Big Data Analytics Using Spark

4 credits

This course covers techniques for achieving scalability in data analysis, using tools such as MapReduce, Hadoop, and Spark. Topics include programming Spark using PySpark; identifying the computational tradeoffs in a Spark application; performing data loading and cleaning using Spark and Parquet; modeling data through statistical and machine learning methods, and mitigating bottlenecks that arise in massive parallel computations by using the Spark framework. This is a distance education course. Prerequisites: DSC 255R. Restricted to major codes DS78 and DS79. All other students with graduate standing may be considered as space permits.