Classes

with apologies and thanks To Robert Balder: visit partiallyclips.com

As a professor, I sometimes find myself acting as an instructor in a formal setting. I tend to teach senior-level undergraduate and graduate courses, mostly, but I have been known to teach lower-division courses as well. Actually, now that I'm mired in the wonders of administration, I no longer teach on campus, but I do teach online courses out of sheer love, and possibly for profit.

Here is a list of pointers to the classes I teach, or will teach, or have taught (or something) for those of you in my classes or trying to figure out how a class from me might be. In the meantime, I think the comic strip above nicely captures my teaching philosophy.

2020-present

Fall

CS 7641 Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Summer

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Spring

CS 7641
Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

2019

Fall

CS 7641 Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Summer

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates

CS 7641
Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

2018

Fall

CS 7641 Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Summer

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates

CS 7641
Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

2017

Fall

CS 7641 Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Summer

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates (SOUP version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates

CS 7641
Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 7642 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

2016

Fall

CS 7641 Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 8803 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Summer

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates (SOUP version!)

CS 8803 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates

CS 7641
Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 8803 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

2015

Fall

CS 7641 Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

CS 8803 Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates

CS 7641
Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

2014

Fall

CS 7641 Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates

CS 7641
Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

2013

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning.

2012

Spring

CS 4641
Machine Learning: An introductory course in approaches in Machine Learning, now in undergraduate-only flavor.

2011

Fall

CS 1100 Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. Cedric Stallworth and I are the class organizers.

Spring

CS 7641
CS 4641
Machine Learning: An introductory course in approaches in Machine Learning. There is an undergraduate and a graduate section with slightly different assignments.

2010

Fall

CS 1100 Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. Cedric Stallworth and I are the class organizers.

Spring

CS 7641
CS 4641
Machine Learning: An introductory course in approaches in Machine Learning. There is an undergraduate and a graduate section with slightly different assignments.

2009

Fall

CS 1100 Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. Cedric Stallworth and I are the class organizers.

Spring

CS 7/4641 Machine Learning: An introductory course in approaches in Machine Learning.

2008

Fall

CS 1100 Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. I'm the class organizer.

Spring

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 7/4641 Machine Learning: An introductory course in approaches in Machine Learning.

2007

Fall

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 4731 Game AI: An introductory course in applications of Artificial Intelligence to Game and Narrative.

CS 1100 Freshman Leap: A semi-formal series of seminars for incoming CS students, arising from an earlier incarnation as 1800. I'm the class organizer.

Spring

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 7/4641 Machine Learning: An introductory course in approaches in Machine Learning.

CS 4480/8dfx DVFX Sports Edition: A course on DVFX targeted towards sports data. This is really Irfan Essa's class, but my name is on it because there will be some opportunity for machine learning.

2006

Fall

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 3600 Introduction to AI: An introductory course in approaches in Artificial Intelligence and Intelligent Systems.

CS 1100 Freshman Leap: A semi-formal series of seminars for incoming CS students, arising from an earlier incarnation as 1800. I'm the class organizer.

Spring

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 7/4641 Machine Learning: An introductory course in approaches in Machine Learning.

CS 8803 APIE Adaptive Personalized Information Environments: This is a class on one of my major research interests, and happily co-taught with Jeff Pierce. It's a project-driven course, and is now on its final step towards being an official course.

2005

Fall

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 7641 Machine Learning: An introductory graduate course in approaches in Machine Learning.
CS 1100 Freshman Seminar: An informal series of seminars for incoming CS freshmen, co-ordinated by Merrick Furst.

Spring

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 7/4641 Machine Learning: An introductory course in approaches in Machine Learning. There are ungraduate and graduate sections.

CS 4002 Robots and Society: This is a course about the impact of robots and other intellgent agents on our organizations and our culture. This counts as an alternative to 4001, the required senior-level course on ethics.

2004

Fall

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 1801 Freshman Seminar: An informal series of seminars for incoming CS freshmen, co-ordinated by Merrick Furst.

Summer

CS 1371B Computing for Engineers: An introductory programming and computing course, specifically for Engineers (lots of Matlab!).

Spring

CS 8001 ISR Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.

CS 7641 Machine Learning: A graduate introductory course in approaches in Machine Learning.

CS 8803 APIE Adaptive Personalized Information Environments: This is a class on one of my major research interests, and happily co-taught with Jeff Pierce. It's a project-driven course, and continues its march towards being an official course.

2003

Fall

CS 4600 A/B Introduction to Intelligent Systems: The introductory undergraduate course for Artificial Intelligence and Intelligent Systems.

CS 1801 Freshman Seminar: An informal series of seminars for incoming CS freshmen, co-ordinated by Merrick Furst.

Spring

CS 8802B Adaptive Personalized Information Environments: This is a class on one of my major research interests, and happily co-taught with Jeff Pierce. It's a project-driven course, and we plan to turn it into a "real" course over the next two years.

CS 4000D Computerization in Society: This is a required senior-level course that "examines computing as a social process with emphasis on ethical issues and the social impact of computerization on local and global organizations." Personally, I think those issues are better described as policy than ethical, but we'll see as the semester goes along.

2020-present
Fall
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Summer
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Spring
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
2019
Fall
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Summer
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
2018
Fall
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Summer
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
2017
Fall
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Summer
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates (SOUP version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 7642	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
2016
Fall
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 8803	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Summer
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates (SOUP version!)
CS 8803	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 8803	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
2015
Fall
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
CS 8803	Reinforcement Learning and Decision Making: A course in approaches in Reinforcement Learning and Decision Making for graduates (OMSCS version!)
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

2014
Fall
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning... for undergraduates
CS 7641	Machine Learning: An introductory course in approaches in Machine Learning... for graduates (OMSCS version!)

2013
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning.

2012
Spring
CS 4641	Machine Learning: An introductory course in approaches in Machine Learning, now in undergraduate-only flavor.

2011
Fall
CS 1100	Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. Cedric Stallworth and I are the class organizers.
Spring
CS 7641 CS 4641	Machine Learning: An introductory course in approaches in Machine Learning. There is an undergraduate and a graduate section with slightly different assignments.

2010
Fall
CS 1100	Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. Cedric Stallworth and I are the class organizers.
Spring
CS 7641 CS 4641	Machine Learning: An introductory course in approaches in Machine Learning. There is an undergraduate and a graduate section with slightly different assignments.

2009
Fall
CS 1100	Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. Cedric Stallworth and I are the class organizers.
Spring
CS 7/4641	Machine Learning: An introductory course in approaches in Machine Learning.

2008
Fall
CS 1100	Freshman Leap: A semi-formal series of seminars for incoming CS students that introduces a variety of foundational, motivational and topical subjects for the computationalist. I'm the class organizer.
Spring
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 7/4641	Machine Learning: An introductory course in approaches in Machine Learning.

2007
Fall
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 4731	Game AI: An introductory course in applications of Artificial Intelligence to Game and Narrative.
CS 1100	Freshman Leap: A semi-formal series of seminars for incoming CS students, arising from an earlier incarnation as 1800. I'm the class organizer.
Spring
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 7/4641	Machine Learning: An introductory course in approaches in Machine Learning.
CS 4480/8dfx	DVFX Sports Edition: A course on DVFX targeted towards sports data. This is really Irfan Essa's class, but my name is on it because there will be some opportunity for machine learning.

2006
Fall
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 3600	Introduction to AI: An introductory course in approaches in Artificial Intelligence and Intelligent Systems.
CS 1100	Freshman Leap: A semi-formal series of seminars for incoming CS students, arising from an earlier incarnation as 1800. I'm the class organizer.
Spring
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 7/4641	Machine Learning: An introductory course in approaches in Machine Learning.
CS 8803 APIE	Adaptive Personalized Information Environments: This is a class on one of my major research interests, and happily co-taught with Jeff Pierce. It's a project-driven course, and is now on its final step towards being an official course.

2005
Fall
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 7641	Machine Learning: An introductory graduate course in approaches in Machine Learning.
CS 1100	Freshman Seminar: An informal series of seminars for incoming CS freshmen, co-ordinated by Merrick Furst.
Spring
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 7/4641	Machine Learning: An introductory course in approaches in Machine Learning. There are ungraduate and graduate sections.
CS 4002	Robots and Society: This is a course about the impact of robots and other intellgent agents on our organizations and our culture. This counts as an alternative to 4001, the required senior-level course on ethics.

2004
Fall
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 1801	Freshman Seminar: An informal series of seminars for incoming CS freshmen, co-ordinated by Merrick Furst.
Summer
CS 1371B	Computing for Engineers: An introductory programming and computing course, specifically for Engineers (lots of Matlab!).
Spring
CS 8001 ISR	Intelligent Systems Reading Group: An ongoing reading group on research papers in IS.
CS 7641	Machine Learning: A graduate introductory course in approaches in Machine Learning.
CS 8803 APIE	Adaptive Personalized Information Environments: This is a class on one of my major research interests, and happily co-taught with Jeff Pierce. It's a project-driven course, and continues its march towards being an official course.

2003
Fall
CS 4600 A/B	Introduction to Intelligent Systems: The introductory undergraduate course for Artificial Intelligence and Intelligent Systems.
CS 1801	Freshman Seminar: An informal series of seminars for incoming CS freshmen, co-ordinated by Merrick Furst.
Spring
CS 8802B	Adaptive Personalized Information Environments: This is a class on one of my major research interests, and happily co-taught with Jeff Pierce. It's a project-driven course, and we plan to turn it into a "real" course over the next two years.
CS 4000D	Computerization in Society: This is a required senior-level course that "examines computing as a social process with emphasis on ethical issues and the social impact of computerization on local and global organizations." Personally, I think those issues are better described as policy than ethical, but we'll see as the semester goes along.