This course is part of Mind and Machine Specialization.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Mind and Machine Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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English
Tiếng Việt
What you'll learn
Understand the Turing test and its implications for AI
Analyze Searle's Chinese Room thought experiment
Explore historical and modern AI system developments
Evaluate computational complexity in cognitive problems
Examine the relationship between human and machine intelligence
Skills you'll gain
This course includes:
2.5 Hours PreRecorded video
9 assignments
Access on Mobile, Desktop, Tablet
FullTime access
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There are 4 modules in this course
This foundational course explores the intersection of cognitive science and artificial intelligence, examining how historical ideas about cognition shape our understanding of artificial systems. Students learn about key concepts including the Turing test, Searle's Chinese Room experiment, and computational approaches to understanding intelligence. The curriculum covers the history of automata, boundaries of machine intelligence, and fundamental problems in cognitive computation, providing a comprehensive introduction to both philosophical and practical aspects of AI and cognitive science.
Introduction
Module 1 · 37 Minutes to complete
Tests and Thought Experiments
Module 2 · 3 Hours to complete
A Hard Problem
Module 3 · 43 Minutes to complete
Cognitive Problems in Computational Terms
Module 4 · 2 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Mind and Machine Specialization
Instructor
Research Associate
Dr. David Quigley is a Research Associate in the Institute of Cognitive Science and an Assistant Professor - Adjunct in the Department of Computer Science at the University of Colorado Boulder. His research focuses on applying learning analytics techniques to develop machine learning models that analyze student activity and understanding in science classrooms. Dr. Quigley earned his Ph.D. from CU Boulder, where he contributed to projects such as the Inquiry Hub Research-Practice Partnership and the Chicago City of Learning initiative.Prior to his doctoral studies, Dr. Quigley completed his undergraduate and master’s degrees at Georgia Tech, working with the Contextual Computing Group on various projects related to human-computer interaction and educational technology.At CU Boulder, he teaches courses including "Computational Vision," "Interpersonal, Developmental, and Evolutionary Perspectives of the Mind," "Methods for Solving Problems," and "What is 'the mind' and what is artificial intelligence?" His work not only enhances educational practices but also contributes to a deeper understanding of how technology can support learning in science education.Dr. Quigley's contributions to the field of cognitive science and education technology position him as a key figure in advancing research on learning analytics and its practical applications in classroom settings.
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