Introduces fundamental concepts and methods in data analytics engineering, with a focus on probability, eigenvalues and eigenvectors, cluster analysis, text mining, and time series analysis. Covers modern data structures and computational techniques for data cleaning and wrangling. Prepares students for advanced coursework in data analytics.
Offering history
Term
Sections
Enrolled
Capacity
Full
Open seats/section
Fall 2025
1
134
500
27%
366.0
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 0% · W 0% · Th 0% · F 0%
Common patterns: async (100% of sections)
— in patterns, R means Thursday