UNIT 016 h allocated
Linear algebra
- Vectors and matrices
- dot products
- projections
- norms and rank
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MATHEMATICS & DATA / CORE
MTH110Mathematics for learning systems
24 h productive allocation9 h 36 m learning + 14 h 24 m training4 units · 1 assessed practical brief
Detailed course plan and training brief. A complete taught course pack is in preparation. The linked foundation module, where shown, is a smaller available resource.
BEFORE YOU BEGIN
A clear starting point.
Prerequisites: AI101
Core studio / CPU-friendly local or notebook environment
WHAT YOU SHOULD BE ABLE TO DEMONSTRATE
- Explain the assumptions and failure modes in linear algebra.
- Complete the practical: implement a least-squares fit and a gradient-descent update on synthetic data; compare numerical and analytic gradients.
- Defend the resulting derivation sheet with reproducible evidence.
THE SUBJECTS / FOUR CONNECTED UNITS
What you will study.
UNIT 026 h allocated
Calculus and optimisation
- Derivatives
- chain rule
- gradients
- learning-rate behaviour
UNIT 036 h allocated
Probability foundations
- Conditional probability
- Bayes rule
- random variables
- expectation
UNIT 046 h allocated
Numerical reasoning
- Floating-point error
- conditioning
- scaling
- finite-difference gradient checks
THE TRAINING STUDIO
Make the subject
visible in your work.
Implement a least-squares fit and a gradient-descent update on synthetic data; compare numerical and analytic gradients.
Evidence to produce
- Derivation sheet
- gradient check
- convergence plot
- units and assumptions
Training brief for supervised delivery. Code, datasets, answer keys and environment acceptance must be completed in the full course pack before delivery is confirmed.
ASSESS THE REASONING
A question you
should be able to answer.
Why can a mathematically correct update still be unstable in a numerical implementation?
Review dimensions
Technical correctness · reproducibility · interpretation of results · failure analysis · individual explanation. Course-level rubric and faculty moderation form part of the final adopted teaching pack.
External reference access, hardware, cloud accounts and paid services are separate. No third-party certification is included by implication.