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Faculty Course Questionnaires - CSCI 5622


CSCI 5622 (3). Machine Learning.

Trains students to build computer systems that learn from experience. Includes the three main subfields: supervised learning, reinforcement learning and unsupervised learning. Emphasizes practical and theoretical understanding of the most widely used algorithms (neural networks, decision trees, support vector machines, Q-learning). Covers connections to data mining and statistical modeling. A strong foundation in probability, statistics, multivariate calculus, and linear algebra is highly recommended. Prerequisites: Graduate standing or consent of instructor.

CSCI 5622. Machine Learning
Burl, Michael
Fall 2002 (sec. 001) MidMidHiLo·
Fall 2003 (sec. 001) HiHiHiMidStar
Grudic, Gregory
Fall 2001 (sec. 001) HiHiHiHiHi
Fall 2004 (sec. 002) HiHiHiHiStar
Fall 2005 (sec. 001) HiHiHiHiStar
Fall 2006 (sec. 001) HiHiMid4-6Star
Spring 2008 (sec. 001) HiHiHi7-9Hi
Fall 2008 (sec. 001) HiHiHi7-9Hi
Hacioglu, Kadri
Fall 1998 (sec. 001) HiHiHiHi·
Fall 1999 (sec. 001) MidMidMidMidStar
Mozer, Michael
Fall 1997 (sec. 001) HiHiHiHi·
Fall 1999 (sec. 001) MidMidHiHiStar
Spring 2001 (sec. 001) StarHiHiHiStar
Nielsen, Rodney
Fall 2009 (sec. 002) MidMidHi10-12Hi
Singh, Satinder
Fall 1997 (sec. 001) HiHiHiHiHi

The Faculty Course Questionnaire (FCQ) program allows students to rate their instructors and courses at the end of each term. It provides information to instructors for teaching improvement, to students for course selection, and to deans and chairs for management. Students evaluate each course-section in three ways: multiple-choice "core" questions printed on all FCQ forms, multiple-choice optional questions selected and/or written by the instructor and/or the department, and several open-ended items which request student comments.

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Department of Computer Science
College of Engineering and Applied Science
University of Colorado Boulder
Boulder, CO 80309-0430 USA
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May 5, 2012 (13:25)