CSIS 44517 Big Data

An introduction to the design of data-intensive, reliable, scalable, and maintainable systems. Includes an introduction to current and relevant tools, technologies, design principles, and frameworks. This may include concepts such as parallel programming, distributed computing, distributed file systems, MapReduce, regular expressions, and the ingesting and processing of data at rest and data in motion. Tools used may include Hadoop, HDFS, Pig, Hive, Spark, Storm, Kafka, Mahout, MLlib, etc. Undergraduate prerequisites: MATH 17230 or MATH 17316, both with a grade of C or better and CSIS 44242 with a grade of C or better. Graduate prerequisite: CSIS 44542 with a grade of B or better, or concurrent enrollment in CSIS 44542, or consent of instructor. (F)

Credits

3