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Under construction. This area is a framework being built: most courses have no teaching material yet, and things may change or break. Private self-study. Not an official programme and not recognised by any ministry or school. No qualification, mark or document is issued, and “years 1 to 3” and “advanced” are names of study paths only.

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A18 Neural-network mathematics

Advanced pathA: Advanced appliedplannedabout 180 h (planning estimate)

Planned: syllabus only, no teaching material yet. Nothing on this page can be studied; it describes what the course would cover.

Named in: Advanced applied mathematics pathway

Why this course

Derives backpropagation and separates empirical behaviour from guarantees.

Prerequisites

Required
A09 Mathematics of statistical learning, B06 Multivariable & vector calculus, B19 Numerical linear algebra
Recommended
none
Can be taken at the same time
none
Everything required, transitively (23 courses)
A02, A09, B01, B02, B03, B04, B05, B06, B08, B09, B11, B12, B13, B15, B17, B19, B20, F01, F02, F03, G01, G03, U09
Courses that require this one
E36

Concept-level units

Units follow the syllabus order, as a recommended sequence rather than a gate.

  1. Computational graphs
  2. Backpropagation
  3. Initialization and gradients
  4. Optimization behaviour
  5. Approximation themes
  6. Reliable numerical experiments

Assessable outcome

Derive backpropagation and distinguish empirical behaviour from mathematical guarantees.

Assessment design

  • deeper problem sets
  • reconstruction of an unfamiliar argument
  • advanced source reading
  • cumulative examination or substantial project

cumulative; uses spaced retrieval

Resources

Every title here is candidate, unverified unless marked verified. Titles were suggested while planning. Nobody has checked that they exist, what they cost or how they are licensed.

  • Prince · Understanding Deep Learning
  • Goodfellow et al

Content record

Version
0.0.0
Review
no review of any kind
Provenance
catalogue imported from the owner brief of 29 Oct 2026; no teaching content authored
Known issues
none recorded
Type
course

Bridges and laboratories

  • Laboratory: Computational graphs and backpropagation planned Expose derivatives and numerical checks, not only animations

You and this course

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