Keywords: data structures
Displaying 1-11 of 11 results.
Advanced Algorithms, Fall 1999
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Abstract: A first-year graduate course in algorithms. Emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Data structures. Network flows. Linear programming. Computational geometry. Approximation algorithms.
Advanced Algorithms, Fall 2001
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| Type: | Course Related Materials |
Abstract: A first-year graduate course in algorithms. Emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Data structures. Network flows. Linear programming. Computational geometry. Approximation algorithms. Alternate years.
Advanced Algorithms, Fall 2005
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| Type: | Course Related Materials |
Abstract: This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic ... More »
Computer Graphics, Fall 2003
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| Type: | Course Related Materials |
Abstract: Introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial ... More »
Foundations of Software Engineering, Fall 2000
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| Type: | Course Related Materials |
Abstract: Foundations subject in modern software development techniques for engineering and information technology. Covers the design and development of component-based software (using C# and .NET); data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web ... More »
Introduction to Computers and Engineering Problem Solving, Fall 2002
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| Type: | Course Related Materials |
Abstract: This course presents fundamental software development and computational methods for engineering and scientific applications. Object-oriented software design and development is the focus of the course. Weekly programming problems cover programming concepts, graphical user interfaces, numerical methods, ... More »
Introduction to Computers and Engineering Problem Solving, Fall 2005
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| Type: | Course Related Materials |
Abstract: This course teaches fundamental software development and computational methods for engineering, scientific and managerial applications. Emphasis is focused on object-oriented software design and development. Assignments cover programming concepts, graphical user interfaces, numerical methods, data structures, ... More »
Introduction to Computers and Engineering Problem Solving, Spring 2005
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| Type: | Course Related Materials |
Abstract: This course examines fundamental software development and computational methods for engineering, scientific and managerial applications. Emphasis is placed on object-oriented software design and development. Students engage in active learning using laptop computers (available on loan). Assignments cover ... More »
Java Preparation for 6.170, January (IAP) 2006
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| Type: | Course Related Materials |
Abstract: This course focuses on introducing the language, libraries, tools and concepts of Java®. The course is specifically targeted at students who intend to take 6.170 in the following term and feel they would struggle because they lack the necessary background. Topics include: Object-oriented programming, ... More »
Project Overview - CS 61B Data Structures Fall 2007
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| Type: | Course Related Materials |
Abstract: Project Overview. From CS 61B: Data Structures - Fall 2007. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for ... More »
Randomized Algorithms, Fall 2002
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| Type: | Course Related Materials |
Abstract: Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest ... More »
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