Department
of Psychology
http://www.uncc.edu/cognisci/
Degree
Graduate Certificate
Coordinator:
Paula Goolkasian, Professor of Psychology
Graduate
Faculty
Boyd Davis, Professor of English
Bei-Tseng (Bill)
Marvin Croy, Associate Professor of Philosophy
George Demakis, Assistant Professor of Psychology
Mark Faust, Assistant Professor of Psychology
Paul Foos, Professor of Psychology
Jane Gaultney, Associate Professor of Psychology
Paula Goolkasian, Professor of Psychology
Mirsad Hadzikadic,
Dean,
Larry F. Hodges, Chair and Professor of Computer Science
Tony Jackson, Associate Professor of English
Susan Johnson, Associate Professor of Psychology
Yogendra Kakad, Professor of Electical and Computer Engineering
Kayvan Najarian, Assistant Professor of Computer Science
Anita Raja, Assistant Professor of Software and Information Systems
Alan Rauch, Associate Professor of English
Ralf Thiede, Associate Professor of English
Lori Van Wallendael, Associate Professor of Psychology
David Wilson, Assistant Professor of Software and Information Systems
Jing Xiao, Professor of Computer Science
GRADUATE CERTIFICATE IN COGNITIVE SCIENCE
The Cognitive Science Certificate Program will offer graduate students an opportunity for an interdisciplinary program of study. Their training will focus on an understanding of human cognitive processes and the means by which complex mental processes can be modeled or simulated by artificial systems. Cognitive science is a dynamic and rapidly evolving field that studies intelligent systems by synthesizing the knowledge and methodology from the fields of cognitive psychology, artificial intelligence, linguistics, philosophy of mind and cognitive neuroscience. Students will be provided with the conceptual framework and the technical skills necessary to enhance careers in research, teaching, business or government. Students completing the program will add an interdisciplinary perspective to the training received in their major, better preparing them for employment or further study in a variety of sciences and social sciences. The certificate may be pursued concurrently with another graduate degree program at UNC Charlotte.
Additional
Admission Requirements
The certificate program is open to all students who hold a bachelor’s degree from an accredited university and either:
1) are enrolled and in good standing in a graduate degree program at UNC Charlotte, or
2) have a minimum GPA of 3.0 for their undergraduate courses.
Application for the Cognitive Science Certificate Program is made through the Office of Graduate Admissions.
Certificate Requirements
The Cognitive Science Certificate Program involves 15 hours of coursework. Students must take the required introductory course and at least two of the disciplinary courses. The remaining hours may come from any of the other topics courses listed. A cumulative GPA of 3.0 will be required and at most one course with a grade of C may be allowed toward the certificate.
Required
PSYC/ITCS/ITIS 6216 Introduction to Cognitive Science
Disciplinary courses (Must take at least two)
PSYC6116 Cognition
ENG5263 Linguistics and Language Learning
PHIL6050 Philosophy of Mind
ITCS6150 Intelligent Systems
Topics
ENG6070 Semiotics & Interpretation of Signs
PSYC6015 Topics in Perception & Physiological Psychology,
PSYC5316 Cognitive Neuroscience
PSYC6115 Sensation and Perception
PSYC6102 Research Design and Quantitative Methods
ITCS5151 Intelligent Robotics
ITCS5152 Computer Vision
ITCS6153 Neural Networks
ITCS6156 Machine Learning
ITCS6010 Topics: Virtual Reality
ITCS6170 Logic for AI
ITCS6158 Natural Language Processing
ECGR5196 Introduction to Robotics
ECGR6102 Optimization of Engineering Designs
ECGR6266/ECGR8266 Neural Networks Theory and Design
CEGR5181 Human Factors in Traffic Engineering
Topics, seminars, or other courses in the cognitive sciences approved by the Program Coordinator.
Courses In Cognitive Science
CEGR 5181. Human Factors in Traffic Engineering. (3) Study of the driver’s and pedestrian’s relationship with the traffic system, including roadway, vehicle and environment. Consideration of the driving task, driver and pedestrian characteristics, performance and limitations with regard to traffic facility design and operation.
ECGR 5196. Introduction To Robotics. (3) Prerequisites: ECGR 2103 or MEGR 2101 and senior standing. Modeling of industrial robots including homogeneous transformations, kinematics, velocities, static forces, dynamics, computer animation of dynamic models, motion trajectory planning, and introduction to vision, sensors and actuators (dual-listed with MEGR 4127). (Fall)
ECGR 6102. Optimization of Engineering Designs. (3) Prerequisite: ECGR 5101 or consent of department. The development of computationally feasible algorithms for solving optimization problems in engineering designs. Introduction to non-linear programming methods; study of constrained and unconstrained problems, linear programming problems and other related topics. (On demand)
ECGR 6266/ 8266. Neural Networks Theory and Design. (3) Topics include: Neural network model and network architectures; single layers, multiple layers network, perceptron learning rules; supervised hebian learning; performance optimization; widrow hoff learning; backpropagation; associative learning; competitive learning; grossberg network; Hopfield network; application of neural network. (On demand)
ENGL 5263. Linguistics and Language Learning.
(3)
ENGL 6070. Topics in English. (3) Selected topics of literature and language. May be repeated for credit as topics vary and with English Department approval. (Fall, Spring)
ITCS 5151. Intelligent Robotics. (3) Prerequisites: ITCS 1215 and MATH 2164, or consent of the Department. General introduction to spatial descriptions and transformations, and manipulator position and motion. More study on robot planning, programming, sensing, vision, and CAD/CAM. (Odd, spring) (Evenings)
ITCS 5152. Computer Vision. (3) Prerequisites: ITCS 1215 or MATH 2164, or consent of the Department. General introduction to Computer Vision and its application. Topics include low level vision, 2D and 3D segmentation, 2D description, 2D recognition, 3D description and model-based recognition, and interpretation. (Odd, Spring) (Evenings)
ITCS 6153. Neural Networks. (3) Prerequisites: ITCS 6114. Topics include: Basic notions and models of artificial neural nets; single layer neural classifiers; multilayer one-way neural nets; single layer feedback networks; neural models of associative memory; self organizing neural nets; translation between neural networks and knowledge bases; applications of neural networks. (Even, Fall) (Evenings)
ITCS 6156. Machine Learning. (3) Prerequisite: ITCS 6150 or consent of the department. Machine learning methods and techniques including: acquisition of declarative knowledge; organization of knowledge into new, more effective representations; development of new skills through instruction and practice; and discovery of new facts and theories through observation and experimentation. (On demand)
ITCS 6010. Topics in Computer Science. (3) Prerequisite: consent of the department. Topics in computer science selected to supplement the regular course offerings. May be repeated for credit as topics vary. (On demand)
ITCS 6170. Logic for Artificial Intelligence. (3) Prerequisite: ITCS 6150 or consent of the department. Introduction to basic concepts of logic for artificial intelligence, including declarative knowledge, inference, resolution, non-monotonic reasoning, induction, reasoning with uncertain beliefs, distributed information systems, intelligent information systems, planning and intelligent-agent architecture. (On demand)
ITCS 6150. Intelligent Systems. (3) Prerequisites: full graduate standing or consent of the department. To introduce core ideas in AI. Heuristic versus algorithmic methods; problem solving; game playing and decision making; automatic theorem proving; pattern recognition; adaptive learning; projects to illustrate theoretical concepts. (Fall) (Evenings)
ITCS 6158. Natural Language Processing. (3) Prerequisite: ITCS 6150. Principles, methodologies, and programming methods of natural language processing including foundations of natural language understanding, namely: lexical, syntactic, and semantic analysis, discourse integration, and pragmatic and morphological analysis. (On demand)
PHIL 6050 - Philosophy of Mind . (3) This course addresses questions concerning the relationship between body and mind, the existence of other minds, the nature of consciousness, and the architecture of cognition. Approaches to these questions include traditional philosophical sources (emphasizing metaphysics and epistemology) and more recent developments in cognitive science (including the computational model of mind, mental representation,connectionist systems, and artificial intelligence). Also addressed are ethical and social issues involved in the design and implementation of intelligent systems. (Yearly)
PSYC 5316. Cognitive Neuroscience. (3) Prerequisite: graduate standing or permission of the instructor. Biological basis of consciousness and the neurobiology of mental processes by which we perceive, act, learn, and remember; representation of mental processes from electrophysiological and brain imaging techniques, clinical neurology, and computational science. (Alternate Years)
PSYC 6015. Topics in Perception and Physiological Psychology. (3) An examination of selected topics in the areas of sensation and perception, physiological and neuropsychology, with an emphasis on the applications to the areas of clinical, community, and industrial psychology. May be repeated for credit with the permission of department. (Alternate years)
PSYC 6102. Research Design and Quantitative Methods in Psychology. (3) Prerequisites: MATH 1222 and PSYC 2102 or equivalent. Experimental and correlational methods of psychological research, including single subject designs with emphasis on research design and the application of statistical methods to psychological research. (Fall)
PSYC 6115. Sensation and Perception. (3) Processes involved in receiving and interpreting sensory data including all the sensory systems with an emphasis on vision. (On Demand)
PSYC 6116. Cognition. (3) Concerned with how humans acquire information, retain information in memory, and use this information to reason and solve problems. Current emphases include memory, category learning, planning, concept formation, problem solving, mental models, and knowledge representation. (Alternate Years)
PSYC 6216/ITCS 6216/ITIS 6216. Introduction to Cognitive Science. (3) This course presents multiple perspectives on the study of intelligent systems. Broad coverage of such topics as philosophy of mind; human memory processes; reasoning and problem solving; artificial intelligence; language processing (human and machine); neural structures and processes; and vision. Also included is participation in the cognitive science seminar (Same as ITCS 6216, and ITIS 6216) (Fall Semester)