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Fall 2003 First day of classes for CMU & Pitt: Monday, August 25, 2003. Core courses: Cognitive Neuroscience,
CMU Computer Science 15-681 Machine Learning Fall: 12 units (undergraduate version)
Machine Learning is concerned with computer programs that automatically improve their performance through experience (e.g., programs that learn to spot high-risk medical patients, recognize human faces, detect credit card fraud, and drive autonomous robots). This course covers the theory and practical algorithms for machine learning from a variety of perspectives. We cover topics such as datamining, decision tree learning, neural network learning, statistical learning methods, genetic algorithms, Bayesian learning methods, explanation-based learning, and reinforcement learning. The course covers theoretical concepts such as inductive bias, the PAC learning framework, minimum description length principle, and Occam's Razor. Short programming assignments include hands-on experiments with various learning algorithms. Typical assignments include neural network learning for face recognition, and decision tree learning from databases of credit records. Prerequisite: 15-212, or permission of the instructor.
15-781 Machine Learning: 12 units (graduate version)
Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers the theory and practice of machine learning from a variety of perspectives. We cover topics such as learning decision trees, neural network learning, statistical learning methods, genetic algorithms, Bayesian learning methods, explanation-based learning, and reinforcement learning. The course covers theoretical concepts such as inductive bias, the PAC and Mistake-bound learning frameworks, minimum description length principle, and Occam's Razor. Programming assignments include hands-on experiments with various learning algorithms. Typical assignments include neural network learning for face recognition, and decision tree learning from databases of credit records. CMU Robotics 16-720 Section A, Computer Vision: 12 units
Description: This course deals with the science and engineering of computer vision, that is, the analysis of patterns in visual images of the world with the goal of reconstructing and understanding the objects and processes in the world that are producing them. The emphasis is on physical, mathematical, and information processing aspects of vision. Topics covered include image formation and representation, camera geometry and calibration, multi-scale analysis, segmentation, contour and region analysis, energy-based techniques, reconstruction of based on stereo, shading and motion, 3-D surface representation and projection, and analysis and recognition of objects and scenes using statistical and model-based techniques. The material is based on a recent graduate-level textbook augmented with research papers, as appropriate. The course involves considerable Matlab programming exercises. CMU Psychology 85-713 Human Information Processing and Artificial Intelligence: 9 units
Reading is a
composite of very complex cognitive skills. It is also an area in which there
has been rapid progress in understanding the process, its acquisition, and the
sources of difficulty and disability. This course examines research and
theories on sentence and text comprehension, word recogni-tion, individual
differences in reading ability, dyslexia, writing systems, eye fixations,
perception, instructional methods, and speed reading. 85-765 Cognitive Neuroscience: 9 units [CNBC core course]
This course will cover fundamental findings and approaches in cognitive neuroscience, with the goal of providing an overview of the field at an advanced level. Topics will include high-level vision, spatial cognition, working memory, long-term memory, learning, language, executive control, and emotion. Each topic will be approached from a variety of methodological directions, for example, computational modeling, cognitive assessment in brain-damaged humans, non-invasive brain monitoring in humans, and single-neuron recording in animals. Lectures will alternate with sessions in seminar format. Prerequisite: Permission of Instructor (Graduate standing or undergraduates must have strong prior background in at least one relevant discipline, and permission of instructor. 85-782 Consciousness and Cognition: 9 units
This course will examine the relationship between cognition and consciousness. One particular focus will be on the issue of how complex the processes that are largely unconsciously controlled may be and another is on the interaction of conscious and non-conscious processes in the control of cognition. We will also very briefly examine relevant ideas about consciousness that arise in other fields such as philosophy of mind and physics. The major topics to be included will be drawn from: the experience and functionality of consciousness, neuroscience approaches to consciousness, perceptual and attentional work on consciousness, cognition in altered states of consciousness (in particular, dreaming), implicit memory, and the proceduralization of higher level cognitive processes. The course will consist of our reading and discussing primary research literature from the above areas. There will be a number of short written assignments based on the weekly reading and a term paper. GRADUATE STUDENTS ONLY.
CMU Statistics 36-749 Experimental Design for Behavioral and Social Sciences: 12 units
Statistical aspects of the design and analysis of planned experiments are studied in this course. A clear statement of the experimental factors will be emphasized. The design aspect will concentrate on choice of models, sample size and order of experimentation. The analysis phase will cover data collection and computation, especially analysis of variance, and will stress the interpretation of results. In addition to weekly lecture, students will attend a computer lab once a week. Prerequisite: 36-202, 36-220, or 36-247 Pitt Mathematics NONE. NROSCI/MSNBIO 2100 Cellular and Molecular Neurobiology: CR HRS: 7.0 [CNBC core course]
This is a required course for students in the Program in Neuroscience, and also satisfies the CNBC core requirement in neurophysiology. The course is very demanding. For this reason, CNBC students not in the Neuroscience program might prefer to take Jon Johnson's undergraduate neurophysiology course in the Spring instead. The regular syllabus will be augmented with half a dozen supplementary lectures specifically for CNBC graduate students. The Cellular and Molecular course covers protein structure and function, gene expression, neuronal development, membrane properties, the action potential, synaptic transmission, and second messenger systems, and synaptic plasticity. It consists of a lecture section and a conference section; students should sign up for both. The conference section is devoted to discussion of papers in the primary literature. NROSCI 2011 Functional Neuroanatomy: CR HRS: 4.0
This course covers the basic structure of the central nervous system from spinal cord to cerebral cortex. The major sensory, motor and integrative neural systems of the human brain are discussed. Based on an understanding of normal neural connections and brain function, the anatomical and physiological basis of various neurological disorders of the nervous system will be explored. Special Enrollment Counseling is required for registration. Students should contact Dr. Sesack for permission to register.
NROSCI 3023 Seminar in Cognitive Neuroscience: CR HRS: 1.0 to 3.0
This is a journal club devoted to cognitive neuroscience.. Pitt
Psychology
PSY 2205 Psychopathology: CR HRS: 3.0
The aim of this course is to provide a critical background in research strategies, phenomena, empirical research, and models of adult psychopathology. The course emphasis will be on etiological and pathological research, with both psychological and biological findings to be discussed. Course concentration will be on the major psychopathologies with clinical onset in adulthood, including schizophrenia, affective disorders, anxiety, addictions, and eating disorders. Conceptual and methodological issues that cross diagnostic categories will be stressed. Treatment approaches and differential diagnosis will be covered but not emphasized.
PSY 2400 Human Cognition: Research Methods: CR HRS: 2.0
This course covers experimental research methods including proposing an experiment, literature search, experimental design, programming experiments, simple data analysis, research writing, and oral presentation. Specific research techniques for reaction time, memory and learning methods, protocol analysis, and human subject methods are covered. The course provides students experience with the technical skills for advanced research. The course will require a number of laboratory assignments, execute human experiment, write-up an experiment and an in-class final. |