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| Old Course Code | Subject Area | Catalogue Number | Long Title | Units | Description |
| IC100 | COGS | 1000 | Minds & Machines: Introduction to Cognitive Science | 2 | Aims to introduce basic issues, concepts, & terminology of cognitive science. Compares & contrasts cognitive architecture of brains & computers. |
| IC206 | COGS | 2000 | Architecture of the Mind: Natural & Artificial | 2 | Aims to introduce basic issues, concepts & terminology of architecture of mind, from neurons to systems. Overview of classical computational approach, perception, central & motor systems from the perspectives of both cognitive psychology & artificial inte |
| IC231 | COGS | 2010 | Laboratory Introduction to Models in Cognitive Science | 2 | Introduction to basic principles & issues related to computational modelling of cognitive, perceptual & linguistic processes in cognitive science. Introduction to neural networks & other modeling frameworks, significance of neural networks for cognitive s |
| IC310 | COGS | 3000 | Language, Thought & Representation | 2 | Aims to provide interdisciplinary treatment of topics in perception, comprehension & production of natural language. |
| IC330 | COGS | 3010 | Human Reasoning & Rationality | 2 | Inductive & deductive validity, fallacies, reasoning processes, role of learning & memory in reasoning & formal models of reasoning. Approached from point of view of case studies of human reasoning & problem solving, issues in epistemology & reasoning as |
| IC400 | COGS | 4000 | Cognitive Science Project Part A | 4 | Individual student research project |
| IC401 | COGS | 4100 | Graduate Certificate Seminar | 2 | Aims to integrate content for the contributing Cognitive Science disciplines through discussion, seminar presentation & written reports. |
| IC408 | COGS | 4021 | Cognitive Computing I | 2 | Artificial neural networks, review of the literature; emphasis on simulation techniques. Aims to provide introduction to research skills in artificial neural networks. |
| IC409 | COGS | 4031 | Cognitive Computing II | 2 | Advanced topics in artificial neural networks, evolutionary computing & cognitive modeling. The subject involves practical & theoretical case studies & an in-depth simulation project. |