436F646521
All programmers are playwrights and all computers are lousy actors.
These are the courses of significant content that have helped me most as a computer science student and showcase my work. They are ordered by first course in progress, then significance in the amount of work which is presentable.
In the Cognitive Science Capstone we are developing a project of modest scale which utilizes principles from Psychology and Computer Science. Since it is still early in the semester, more information will be available soon!
In web services we learned the basics of the protocols and services which define the web as it is today, including XML parsers in java (DOM and SAX), SOAP, WSDL, UDDI, and other useful services such as Google Web Toolkit. The course had a large final project of original design for which myself and one other person chose to write an application for displaying music trends across the world called AudioMappr!
This course used the principles learned in the first AI course such as LISP programming and a background of AI in leading the students through a term project of the students own design. I chose to write a genetic algorithm to solve the p-space complete Rush Hour game. The course expected biweekly presentations of progress and frequent demos to showcase what progress was being made. The course culminated with a final demo and paper worthy of publishing based on the work done.
Well known as the hardest course in the computer science curriculum at Oswego, each student wrote a version of the MiniJava compiler. The course material itself was very theory driven, with the actual implimentation being left to the student as coursework. This course was one of the most enligtening courses I have taken at Oswego and the in depth knowledge of how memory and processor registers are managed has really helped my programming.
A largely theory based course, this course used O'Reily and Munakata's book which trys to lead to an understanding of the human mind through computational modeling of its processes. The course gave a great overview of how the neurons in our brain actually work in contrast to how the computational models work. The course culminated in a research project in which I studied unsupervised learning neural networks and has become the basis for my Honors Thesis.
This course provides an introduction to LISP and Prolog in the context of artificial intelligence. The course largely consisted of programming toy type problems such as board games using heuristics and other look ahead algorithms. The most valuable part of this course was the introduction to LISP and the major concepts of AI such as intelligent agents.
A course based mostly in the theory of computational linguistics we learned about not only much of the linguistic structure of languages themselves but how to model them computationally, how to generate text and speech computationally as well as recognition of text and speech. The coursework was largely toy type problems in Prolog recognizing fairly rigid classes of sentences.