heathermiller · September 25, 2016 13:05
diff --git a/CS4240.txt b/CS4240.txt
 CS 6240: Parallel Data Processing

 This course covers techniques for managing and analyzing very large data sets,
 with an emphasis on approaches that scale out effectively as more compute nodes
 are added. Principles of distributed data management and strategies for
 problem-driven data partitioning are introduced through a selection of design
 patterns from various application domains, including graph analysis, databases,
 text processing, and data mining. Coursework includes hands-on programming
 experience with modern big-data processing technology such as MapReduce, Spark,
 HBase, and Cloud Computing. (This selection is subject to change as technology
 evolves.)

 Pre-reqs: CS 5800 (Algorithms) or CS 7800 (Advanced Algorithms)
	CS 6240: Parallel Data Processing

	This course covers techniques for managing and analyzing very large data sets,
	with an emphasis on approaches that scale out effectively as more compute nodes
	are added. Principles of distributed data management and strategies for
	problem-driven data partitioning are introduced through a selection of design
	patterns from various application domains, including graph analysis, databases,
	text processing, and data mining. Coursework includes hands-on programming
	experience with modern big-data processing technology such as MapReduce, Spark,
	HBase, and Cloud Computing. (This selection is subject to change as technology
	evolves.)

	Pre-reqs: CS 5800 (Algorithms) or CS 7800 (Advanced Algorithms)