AMATH 345Data-Driven Mathematical Models
- Units
- 0.50
- Faculty
- Mathematics
- Subject
- Applied Mathematics
When it runs
- F24
- W25
- S25
- F25
- W26
- S26
- F26
- W27
- S27
Ran in 2 of the last 7 terms. Winter 2027: not on the schedule. Spring 2027: schedule not out yet.
An introduction to data-driven mathematical methods for modelling and prediction of complex systems in science, medicine, and technology. Topics include singular value decomposition, sparsity and compressed sensing, calibration and parameter inference for differential equation models, as well as neural networks and data-driven methods for dynamical systems. Throughout the course, students will learn to use modern data science methods and apply recent advances in data-driven methods to a wide range of applications.
Prerequisites
- Complete all of the following
- Must have completed at least 1 of the following:
- Must have completed at least 1 of the following:
- Must have completed at least 1 of the following:
- PHYS267 - Probability, Statistics, and Data Analysis for Physics and Astronomy (0.50)
- STAT202 - Introductory Statistics for Scientists (0.50)
- STAT206 - Statistics for Software Engineering (0.50)
- STAT221 - Statistics (Non-Specialist Level) (0.50)
- STAT231 - Statistics (0.50)
- STAT241 - Statistics (Advanced Level) (0.50)
Antirequisites
None listed.
Leads to
No course lists it as a requisite.
Fall 2026 sections
| Section | Class | Enrolled | Meets |
|---|---|---|---|
| LEC 001 | 6758 | 46 / 60 | MW 11:30–12:50 |
Check it elsewhere for Fall 2026
- Undergraduate Calendar, 2026–27The official entry
- Requirements for Fall 2026Waterloo’s requisite checker
- Schedule of Classes, Fall 2026Instructors, rooms, live seats
- Quest Class SearchWhere you enrol
- Course outlinesSyllabi from past terms (UW login)
- UW FlowStudent ratings and reviews
- WClassesPast sections back to 2004, and who taught them
Calendar versions
Undergraduate Calendar
- 2025–26
- 2026–27 (shown here)
- 2019–20 and earlier on ucalendar