DATABASES FOR BIG DATA
Examines the basic concepts and practices of big data and distributed analytics computing. The course covers the challenges that arise when the size of data outgrows the limits of traditional data-analytics systems, "the new challenges big data computing introduces and the evolution of the big data ecosystem. Topics include Hadoop, MapReduce, related software, and enhanced approaches such as Spark and big data machine learning. The course is intended for students studying data science, computer science, mathematics or statistics. Three hours lecture per week. Prerequisite: DATASCI.110 and COMPSCI.357; and MATH.240 or MATH.241.