Approved by: Graduate Council
Implementation Date: Fall 2013
Note: Deletions are strikethroughs. Insertions are underlined.
Catalog Copy
ITCS 6190. Cloud Computing for Data Analysis. (3) Cross-listed as ITCS 8190. Prerequisites: ITCS 6114 or permission of instructor. Familiarity with Java, Unix, Data structures and Algorithms, Linear Algebra, and Probability and Statistics is expected. Students should have good programming skills and a solid mathematical background. This course will introduce the basic principles of cloud computing for data-intensive applications. It will focus 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 will 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. (Spring).
ITCS 8190. Cloud Computing for Data Analysis. (3) Cross-listed as ITCS 6190. Prerequisites: ITCS 8114 or permission of instructor. Familiarity with Java, Unix, Data structures and Algorithms, Linear Algebra, and Probability and Statistics is expected. Students should have good programming skills and a solid mathematical background. This course will introduce the basic principles of cloud computing for data-intensive applications. It will focus 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 will 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. (Spring).