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| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
CS 4371 Erick Skorupa Parolin | |||||
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| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
CS 4371 Erick Skorupa Parolin | |||||
A- | |||||
Introduction to Big Data Management and Analytics
CS 4371
Erik Jonsson School of Engineering and Computer Science
This course focuses on scalable data management and mining algorithms for analyzing very large amounts of data (i.e., Big Data). Included topics are: Mapreduce, NoSQL systems (e.g., key-value stores, column-oriented data stores, stream processing systems), association rule mining, large scale supervised and unsupervised learning, and applications including recommendation systems, web and big data security. 3 credit hours.
Prerequisites: (CS 2336 or CS 2337) and CS 4347.
Offering Frequency: Each year
Grades: 525
Median GPA: A-
Mean GPA: 3.434
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Introduction to Big Data Management and Analytics
CS 4371
Erik Jonsson School of Engineering and Computer Science
This course focuses on scalable data management and mining algorithms for analyzing very large amounts of data (i.e., Big Data). Included topics are: Mapreduce, NoSQL systems (e.g., key-value stores, column-oriented data stores, stream processing systems), association rule mining, large scale supervised and unsupervised learning, and applications including recommendation systems, web and big data security. 3 credit hours.
Prerequisites: (CS 2336 or CS 2337) and CS 4347.
Offering Frequency: Each year
Grades: 525
Median GPA: A-
Mean GPA: 3.434
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