MTH (0144) 675 - Big Data Analytics and Regression

Credits: 3.00

Students will learn techniques and tools required for big data analytics. Students will explore: how large, complex datasets interact with different types of regression analysis, scalable computing models, large-scale non-traditional data storage frameworks including graph, key-value, and column-family storage systems; data stream analysis; scalable prediction models and in-memory storage systems.

Prerequisite 1: MTH 601
Free Note: Open only to students in the M.S. in Mathematics.

Course Learning Goals: Students will:

●   Explain and apply the Big Data flow. This will be assessed by Quizzes 1-3 and the mid-term examination.
●   Utilize and apply the Data Analytics lifecycle to Big Data analytics problems. This will be assessed by Quizzes 4-6, the mid-term examination, and the final examination.
●   Apply appropriate techniques and tools to analyze Big Data problems and recognize insights that lead to actionable work items. This will be assessed by Quizzes 7-10 and the final examination.