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Spring 2018 Semester
Oct 23, 2020
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DS 4100 - Data Collection, Integration, and Analysis
Studies how to collect data from multiple sources and integrate them into consistent data sets. Covers how to use semi-automated and automated classification to integrate disparate data sets; how to parse data from files, XML, JSON, APIs, and structured data stores to construct analyzable data sets that are stored in databases; and how to assess and ensure quality of data. Introduces key concepts of algorithms and data structures, including divide-and-conquer, sorting and selection, and graph traversal and descriptive analysis of data through descriptive statistics and plotting. Analyzes complexity and run-time behavior of programs. Presents approaches for data anonymization and protecting data privacy. Studies data shaping and manipulation techniques for data analysis and the R and Python programming languages.
4.000 Credit hours
4.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Data Science Department

Course Attributes:
NUpath Analyzing/Using Data, Computer&Info Sci

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