CCS: Schedule

This the weekly plan for the course. It is distinct from the official timetable showing when and where specific teaching activities take place. When lecture slides are available, they will be linked from the lecture title.

See the CCS Reading List for a full list of obligatory and recommended readings for the course.

Please note this is draft, and some lecture content may still change.

W/CMonday LectureThursday LectureTutorialsAssignment
21 SepLecture 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 SepLecture 3: Parameter Estimation 
Reading: F&L ch. 3		Lecture 4: Maximum Likelihood Estimation
Reading: F&L ch. 4 
Optional: Maths Tutorials		  
5 OctLecture 5: Bayesian Estimation 1
Reading: F&L ch. 6		Lecture 6: Bayesian Estimation 2
Reading: F&L ch. 6		Tutorial 1: Basic Model Building
Solutions		 
12 OctLecture 7: Aggregation across Participants
Reading: F&L ch. 5		Lecture 8: Model Comparison
Reading: F&L ch. 10		Tutorial 2: Parameter Estimation
Solutions		 
19 OctLecture 9: Concepts
Reading: Tenenbaum (2000)		Lecture 10: Categorization
Reading: Battleday et al. (2020)		Tutorial 3: Model Comparison
Solutions		 
26 OctLecture 11: Causality 1Lecture 12: Causality 2Tutorial 4
Solutions		Released 29 October
Materials
2 NovLecture 13: Active Learning 1Lecture 14: Active Learning 2Q&A 
9 NovLecture 15: Language AcquisitionLecture 16: Surprisal 1Tutorial 5
Solutions		 
16 NovLecture 17: Surprisal 2Lecture 18: Large-scale Models 1Tutorial 6
Solutions		Due 19 November Solutions
23 NovLecture 19 Large-scale Models 2Lecture 20: Recap and Q&ATutorial 7
Solutions		 
License
All rights reserved The University of Edinburgh