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Course Criteria
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3.00 Credits
Faculty-directed work on a computer and information sciences project of interest to the faculty member and student. Minimum of 80 clock hours of productive work required. A report of presentation discussing approach, methodology, and results will be submitted upon completion.
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0.00 - 99.00 Credits
No course description available.
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3.00 Credits
Designing client-server application with sockets; traffic analysis; building concurrent and multi-service servers; designing network protocols; measuring and analyzing performance of protocols. Students will complete a number of programming and network analysis experiments during the semester. Background assumed: Data Communication and Networks II or equivalent.
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3.00 Credits
Review of contemporary operating systems (OS), OS design principles and strategies; examination of communication and synchronization protocols; concurrent processes and process scheduling including their statistical analysis; distributed operating systems; client-server computing model; distributed resource management; multiprocessor OS; failure, recovery and fault tolerance; data security; applications. Background assumed: Introduction to Operating Systems or equivalent.
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3.00 Credits
Topics include: time and space complexity; verification of correctness; advanced algorithm design strategies (iterative, divide-and-conquer, greedy methods, dynamic programming, branch-and-bound, etc., with specific examples drawn from sorting, searching, graph theory, matrix and polynomial arithmetic, and cryptography); hard problems and approximation algorithms, with examples such as napsack, bin-packing, and graph coloring problems; introduction to parallel algorithms as time permits. Background assumed: Mathematical Structures and Proof and Data Structures.
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3.00 Credits
Typical topics include: Red-Black trees; AVL trees; B trees; B+ trees; B* trees; tries; splay trees; spatial data structures; self-organizing lists; summation techniques; recurrence relations, including establishing bounds and expanding recurrences; hashing and other complex indices; complexity of searching on various structures. Background assumed: Data Structures.
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3.00 Credits
The course exposes students to a wide range of state-of-the-art research and techniques in the field of computational biology. This is a modern discipline dealing with the discovery and implementation of algorithms facilitating the understanding of biological processes. Various statistical, heuristic, and machine learning methods are used for this purpose, as well as graphical tools to visualize the objects. The course is intended to present some biological problems related to the human genome and the computational methods to resolve them. It will cover an introduction to computational biology, the use of computational methods to search for, classify, analyze, and model protein sequences, i.e. to convert the masses of information from biochemical experiments into useful information.
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3.00 Credits
A variable topics course in computer science. Topics normally not covered in Computer Science or Computer Information Systems undergraduate degree programs but suitable to explore at length at graduate and senior level. Project and a formal presentation are required. Prerequisite: CSIT 341 or equivalent background knowledge and permission of instructor.
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3.00 Credits
The course focuses on the design of CMOS VLSI (Very Large Scale Integrated) chips using integrated circuit cells as building blocks and employing hierarchical design methods. Focus will be on the design of digital systems. Design issues at layout, schematic, logic and RTL levels will be studied. Shareware and freely available design software will be used for laboratory exercises. An overview of VLSI computer-aided design (CAD) tools and theoretical concepts in VLSI architectures will also be discussed. Prerequisite: Completed at least one course in logic design or computer architecture at the undergraduate level.
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3.00 Credits
The course focuses on modern software project development techniques. Topics include Universal Modeling Language (Use Case, Sequence, and Class diagrams), code reusability, design patterns, component development and versioning software. Students will produce a significant, multifaceted software product.
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