CIVE 7100 — Time Series and Geospatial Data Sciences
4 semester hoursGraduateLecturetypical days: MBostonOnlineTraditionalVideo Streaming
Offers an interdisciplinary course covering the fundamentals of time series and spatial statistics with applications in engineering, science, and business. Introduces analysis and forecasting methods for time series, spatial, and spatiotemporal data. Discusses classical time or frequency domain methods, as well as recent techniques motivated from computer science, physics, statistics, or engineering. Case studies relate to ongoing research and to real-world examples. A demo project is selected by the instructor based on discussion with individual students. A computer-based final project can be tailored to student interests in environmental engineering, sustainability sciences, security threat assessments, social sciences, business, or management science and finance. Requires undergraduate probability and statistics (CIVE 3464 or equivalent); background in programming languages such as MATLAB or R helpful but not required.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2023 | 1 | 29 | 35 | 83% | 6.0 |
| Spring 2026 | 2 | 19 | 45 | 42% | 13.0 |
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 60% · T 33% · W 0% · Th 0% · F 33%
Common patterns: M (60% of sections), TF (33% of sections), async (6% of sections) — in patterns, R means Thursday
Professors
Fall
- Auroop Ganguly (100% of students) · reviews
Spring
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (CIVE course descriptions) · Student reviews on RateMyHusky · All CIVE courses · Plan it at numap.app