02-513 Algorithms and Data Structures for Scientists

12 units, Carnegie Mellon University

Introduction to design and analysis of algorithms and data structures. Emphasis placed on techniques that are useful for the analysis of scientific data. Topics include dynamic programming, linear programming, network flows, local and heuristic search, and randomization. NPcompleteness and approximation algorithms will also be covered. Data structures discussed will include balanced trees, priority queues, trees for geometric data, string data structures, and hashing. Minimal previous algorithmic knowledge is assumed. Classwork may include programming assignments, but strong programming skills not required. This course is not open to CS majors.

Prerequisites: none listed

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