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AMATH 449Neural Networks

Units
0.50
Faculty
Mathematics
Subject
Applied Mathematics
Cross-listed
CS 479

When it runs

  1. F24
  2. W25
  3. S25
  4. F25
  5. W26
  6. S26
  7. F26
  8. W27
  9. S27

Ran in 3 of the last 7 terms. Winter 2027: scheduled, 4 lecture sections. Spring 2027: schedule not out yet.

An introduction to neural network methods, with some discussion of their relation to neuroscience. Simple neuron models and networks of neurons. Training feedforward networks. Backpropagation of errors and stochastic gradient descent. Unsupervised learning methods. Recurrent neural networks. Convolutional neural networks. Continuous time models. Adversarial attacks. Advanced topics may include neural engineering, biologically plausible learning methods.

Prerequisites

  • Complete 1 of the following
    • Must have completed at least 1 of the following:
      • STAT230 - Probability (0.50)
      • STAT240 - Probability (Advanced Level) (0.50)
    • Earned a minimum grade of 60% in each of the following:
      • STAT206 - Statistics for Software Engineering (0.50)

Corequisites

  • Completed or concurrently enrolled in at least 1 of the following:
    • AMATH242 - Introduction to Computational Mathematics (0.50)
    • CS335 - Computational Methods in Business and Finance (0.50)
    • CS370 - Numerical Computation (0.50)
    • CS371 - Introduction to Computational Mathematics (0.50)

Antirequisites

None listed.

Leads to

No course lists it as a requisite.

Fall 2026 sections

Enrolment from UW Open Data, which can trail Quest by up to two days. Instructors and rooms: Schedule of Classes.
SectionClassEnrolledMeets
LEC 001676125 / 25MW 14:30–15:50
LEC 002676224 / 25MW 16:00–17:20
TST 101677349 / 50Oct 22 08:30–10:20

Winter 2027 sections

Enrolment from UW Open Data, which can trail Quest by up to two days. Instructors and rooms: Schedule of Classes.
SectionClassEnrolledMeets
LEC 00163550 / 25MW 10:00–11:20
LEC 00264490 / 25MW 14:30–15:50
LEC 00385040 / 25MW 16:00–17:20
LEC 701241725 / 9999Online or by arrangement
TST 10164150 / 75Feb 23 19:00–20:50

Reviewed on UW Flow

67% liked it63% easy100% useful

From 3 ratings and 2 comments on UW Flow. The most helpful comments, quoted as written, without names. Read them all on UW Flow.

  • Useful intro to Neural Networks and their history, UWaterloo needs a Neural Networks II course or a separate LLM course though given the progress in last ~5 years

    Jul 2026 · liked itOn UW FlowRemove this

  • Neural Networks is just not something I'm interested in, but had to take this class to full fill my degree requirements. The assignments were mostly a mix bag, the math parts were straight forward to do, but I did struggle on all the coding sections. Professor Mohamed Hibat-Allah was ok when I took it, he seemed really sweet but did struggle trying to be clear. The concepts were cool to just know of and how they work

    Mar 2026 · didn’t like itOn UW FlowRemove this

Check it elsewhere for Fall 2026

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