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DSCI 521 Data Analysis and Interpretation 3.0 Credits

Introduces methods for data analysis and their quantitative foundations in application to pre-processed data. Covers reproducibility and interpretation for project life cycle activities, including data exploration, hypothesis generation and testing, pattern recognition, and task automation. Provides experience with analysis methods for data science from a variety of quantitative disciplines. Concludes with an open-ended term project focused on the application of data exploration and analysis methods with interpretation via statistical, algorithmic, and mathematical reasoning.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: DSCI 501 [Min Grade: C] (Can be taken Concurrently)

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