Detailed Course Information |
Spring 2026 Semester
Feb 05, 2026 |
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| CS 3250 - Data-Driven Product Management |
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Presents a variety of methodologies for gathering data in support of all phases of product management. Studies techniques for instrumentation and experimentation to reduce product risk, including abuse resistance and managing regulatory and reputational risk. Introduces emerging techniques supporting data-driven product management, emphasizing computer science-based techniques that help scale data collection and analysis. Builds analytical competency through a rigorous grounding in data collection and analysis methodology, case studies, and experiential learning with technology companies. Offers students an opportunity to learn how to identify the appropriate method(s) for a given phase and context, reduce bias in data collection, and to confirm and contextualize methodological knowledge by partnering with technology companies to develop data-driven product recommendations.
4.000 Credit hours 4.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Computer Science Department Course Attributes: Computer&Info Sci Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: Undergraduate level DS 3000 Minimum Grade of D- or Undergraduate level MGSC 2301 Minimum Grade of D- |
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