Note: Days and times for the live Class, Tutorial and Lab sessions will be shown on the Live Sessions Schedule page on Learn.
| Week start | Study Topics | Lab activity | Small group tutorial activity | Class meeting |
| 1 15/1 | Probability Thinking about Data | Lab 0 (self): Intro to Python and ML packages Lab 1: get started | Course overview and activities Probability Q&A Thinking about Data Q&A | |
| 2 22/1 | Naive Bayes - videos/slides - quiz - answers Decision Trees - videos/slides - quiz - answers | Lab 1 Collaborate: Data Analysis &Visualisation & Multinomial Naive Bayes | Tutorial 1: get started | Naive Bayes Q&A Decision Trees Q&A |
| 3 29/1 | Generation Evaluation | Lab 2: get started | Tutorial 1: Naive Bayes and Feature Engineering | Generalisation and Evaluation Q&A |
| 4 5/2 | Linear Regression Logistic Regression | Lab 2 Collaborate: Decision Trees and Linear Regression | Tutorial 2: get started | Linear Regression Q&A Logistic Regression Q&A |
| 5 12/2 | Optimisation and Regularisation Support Vector Machines I & II | Lab 3: get started | Tutorial 2: Decision Trees and Gaussian Naive Bayes | Optimisation and Regularisation Q&A Support Vector Machines Q&A |
| - | - | - | - | |
| 6 26/2 | Ethics and ML Nearest Neighbour Methods | Lab 3 Collaborate: SVMs, Evaluation | Tutorial 3: get started | Ethics & ML Q&A Nearest Neighbour Q&A |
| 7 4/3 | K-Means Gaussian Mixture Models | Lab 4: get started | Tutorial 3: Logistic Regression | K-Means Q&A Gaussian Mixture Models Q&A |
| 8 11/3 | Principal Components Analysis Hierarchical Clustering | Lab 4 Collaborate: Clustering, PCA and Evaluation | Tutorial 4: get started | PCA Q&A Hierarchical Clustering Q&A |
| 9 18/3 | Neural Networks - videos/slides | Lab 5: get started | Tutorial 4: SVMs and Gaussian Mixture Models | Neural Networks Q&A |
| 10 25/3 | Lab 5 self-study: Neural Networks | Review and Revision Q&A |