Capstone course in which students will develop and execute a project involving real-world data. Projects will include: formulation of a question to be answered by the data; collection, cleaning and processing of data; choosing and applying a suitable model and/or analytic method to the problem; and communicating the results to a non-technical audience.
At the end of this course, students will be able to demonstrate their knowledge, skills and abilities (KSAs) to develop and execute a data science project using real-world data and effectively communicate their results to a non-technical audience.
Program-specific student learning outcomes: Students will be able to
- Formulate a research question, problem or hypothesis that can be answered or tested using real-world data;
- Collect and manage data to devise solutions to their research question, problem or hypothesis;
- Select, apply and evaluate models, tools and methods to address their research question, problem or hypothesis;
- Interpret and assess their results and evaluate the limitations of their findings;
- Prepare a professional report of their work and effectively communicate their findings to a non-technical audience.
Prerequisites: DS 700: Foundations of Data Science, DS 705: Statistical Methods, DS 710: Programming for Data Science, DS 715: Data Warehousing, DS 730: Big Data: High-Performance Computing, DS 735: Communicating About Data, DS 740: Data Mining, DS 745: Visualization and Unstructured Data Analysis, DS 775: Prescriptive Analytics
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