Exploration of the design and implementation of data structures and algorithms fundamental to computer systems and applications and to software engineering.
Exploration of the design and implementation of data structures and algorithms fundamental to computer systems and applications and to software engineering.
Topics include trees, graphs, basic analysis of algorithmic complexity, fundamental questions of computability, and introduction to the algorithmic basis of intelligent systems. Programming projects.
Metropolitan State was established in 1971, and now serves more than 10,500 students in the metropolitan area as we approach our fiftieth anniversary.
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Metropolitan State University is a comprehensive urban university committed to meeting the higher education needs of the Twin Cities and greater metropolitan population.
The university will provide accessible, high-quality liberal arts, professional, and graduate education to the citizens and communities of the metropolitan area, with continued emphasis on underserved groups, including adults and communities of color.
Within the context of lifelong learning, the university will build on its national reputation for innovative student-centered programs that enable students from diverse backgrounds achieve their educational goals.
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Models, algorithms, recurrences, summations, growth rates. Probabilistic tools, upper and lower bounds; worst-case and average-case analysis, amortized analysis, dynamization. Comparison-based algorithms: search, selection, sorting, hashing. Information extraction algorithms (graphs, databases).
Survey of advanced algorithms and data structures such as heaps and heapsort, quicksort, red-black trees, B-trees, hash tables, graph algorithms, divide and conquer algorithms, dynamic programming, and greedy algorithms. Methods for proving correctness and asymptotic analysis.
This course covers and relates fundamental components of programs. Students use various data structures to solve computational problems, and implement data structures using a high-level programming language.
This course covers the theory and application of commonly used data structures and related algorithms for maintaining them. Emphasis is placed on efficiency, appropriate use, and the creation of encapsulated, object-oriented data structures.
This course presents some fundamental data structures, including lists, stacks, queues, hashes, and binary trees. Students will master a number of algorithms including Mergesort and Quicksort.
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