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Dec 26, 2024
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DSBA 6190 - Cloud Computing for Data Analysis
Introduction to the basic principles of cloud computing for data-intensive applications. Focuses on parallel computing using Google’s MapReduce paradigm on Linux clusters, and algorithms for large-scale data analysis applications in web search, information retrieval, computational advertising, and business and scientific data analysis. Students read and present research papers on these topics, and implement programming projects using Hadoop, an open source implementation of Google’s MapReduce technology, and related NoSQL technologies for analyzing unstructured data.
Credit Hours: (3)
Restriction(s): Familiarity with Java, Unix, Data Structures and Algorithms, Linear Algebra, and Probability and Statistics; good programming skills; and a solid mathematical background.
Prerequisite(s): ITCS 6114 or permission of department.
Cross-listed Course(s): ITCS 6190 and ITCS 8190
Most Recently Offered (Day): Spring 2020, Spring 2017
Most Recently Offered (Evening): Fall 2020, Fall 2019, Spring 2019
Schedule of Classes
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