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Course Criteria
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4.00 Credits
The design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures and on measures of algorithmic efficiency. Sorting (heapsort, mergesort, quicksort), searching, graph algorithms. Experimental analysis of algorithms also emphasized. Use of computer required. Prerequisite: CMPSCI 250.
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4.00 Credits
In this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semester-long team project in which a software development project is carried through all the stages of the software life cycle. Topics in this course include requirements analysis, specification, design, abstraction, programming style, testing, maintenance, communication, teamwork, and software project management. Particular emphasis is placed on communication and negotiation skills and on designing and developing maintainable software. This course satisfies the Integrative Experience requirement for BS-CMPSCI and BA-CMPSCI majors. Use of computer required. Several written assignments, in-class presentations, exams, and a term project.
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3.00 Credits
In this course we examine the important problems in Usability, Human Computer Interaction, User Interfaces, and Human Centered Computing. We will examine elements of HCI history, understanding human capabilities, HCI design, several methods for prototyping user interfaces, and new applications and paradigms in human computer interaction.
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3.00 Credits
The World Wide Web was proposed originally as a collection of static documents inter-connected by hyperlinks. Today, the web has grown into a rich platform, built on a variety of protocols, standards, and programming languages, that aims to replace many of the services traditionally provided by a desktop operating system. This course will study core technologies, concepts, and techniques behind the creation of modern web-based systems and applications.
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3.00 Credits
This introductory computer vision class will address fundamental questions about getting computers to "see" like humans. We investigate questions such as -What is the role of vision in intelligence? -How are images represented in a computer? -How can we write algorithms to recognize an object? -How can humans and computers "learn to see better" from experience? We will write a number of basic computer programs to do things like recognize handwritten characters, track objects in video, and understand the structure of images.
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4.00 Credits
The design and operation of modern computer operating systems. Review of capabilities of typical computer hardware. Topics include command language interpreter (the shell), processes, concurrency, inter-process communication, linking and loading, memory management, transactions, file systems, distributed systems, security, and protection. Programming projects in Java and C.
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3.00 Credits
The Course explores key concepts of artificial intelligence, including problem solving, state-space representation, heuristic search techniques, game playing, knowledge representation, logical reasoning, automated planning, reasoning under uncertainty, decision theory and machine learning. We will examine how these concepts are applied in the context of several applications.
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3.00 Credits
Computing has become data-driven, and databases are now at the heart of commercial applications. The purpose of this course is to provide a comprehensive introduction to the use of data management systems within the context of various applications. Some of the covered topics include application-driven database design, schema refinement, implementation of basic transactions, data on the web, and data visualization. This course counts as a CS Elective toward the CMPSCI major (BA/BS).
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3.00 Credits
In this course we peel away the layers of abstraction and look at how switches become logic circuits, how logic circuits do math, and how programs really execute. We will wire up some simple examples of logic, move on to programming a minimalist simulation of a computer, and gradually build up to the point where we can appreciate how a C program is translated into machine code and what really happens when it executes. We will also see the impact of hidden acceleration mechanisms like caches, pipelines, and branch predictors.
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1.00 - 18.00 Credits
University of Massachusetts Amherst has not provided a description for this course
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