Computing Practice and Theory

REVISED

Spring 2013 quarter

Faculty

Richard Weiss mathematics, computer science , Aaron Skomra computer science , Judith Cushing computer science

Fields of Study

computer science

Preparatory for studies or careers in

computer science.

Prerequisites

Computer Science Foundations (including discrete mathematics) or equivalent experience.

Description

This project-oriented program for intermediate and advanced computer science students will weave together the theory and practice of two cross-cutting topics in computer science, pattern analysis and modeling, in the context of eScience.  The overriding question of the program is how pattern analysis and modeling, broadly defined, might advance the natural and physical sciences, particularly in the areas of environmental science and climate change studies.    

The program will meet four days a week for lectures, seminar, workshops, and labs.  Particularly in seminar, students will share responsibility for presenting and discussing concepts from the readings and lectures.  One seminar group will focus on applying computation, visualization, data mining, and statistics to problems faced by scientists.  Another group will apply statistics to machine learning and network analysis, and a third will focus on another area, to be determined by faculty and student expertise and interest.  This program will include a guest lecture series that focuses on (how computers are used in) modeling environmental systems.  

In addition to seminar, the program has two disciplinary components and a project.  The disciplinary foci will be 1) the theory and practice of statistics, and 2) data mining, machine learning and pattern recognition.  Students will also be expected to apply the computing discipline of their choice to a research paper, or a programming or statistics project, and present their work. To facilitate projects, faculty will organize small research groups that meet twice weekly (once with a faculty advisor) to discuss progress. Projects will begin with a proposal and bibliography, and should be either small enough in scope to be completed in one quarter or a self-contained part of a larger project.  Possible CS subdisciplines in which faculty will encourage project work include data mining, machine learning, database systems, data visualization (especially visual analytics), networking, security, algorithmic complexity, and formal languages.

This program aims to give students from Computability , Computer Science Foundations , and Music, Math and Cybernetics opportunities to continue work begun in those programs. Students who have taken Computability will be expected to complete more advanced work.

Academic Website

http://blogs.evergreen.edu/cpat/

Location

Olympia

Online Learning

Enhanced Online Learning

Books

Greener Store

Upper Division Science Credit

Students seeking to earn upper division credit must complete the "Seeking Upper Division" form during the first week of the quarter. This form will ask questions that allow students to describe the area of their proposed project work and their competency to complete work at the upper division level (e.g., completion of 2 quarters of Computability).  The form will be posted on the program web site about mid March.

Offered During

Day

Program Revisions