Data Science

Courses

DSCI 511 Data Acquisition and Pre-Processing 3.0 Credits

Introduces the breadth of data science through a project lifecycle perspective. Covers early-stage data-life cycle activities in depth for the development and dissemination of data sets. Provides technical experience with data harvesting, acquisition, pre-processing, and curation. Concludes with an open-ended term project where students explore data availability, scale, variability, and reliability.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit

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

DSCI 591 Data Science Capstone I 3.0 Credits

Explores data science in practice as an open-ended team activity. Initiates an in-depth multi-term capstone study applying computing and informatics knowledge in a data science project. Teams work to develop a significant product with advisors from industry and/or academia. Explores data science-related issues and challenges involved in the application domain of the team’s choice. Applies a development process structure for project planning, specification, design, implementation, evaluation, and documentation.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit

DSCI 592 Data Science Capstone II 3.0 Credits

Explores data science in practice as an open-ended team activity. Completes an in-depth multi-term capstone study applying computing and informatics knowledge in a data science project. Teams work to develop a significant product with advisors from industry and/or academia. Explores data science-related issues and challenges involved in the application domain of the team’s choice. Applies a development process structure for project planning, specification, design, implementation, evaluation, and documentation.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: DSCI 591 [Min Grade: C]

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