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Elementary Data Structures
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In this course, the student will learn the theoretical and practical aspects of algorithms and Data Structures. The student will also learn to implement Data Structures and algorithms in C/C++, analyze those algorithms, and consider both their worst-case complexity and practical efficiency. Upon successful completion of this course, students will be able to: Identify elementary Data Structures using C/C++ programming languages; Analyze the importance and use of Abstract Data Types (ADTs); Design and implement elementary Data Structures such as arrays, trees, Stacks, Queues, and Hash Tables; Explain best, average, and worst-cases of an algorithm using Big-O notation; Describe the differences between the use of sequential and binary search algorithms. (Computer Science 201)

Subject:
Applied Science
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
Network Optimization
Conditional Remix & Share Permitted
CC BY-NC-SA
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15.082J/6.855J/ESD.78J is a graduate subject in the theory and practice of network flows and its extensions. Network flow problems form a subclass of linear programming problems with applications to transportation, logistics, manufacturing, computer science, project management, and finance, as well as a number of other domains. This subject will survey some of the applications of network flows and focus on key special cases of network flow problems including the following: the shortest path problem, the maximum flow problem, the minimum cost flow problem, and the multi-commodity flow problem. We will also consider other extensions of network flow problems.

Subject:
Applied Science
Business and Communication
Computer Science
Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Orlin, James
Date Added:
09/01/2010