| 21 Sep | Lecture 1: Introduction Reading: F&L ch. 1 Optional: Maths Tutorials | Lecture 2: Model Building Reading: F&L ch. 2 Optional: CCS R Cheat Sheet | | |
| 28 Sep | Lecture 3: Parameter Estimation | Lecture 4: Parameters and Probabilities 1 | | |
| 5 Oct | Lecture 5: Parameters and Probabilities 2 | Lecture 6: Aggregation across Participants | Tutorial 1 Materials Solutions | |
| 12 Oct | Lecture 7: Model Comparison 1 | Lecture 8: Model Comparison 2 | Tutorial 2 Materials Solutions | |
| 19 Oct | Lecture 9: Concepts | Lecture 10: Categorization | Tutorial 3 Materials Solutions | |
| 26 Oct | Lecture 11: Causality 1 | Lecture 12: Causality 2 | Tutorial 4 Materials Solutions | Released 29 October Materials |
| 2 Nov | Lecture 13: Active Learning 1 | Lecture 14: Active Learning 2 | Q&A | |
| 9 Nov | Lecture 15: Language Acquisition | Lecture 16: Surprisal 1 | Tutorial 5 Materials Solutions | |
| 16 Nov | Lecture 17: Surprisal 2 | Lecture 18: Large-scale Models 1 | Tutorial 6 Materials Solutions | Due 19 November Solutions |
| 23 Nov | Lecture 19 Large-scale Models 2 | Lecture 20: Recap and Q&A | Tutorial 7 Materials Solutions | |