Note:ÌýThe tables below list all undergraduate AMATH courses and the terms in which they are normally offered.
For up-to-date information on which courses are offered in which terms, please always check .
Fall term = F
Winter term = W
Spring term = S
|
Course |
Term |
Title |
Cross-Listing |
|---|---|---|---|
| AMATH 231 | F, W, S | Calculus 4 | ~ |
| AMATH 242 | W, S | Intro to Computational Mathematics | CS 371 |
| AMATH 250 | F, W, S | Introduction to Differential Equations | ~ |
| AMATH 251 | F | Introduction to Differential Equations (Advanced Level) | ~ |
| AMATH 271 | F | Introduction to Theoretical Mechanics | ~ |
|
|
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| AMATH 331 | F, W | Applied Real Analysis | PMATH 331 |
| AMATH 332 | W, S | Applied Complex Analysis | PMATH 332 |
| AMATH 333 | F | Calculus on Manifolds for Applied Mathematics and Physics | ~ |
| AMATH 342 | F, W | Computational Methods for DEs | ~ |
| AMATH 343 | F | Discrete Models in Applied MathematicsÌý | ~ |
| AMATH 345 | F | Data-Driven Mathematical Models | ~ |
| AMATH 350 | F, W | Differential Equations for Business and Economics | ~ |
| AMATH 351 | F, S | Ordinary Differential Equations 2 | ~ |
| AMATH 353 | W, S | Partial Differential Equations 1 | ~ |
| AMATH 361 | W | Continuum Mechanics | ~ |
| AMATH 362 | W (even) | Mathematics of Climate Change | ~ |
| AMATH 373 | W | Quantum Theory 1 | ~ |
| AMATH 382 | W (even) | Computational Modelling of Cellular Systems | BIOL 382 |
| AMATH 383 | W (odd) |
Introduction to Mathematical Biology |
~ |
| AMATH 390 | F (odd) |
Mathematics and MusicÌý |
~ |
| AMATH 391 | F (odd) | Fourier to Wavelets | ~ |
|
|
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| AMATH 442 | F | Computational Methods for PDEs | ~ |
| AMATH 445 | W | Scientific Machine Learning | AMATH 645 |
| AMATH 449 | F, W | Neural Networks | CS 479, CS 679 |
| AMATH 451 | W | Intro to Dynamical Systems | ~ |
| AMATH 453 | F (odd) | Partial Differential Equations 2 | ~ |
| AMATH 455 | W | Control Theory | ~ |
| AMATH 456 | F | Calculus of Variations | ~ |
| AMATH 463 | F | Fluid Mechanics | ~ |
| AMATH 473 | F | Quantum Theory 2 | PHYS 454 |
| AMATH 474 | W | Quantum Theory 3: Quantum Information and Foundations | PHYS 484 |
| AMATH 475 | W | Intro to General Relativity |
PHYS 476 |
| AMATH 477 | F (odd) | Introduction to Applied Stochastic Processes | ~ |
| AMATH 495 | ~ | Reading Course | ~ |
Current Topics Courses
AMATH 495/900
- Introduction to the Mathematics of Deep Learning (next scheduled offering is Winter 2026)
- Instructor: Professor Jun Liu
- This course aims to give a theoretical introduction to the mathematics of deep learning. It is open to both upper-year undergraduate and graduate students. It is particularly suited for students with a strong background in advanced calculus, linear algebra, and introductory probability or statistics who are interested in the theoretical aspects of deep learning. Self-contained notes will be provided whenever possible, along with supplementary reading materials as needed.
- Tentative topics include:
- Introduction to learning with neural networks
- Approximation theory: Density, approximation degree, lower and upper bounds, benefits of depth, the curse of dimensionality
- Optimization theory: Gradient descent, accelerated gradient descent, stochastic gradient descent, convergence analysis, avoidance of saddle points
- Generalization theory: Generalization bounds, VC-dimension, Rademacher complexity, PAC-Bayes bounds, rethinking the generalization of deep neural networks
- Questions regarding the course can be directed to the instructor Professor Jun Liu (j.liu@uwaterloo.ca).