UNIT 0110 h allocated
Supervised learning
- Linear and logistic regression
- KNN
- SVM
- decision trees
← Course catalogue
MACHINE LEARNING / CORE
ML201Machine learning: baselines to reliable decisions
40 h productive allocation16 h learning + 24 h 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: DAT120
Core studio / CPU-friendly local or notebook environment
WHAT YOU SHOULD BE ABLE TO DEMONSTRATE
- Explain the assumptions and failure modes in supervised learning.
- Complete the practical: compare a dummy baseline and three models on one documented split, select using validation only and explain final test errors.
- Defend the resulting benchmark repository with reproducible evidence.
THE SUBJECTS / FOUR CONNECTED UNITS
What you will study.
UNIT 0210 h allocated
Ensembles and features
- Random forests
- gradient boosting and XGBoost
- encoding
- regularisation
UNIT 0310 h allocated
Unsupervised learning
- K-means
- PCA
- anomaly scoring
- cluster interpretation
UNIT 0410 h allocated
Evaluation and selection
- Cross-validation
- nested preprocessing
- tuning budgets
- calibration and error costs
THE TRAINING STUDIO
Make the subject
visible in your work.
Compare a dummy baseline and three models on one documented split, select using validation only and explain final test errors.
Evidence to produce
- Benchmark repository
- model card
- error analysis
- held-out evaluation
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 is the highest test score not a valid model-selection procedure?
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.