational learning theory.
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