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Course descriptions, prerequisites and more...

Below you will find the list of courses offered through the College's schools, departments, and programs. This list includes important information about each course, including the course description, credit hours, prerequisites, repeatability, and more. Use the filters to narrow your search.

19 courses found. Showing results 1–10.
  • COGS-Q 101 Introduction to Cognitive Science (3 cr.) Introduction to the study of the human mind and intelligent systems using an integrative approach. Explores the nature of intelligence through simulations, robots, human experiments and philosophical inquiry. Topics include perception, consciousness, mental representations, and models of cognition and brain anatomy as each relates to cognition. Provides an overview for those students considering a major in Cognitive Science or a related field.
  • COGS-Q 240 Philosophical Foundations of the Cognitive and Information Sciences (4 cr.) Foundational introduction to the cognitive and information sciences. The primary themes are: (1) causal issues such as functional and computational architecture (e.g., modularity, effectiveness, and implementation, analog/digital), neuroscience, and embodied dynamics; and (2) semantic issues such as meaning, representation, content, and information flow. The role of both themes in logic, perception, computation, cognition, and consciousness. Throughout, an emphasis on writing, analysis, and exposition.
  • COGS-Q 260 Programming for the Cognitive and Information Sciences (3 cr.) R: Mastery of two years of high school algebra or the equivalent. Students will learn to write simple computer programs. Programming assignments will focus on the implementation of an important class of models from cognitive science, such as neural networks or production systems.
  • COGS-Q 301 Brain and Cognition (3 cr.) R: PSY-P 101. An introduction to the neural mechanisms underlying complex cognition, and a survey of topics in neuroscience related to cognition. The course provides a solid background in human biopsychology.
  • COGS-Q 320 Computation in the Cognitive and Information Sciences (3 cr.) P: COGS-Q 260, CSCI-C 200, CSCI-C 211, or CSCI-H 211 with a grade of B or higher. Develop computer programming skills, learn to write programs that simulate cognitive processes, and run experiments with human subjects. The relation between computation and intelligence and a selection of approaches from artificial intelligence will be explored.
  • COGS-Q 330 Perception/Action (3 cr.) P: PSY-P 101 or PSY-P 155 . Roboticists know that actions like catching a fly ball are exceedingly complex, yet people perform them effortlessly. How perceptual information is generated by and used in guiding such actions is covered, as are issues of motor coordination and control. Classes include laboratories on analysis of optic flow and limb movements. Credit given for only one of COGS-Q 330 or PSY-P 330.
  • COGS-Q 345 Animal Cognition (3 cr.) Introduction to the study of animal cognition. Reviews historical, theoretical, and philosophical perspectives on how animals think. Explores debates about specific aspects of cognition, including whether and how animals reason, whether they have memory and concepts, whether they can use tools, whether they communicate or have "language," whether they have consciousness, behave altruistically, and have morals.
  • COGS-Q 350 Mathematics and Logic for the Cognitive and Information Sciences (4 cr.) R: Mastery of two years of high school algebra or the equivalent. An introduction to the suite of mathematical and logical tools used in the cognitive and information sciences, including finite mathematics, automata and computability theory, elementary probability, and statistics, together with short introductions to formal semantics and dynamical systems. Credit given for only one of COGS-Q 350 or COGS-Q 250.
  • COGS-Q 351 Introduction to Artificial Intelligence and Computer Simulation (3 cr.) P: CSCI-C 211, CSCI-H 211, or consent of instructor. A survey of techniques for machine intelligence and their relation to human intelligence. Topics include modeling techniques, neural networks and parallel processing systems, problem-solving methods, knowledge representation, expert systems, vision, heuristics, production systems, speech perception, and natural language understanding. Students who have completed both COGS-C 463 and COGS-C 464 are exempted from taking this course. Credit given for only one of COGS-Q 351 or CSCI-B 351.
  • COGS-Q 355 Neural Networks and the Brain (3 cr.) P: COGS-Q 260, CSCI-C 211, or CSCI-H 211 with a grade of B or higher; and one of COGS-Q 350, COGS-Q 351, or CSCI-B 351; or consent of instructor. An overview of common neural networks, especially deep learning. Practical computer programming exercises, mainly in Python, provide training in how to implement neural networks to solve real-world problems. Students will be able to implement practical neural network solutions and evaluate their suitability as models of the brain and cognition.