ADS-5064: Foundations of Data Science

Description: Fundamental principles and concepts in data science in the context of the end-to-end data science project life cycle. History and evolution of data science. Data science projects in commercial and research settings. Foundational concepts in statistics and machine learning: data and algorithmic modeling, bias-variance tradeoff, supervised and unsupervised learning, training, testing, and validation, experimentation and causation. Principles of data processing: data storage and data formats, data engineering, data quality and integration, data visualization and summarization. The practice of data science: translating real-world problems into data solutions, ethical data decisioning, planning, overseeing, and executing data projects, data science tools, integrating data science solutions. Pre: Graduate standing.

Pathways: N/A

Course Hours: 3 credits

Corequisites: N/A

Crosslist: N/A

Repeatability: N/A