Spatial data science is a timely topic which has been quickly evolving in recent years, and is rich in applications. This course addresses current needs for the statistical modeling of random patterns and structures in spatial contexts, which arise in multiple fields ranging from geophysical, life and earth sciences, to communication engineering and social network analysis. The course approach relies on computational and statistical tools from stochastic geometry, which is the study of random sets and structures in one or higher dimensions. The course is mainly addressed to undergraduate students in mathematics and statistics, and can also benefit science and engineering students possessing a quantitative background.
| Academic Units | 4 |
| Exam Schedule | Fri May 08 2026 00:00:00 GMT+0000 (Coordinated Universal Time) 09:00-11:00 |
| Grade Type | Letter Graded |
| Department Maintaining | MATH(SPS) |
| Prerequisites |
| Index | Type | Group | Day | Time | Venue | Remark |
|---|---|---|---|---|---|---|
| 70680 | LEC/STUDIO | LE | FRI | 1130-1220 | MAS EC RM2 | |
| 70680 | LEC/STUDIO | LE | WED | 1530-1720 | MAS EC RM2 | |
| 70680 | TUT | T | FRI | 1230-1320 | MAS EC RM2 | Teaching Wk2-13 |
0930
1030
1130
1230
1330
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1530
1630
1730
MH4522
LEC/STUDIO | MAS EC RM2
MH4522
LEC/STUDIO | MAS EC RM2
MH4522
TUT | MAS EC RM2
Teaching Wk2-13
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