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ISYS 7730 Data Analytics 3: In Practice (Spring: 2 )

Course Description

Modern information systems now generate massive volumes of data. Organizations everywhere struggle to aggregate, analyze, and monetize the growing deluge of data. Business Analytics capitalizes on this data by combining statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management. Managers can explore patterns, predict future trends and develop proactive, knowledge-driven decisions that affect all parts of modern organizations. This course provides students with a pragmatic familiarity with the capabilities and limitations of emerging analytics techniques, an introduction to the R statistical computing software, an overview of methods and tools, and a core understanding required to be an intelligent manager, designer and consumer of analytics models.

Instructor(s): Sam Ransbotham

Prerequisites: None

Cross listed with:


Last Updated: 10-Apr-18