KOGS2001 Cognitive Modeling (5 cr)
Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Faculty of Information Technology
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028
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Cognitive Modeling
Description
Content
This course explores the computational principles of cognition and intelligence in human beings and machines, focusing on how to build models that think and act like people in the context of human-computer interaction.
Completion methods:
The course is completed via weekly assignments, which are supported by video lectures, interactive notebooks, and instructions by the teacher.
Assesment criteria:
The course is assessed on the basis of the weekly assignments.
Learning outcomes
The course objectives are to: review existing frameworks for modeling human cognition, including broad categories of symbolic, connectionist, and hybrid frameworks; study a particular framework in the context of illustrative psychological domains (e.g., memory, attention, language); build running simulation models of cognition and performance using this framework; explore how such models can be employed in real-world application domains such as intelligent tutoring and driving. As learning outcomes, students completing this course should be able to: describe existing frameworks for modeling human cognition; use an existing computational framework to build running simulation models of cognition and performance; describe how such models can be employed in real-world application domains.
Study materials
Video lectures, interactive notebooks, and supplementary reading.
Completion methods
Method 1
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Parts of the completion methods
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Teaching (5 cr)
Type:
Participation in teaching
Grading scale:
0-5
Language:
English