Schedule are subject to change
Schedule (Spring 2025)
| Week | Date | Type | Topic | Readings |
|---|---|---|---|---|
| Week 1 | Tue, Jan 21 | Lecture | Course introduction | |
| Thu, Jan 23 | Lab session | Python/anaconda installation, Github account | ||
| Week 2 | Tue, Jan 28 | Lecture | Intro to unsupervised clustering. Low dimensional visualisation and dimensionality reduction | Géron, Chapter 8: PCA Unpingco, Chapter 4.10 |
| Thu, Jan 30 | Lab session | |||
| Week 3 | Tue, Feb 04 | Lecture | Clustering using k-means and Gaussian mixture models | Géron, Chapter 9 Unpingco, Chapter 4.11 |
| Thu, Feb 06 | Lab session | |||
| Week 4 | Tue, Feb 11 | Lecture | Interpreting clustering and hierarchical clustering | Géron, Chapter 9 |
| Thu, Feb 13 | Lab session | |||
| Week 5 | Tue, Feb 18 | Lecture | Building supervised classification models: from data preparation to model evaluation | Géron, Chapters 2 & 3: Performance Measures |
| Thu, Feb 20 | Lab session | |||
| Week 6 | Tue, Feb 25 | Lecture | Classification using K-nearest neighbours and decision trees | Géron, Chapter 6 |
| Thu, Feb 27 | Lab session | |||
| Week 7 | Tue, Mar 04 | Lecture | Classification using naive Bayes and Support Vector Machines | Unpingco, Chapter 2.6.6 Géron, Chapters 5: Linear & nonlinear SVM Classification |
| Thu, Mar 06 | Lab session | |||
| Week 8 | Tue, Mar 11 | Lecture | Data partition, cross-validation and hyperparameter tuning | Géron, Chapter 2: Select and Train a Model; Fine-tune Your Model |
| Thu, Mar 13 | Lab session | Mid-term assessment | ||
| Week 9 | Tue, Mar 18 | SPRING BREAK | ||
| Thu, Mar 20 | SPRING BREAK | |||
| Week 10 | Tue, Mar 25 | Lecture | Reducing predictors using feature transformation and feature selection. Ensemble learning | Géron, Chapter 7 |
| Thu, Mar 27 | Lab session | |||
| Week 11 | Tue, Apr 01 | Lecture | Regression analysis for linear problems | Géron, Chapter 4: Linear Regression, Gradient Descent |
| Thu, Apr 03 | Lab session | |||
| Week 12 | Tue, Apr 08 | Lecture | Polynomial regression and regularised linear models | Géron, Chapter 4: Polynomial Regression, Regularized Linear Models |
| Thu, Apr 10 | Lab session | |||
| Week 13 | Tue, Apr 15 | Lecture | Non-parametric regression models | Géron, Chapter 5: SVM Regression Géron, Chapter 6: Regression |
| Thu, Apr 17 | Lab session | |||
| Week 14 | Tue, Apr 22 | Lecture | Artificial neuron and feedforward neural network | Géron, Chapter 10: From Biological to Artificial Neurons |
| Thu, Apr 24 | Lab session | |||
| Week 15 | Tue, Apr 29 | Lecture | Fine-tuning artificial neural networks | Géron, Chapter 10: Fine-Tuning Neural Network Hyperparameters |
| Thu, May 01 | Reading day | |||
| Week 16 | Tue, May 06 | Lecture | End-term assessment | |
| Thu, May 08 | Reading day |