CDS 421: Computational Data Science
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Course Information from the University Catalog
Credits: 3
Covers the governing framework of data science for storing and processing big data in a distributed computer environment using simple programming models. Includes a comprehensive selection of tools from Hadoop, MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, Kafka. Students are expected to complete several computer projects using these cyber packages. Limited to three attempts.
Recommended Prerequisite: CDS 251 or equivalent computer programming language, and knowledge of computer operating system, or permission of instructor.
Schedule Type: Lecture
Grading:
This course is graded on the Undergraduate Regular scale.
This course is graded on the Undergraduate Regular scale.
