Algorithms
In addition two versions of the course, Foundations of Algorithms, have been taught through the Johns Hopkins part time graduate programs:
- 605.421.31: Foundations of Algorithms (face-to-face)
- 605.421.81: Foundations of Algorithms (online)
A web site describing the course can be found here. Fundamentally, both courses are identical. The difference is in the mode of delivery. Creation of the online course enabled Hopkins to offer its first fully online engineering graduate degree--the Master of Science in Bioinformatics.
Artificial Intelligence
As artificial intelligence and machine learning are areas of research for me, I teach a number of courses that fall under these topics. The three courses of particular interest are as follows:
- CS 436: Artificial Intelligence
- CS 513: Computational Research Topics -- Currently focusing on structured probabilistic models
- CS 536: Advanced Artificial Intelligence -- Topics TBD
I am teaching an introductory, undergraduate course in artificial intelligence during the fall of 2008 at Montana State University. This course is an adaptation of the AI course taught at Johns Hopkins for almost 10 years. A web site for the course can be found here.
Machine Learning
The field of machine learning is explore through two different courses. One is offered through the part time graduate program at Johns Hopkins in an online setting, and the other is offered as a graduate seminar, jointly between Montana State and Johns Hopkins. The seminar is a "readings" course where those interested in machine learning gather once per week to discuss current papers in machine learning of interest to the group.
- CS 500-01: Research Seminar (full time)
- 605.746.31: Machine Learning (part time)
- 600.735: Seminar in Machine Learning (full time)
Evolutionary Computation
Currently, this course is only offered through the part time graduate program at Johns Hopkins and has the number 605.747.81. The course is in the process of being converted to an online course and is taught as an advanced seminar/research projects course where students get first-hand experience exploring and performing research in evolutionary computation. A web site describing this course can be found here.