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Fall 2017 Semester
Sep 26, 2017
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Information Select the desired Level or Schedule Type to find available classes for the course.

DS 5110 - Introduction to Data Management and Processing
Discusses the practical issues and techniques for data importing, tidying, transforming, and modeling. Offers a gentle introduction to techniques for processing big data. Programming is a cross-cutting aspect of the course. Offers students an opportunity to gain experience with data science tools through short assignments. Course work includes a term project based on real-world data. Covers data management and processing—definition and background; data transformation; data import; data cleaning; data modeling; relational and analytic databases; basics of SQL; programming in R and/or Python; MapReduce fundamentals and distributed data management; data processing pipelines, connecting multiple data management and analysis components; interaction between the capabilities and requirements of data analysis methods (data structures, algorithms, memory requirements) and the choice of data storage and management tools; and repeatable and reproducible data analysis.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Data Science Department

Course Attributes:
Graduate CCIS Data Sci Cert

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

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